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Background: Mild cognitive impairment (MCI) may lead to difficulty maintaining postural stability and balance during locomotion. This heightened susceptibility to falls is particularly evident during tasks such as obstacle negotiation, which demands efficient motor planning and reallocation of attentional resources. This study proposed a multi-objective optimal control (MOOC) technique to assess the changes in motor control strategies during obstacle negotiation in older people affected by amnestic MCI. Methods: Motion data from 12 older adults with MCI and 12 controls when crossing obstacles were measured using a motion capture system, and used to obtain the control strategy of obstacle-crossing as the best compromise between the conflicting objectives of the MOOC problem, i.e., minimising mechanical energy expenditure and maximising foot-obstacle clearance. Comparisons of the weighting sets between groups and obstacle heights were performed using a two-way analysis of variance with a significance level of 0.05. Results: Compared to the controls, the MCI group showed significantly lower best-compromise weightings for mechanical energy expenditure but greater best-compromise weightings for both heel- and toe-obstacle clearances. This altered strategy involved a trade-off, prioritising maximising foot-obstacle clearance at the expense of increased mechanical energy expenditure. The MCI group could successfully navigate obstacles with a normal foot-obstacle clearance but at the cost of higher mechanical energy expenditure. Conclusions: MCI alters the best-compromise strategy between minimising mechanical energy expenditure and maximising foot-obstacle clearances for obstacle-crossing in older people. These findings provide valuable insights into how MCI impacts motor tasks and offer potential strategies for mitigating fall risks in individuals with MCI. Moreover, this approach could serve as an assessment tool for early diagnosis and a more precise evaluation of disease progression. It may also have applications for individuals with impairments in other cognitive domains. [ABSTRACT FROM AUTHOR]

Background: Walking speed, a key element of gait analysis, is essential for evaluating the biomechanics of the musculoskeletal system and is typically assessed on flat surfaces, such as walkways or treadmills. While many authors have compared the differences and similarities between treadmill and overground walking, no studies have yet investigated the differences between treadmill gait analysis at self-selected speed (SS) and overground simulated speed (OS). The hypothesis is that accurate kinematic measurements depend on selecting the correct gait speed; however, a mismatch between the perceived comfortable treadmill speed and actual overground speed may affect the accuracy of treadmill gait analyses. This study aimed to assess treadmill gait in healthy young adults by comparing the SS with the OS. The objectives were to determine whether participants could match SS with OS on a treadmill, examine sex differences in gait kinematics and spatiotemporal parameters (KSP) at different speeds, and identify which speed better reflects natural gait kinematics. Methods: A total of 60 healthy men and 70 healthy women, aged 22–35 years, participated in this cross-sectional study to investigate the gait kinematics and spatiotemporal differences between the SS and OS. Student's t-test, Bonferroni adjustment, Cohen's effect size, and quadratic regression were employed to analyse differences across walking speeds and groups. Results: A discrepancy between OS and SS was observed in 66.4% of the participants. Our findings revealed that the adjusted R² values for KSP at SS were consistently greater than those at OS, suggesting that SS offers a more robust and accurate representation of gait kinematics, whereas OS is less reliable. Conclusions: These findings underscore the importance of individualized speed selection in gait analysis, as it significantly impacts the accuracy of kinematic and spatiotemporal measurements. This insight is pivotal for clinicians and researchers to develop more effective rehabilitation strategies and comprehensively understand gait dynamics. [ABSTRACT FROM AUTHOR]

Background: Gait variables assessed by inertial measurement units (IMUs) show promise as screening tools for aging-related diseases like sarcopenia. The main aims of this systematic review were to analyze and synthesize the scientific evidence for screening sarcopenia based on gait variables assessed by IMUs, and also to review articles that investigated which gait variables assessed by IMUs were related to sarcopenia. Methods: Six electronic databases (PubMed, SportDiscus, Web of Science, Cochrane Library, Scopus and IEEE Xplore) were searched for journal articles related to gait, IMUs and sarcopenia. The search was conducted until December 5, 2023. Titles, abstracts and full-length texts for studies were screened to be included. Results: A total of seven articles were finally included in this review. Despite some methodological variability among the included studies, IMUs demonstrated potential as effective tools for detecting sarcopenia when coupled with artificial intelligence (AI) models, which outperformed traditional statistical methods in classification accuracy. The findings suggest that gait variables related to the stance phase such as stance duration, double support time, and variations between feet, are key indicators of sarcopenia. Conclusions: IMUs could be useful tools for sarcopenia screening based on gait analysis, specifically when artificial intelligence is used to process the recorded data. However, more development and research in this field is needed to provide an effective screening tool for doctors and health systems. [ABSTRACT FROM AUTHOR]

Introduction: This study evaluates the gait analysis obtained by Inetial Measurement Units (IMU) before and after surgical management of Spastic Equino Varus Foot (SEVF) in hemiplegic post-stroke patients and to compare it with the functional results obtained in a monocentric prospective cohort. Methods: Patients with post-stroke SEVF, who underwent surgery in a single hospital between November 2019 and December 2021 were included. The follow-up duration was 6 months and included a functional analysis using Goal Attainment Scaling (GAS) and a Gait analysis using an innovative Multidimensional Gait Evaluation using IMU: the semiogram. Results: 20 patients had a gait analysis preoperatively and at 6 months postoperatively. 90% (18/20) patients had a functional improvement (GAS T score ≥ 50) and 50% (10/20) had an improvement in walking technique as evidenced by the cessation of the use of a walking aid (WA). In patients with functional improvement and modification of WA the change in the semiogram area was + 9.5%, sd = 27.5%, and it was + 15.4%, sd = 28%. In the group with functional improvement without change of WA. For the 3 experiences (two patients) with unfavorable results, the area under the curve changed by + 2.3%, -10.2% and − 9.5%. The measurement of the semiogram area weighted by average speed demonstrated very good reproducibility (ICC(1, 3) = 0.80). Discussion: IMUs appear to be a promising solution for the assessment of post-stroke hemiplegic patients who have undergone SEVF surgery. They can provide a quantified, objective, reliable in individual longitudinal follow up automated gait analysis solution for routine clinical use. Combined with a functional scale such as the GAS, they can provide a global analysis of the effect of surgery. [ABSTRACT FROM AUTHOR]

The recovery process after tibial plateau fractures varies, with some patients experiencing persistent gait asymmetries for a long period of time. The aim of this study is to analyse knee joint kinematics and kinetics post-fracture using a linear mixed-effects model, assessing 26 participants over 24 months (aged 45, range 26–63), and an age-matched control group (aged 47, range 26–62). Participants underwent three-dimensional gait analysis at 6-, 12- and 24-months post-injury. Controls participated in the gait analysis on one occasion. Six gait variables related to knee joint kinematics and kinetics were analysed with a linear mixed-effects model. The model was constructed to determine if there was a differential improvement over time between the injured and the non-injured legs across the six variables, referred to as an interaction effect. If no interaction effect was observed, the model assessed whether there was a side difference between the legs and if there was any improvement over time in both legs. Additionally, non-parametric tests were performed to assess differences between the non-injured leg and the control group across the six variables 24 months after injury. The findings revealed an interaction effect in terms of cumulative absorbed power (p = 0.02, side difference p = 0.06). Other variables showed no interaction effects. Although a side difference between legs was observed for all variables (p < 0.001), only the variables regarding generated power exhibited improvements over time (p = 0.02 respectively). Minimal knee flexion, range of motion, and maximal extending knee joint moment showed no improvements over time. At the 24-month follow-up, the maximal extending knee joint moment was the only variable that differed between the non-injured leg and controls, with increased moment observed for the non-injured leg compared with the controls (p = 0.03). Taken together, two years post-fracture, patients demonstrated pronounced side differences between the injured and non-injured legs with worse ability to extend the knee joint and to generate power in the injured leg. While the kinetic variables improved over time, there were no improvements observed in kinematic variables. Moreover, the non-injured leg performed similarly to healthy controls in terms of minimal knee flexion, range of motion, and generated and absorbed power. [ABSTRACT FROM AUTHOR]

Beyond qualitative assessment, gait analysis involves the quantitative evaluation of various parameters such as joint kinematics, spatiotemporal metrics, external forces, and muscle activation patterns and forces. Utilizing multibody dynamics-based musculoskeletal (MSK) modeling provides a time and cost-effective non-invasive tool for the prediction of internal joint and muscle forces. Recent advancements in the development of biofidelic MSK models have facilitated their integration into clinical decision-making processes, including quantitative diagnostics, functional assessment of prosthesis and implants, and devising data-driven gait rehabilitation protocols. Through an extensive search and meta-analysis of over 116 studies, this PRISMA-based systematic review provides a comprehensive overview of different existing multibody MSK modeling platforms, including generic templates, methods for personalization to individual subjects, and the solutions used to address statically indeterminate problems. Additionally, it summarizes post-processing techniques and the practical applications of MSK modeling tools. In the field of biomechanics, MSK modeling provides an indispensable tool for simulating and understanding human movement dynamics. However, limitations which remain elusive include the absence of MSK modeling templates based on female anatomy underscores the need for further advancements in this area. [ABSTRACT FROM AUTHOR]

Background: Multiple system atrophy (MSA) is recognized as an atypical Parkinsonian syndrome, distinguished by a more rapid progression than that observed in Parkinson's disease. Unfortunately, the prognosis for MSA remains poor, with a notable absence of globally recognized effective treatments. Although preliminary studies suggest that transcranial magnetic stimulation (TMS) could potentially alleviate clinical symptoms in MSA patients, there is a significant gap in the literature regarding the optimal stimulation parameters. Furthermore, the field lacks consensus due to the paucity of robust, large-scale, multicenter trials. Methods: This investigation is a multi-center, randomized, double-blind, sham-controlled trial. We aim to enroll 96 individuals diagnosed with MSA, categorized into Parkinsonian type (MSA-P) and cerebellar type (MSA-C) according to their predominant clinical features. Participants will be randomly allocated in a 1:1 ratio to either the TMS or sham stimulation group. Utilizing advanced navigation techniques, we will ensure precise targeting for the intervention, applying theta burst stimulation (TBS). To assess the efficacy of TBS on both motor and non-motor functions, a comprehensive evaluation will be conducted using internationally recognized clinical scales and gait analysis. To objectively assess changes in brain connectivity, functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) will be employed as sensitive indicators before and after the intervention. Discussion: The primary aim of this study is to ascertain whether TBS can alleviate both motor and non-motor symptoms in patients with MSA. Additionally, a critical component of our research involves elucidating the underlying mechanisms through which TBS exerts its potential therapeutic effects. Ethics and dissemination: All study protocols have been reviewed and approved by the First Affiliated Medical Ethics Committee of the Air Force Military Medical University (KY20232118-F-1). Trial registration: Chinese Clinical Trial Registry ChiCTR2300072658. Registered on 20 June 2023. [ABSTRACT FROM AUTHOR]

Background: Total knee replacement (TKA) is a frequent modality performed in patients with knee osteoarthritis (OA). The aim of this study was to perform a meta-analysis and systematic review to evaluate the efficacy after TKA by gait analysis in patients with OA. Methods: PubMed, EMBASE, the Cochrane library, and Web of Science were searched for relevant studies from inception to July 2024. STATA SE 14.0 software was used for statistical analysis according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA 2020) guideline. Results: A total of 2525 reports were identified with 24 studies meeting pre-designed inclusion criteria. Several gait parameters were investigated. In patients with knee OA after TKA, there existed an increase in the Max knee flexion (WMD, 3.12; 95% CI, 0.93 to 5.32; I2 = 73.9%, P < 0.001), the Cadence (WMD, 4.05; 95% CI, 2.28 to 5.82; I2 = 48.9%, P = 0.068), the stride length (WMD, 0.05; 95% CI, 0.01 to 0.09; I2 = 77.1%, P < 0.001), the walking speed (WMD, 0.08; 95% CI, 0.02 to 0.14; I2 = 93.3%, P < 0.001), and the step length (WMD, 0.04; 95% CI, 0.00 to 0.07; I2 = 89.3%, P < 0.001) while a decrease in the double support time (WMD, -0.04; 95% CI, − 0.08 to -0.01; I2 = 0.0%, P = 0.585). Besides, no statistically significant differences were observed in the Knee range of motion (ROM), the Max knee rotation at stance phase, the Max knee extension, the step width, the stride time and the step time. Sensitivity analysis showed that all the results were robust. Conclusions: In summary, the study found that, in patients with knee OA undergoing TKA may have great effects on improving gait parameters. If there are more high-quality studies in the future, we should make a more comprehensive evaluation of walking function by gait analysis together with other evaluation systems such as muscle strength and proprioception measurement. [ABSTRACT FROM AUTHOR]

Background: The loss of gait automaticity is a key cause of motor deficits in Parkinson's disease (PD) patients, even at the early stage of the disease. Action observation training (AOT) shows promise in enhancing gait automaticity. However, effective assessment methods are lacking. We aimed to propose a novel gait normalcy index based on dual task cost (NIDTC) and evaluate its validity and responsiveness for early-stage PD rehabilitation. Methods: Thirty early-stage PD patients were recruited and randomly assigned to the AOT or active control (CON) group. The proposed NIDTC during straight walking and turning tasks and clinical scale scores were measured before and after 12 weeks of rehabilitation. The correlations between the NIDTCs and clinical scores were analyzed with Pearson correlation coefficient analysis to evaluate the construct validity. The rehabilitative changes were assessed using repeated-measures ANOVA, while the responsiveness of NIDTC was further compared by t tests. Results: The turning-based NIDTC was significantly correlated with multiple clinical scales. Significant group-time interactions were observed for the turning-based NIDTC (F = 4.669, p = 0.042), BBS (F = 6.050, p = 0.022) and PDQ-39 (F = 7.772, p = 0.011) tests. The turning-based NIDTC reflected different rehabilitation effects between the AOT and CON groups, with the largest effect size (p = 0.020, Cohen's d = 0.933). Conclusion: The turning-based NIDTC exhibited the highest responsiveness for identifying gait automaticity improvement by providing a comprehensive representation of motor ability during dual tasks. It has great potential as a valid measure for early-stage PD diagnosis and rehabilitation assessment. Trial registration Chinese Clinical Trial Registry: ChiCTR2300067657 [ABSTRACT FROM AUTHOR]

Background: Distal femur osteotomies are a well known and valuable treatment option to manage valgus malalignment with unicompartmental arthritis. Early postoperative complications are well known, and risk factors, such as pulmonary diseases, smoke, high dependent functional status, and body mass index, have been studied, but no study is available about osteotomies when gait is abnormal because of neurodegenerative conditions or when mineral density is below the normal rate. Case presentation: We report the case of a 44 year-old female Mediterranean patient who underwent a biplanar distal femur opening wedge osteotomy surgery following a lateral meniscus total removal, which led to the subsequent development of lateral compartment osteoarthritis and pain, despite general comorbidities, such as multiple sclerosis. Additionally, 2 months later a supracondylar femur fracture above the previously applied Tomofix® plate was reported. Fracture was treated by applying a LCP condylar 16 hole (336 mm) plate, a structural fibular graft, and strut fibular graft on the opposite side. Conclusion: The overall aim of this case report is to provide a lesson to surgeons who want to perform a realignment surgery of the lower limb in patients with abnormal gait. Not only mechanical axes are to be considered, but also bone density, patient's gait, and load force distribution along the bone stock. Emerging literature on three-dimensional cutting guides fails to account for these factors, thus promoting a standardized approach to surgery across all patients. The present case highlights a patient with low bone density and abnormal force distribution resulting from a pathologic neurodegenerative gait. In such cases, treatment decisions must carefully consider the biomechanical vulnerabilities of the native bone and the distribution of vector forces. These conditions must lead the choice toward a longer plate if an osteotomy is indicated, because surgery is more likely to fail. [ABSTRACT FROM AUTHOR]

Background: Gait ability can be objectively assessed using gait analysis. Three-dimensional gait analysis, the most commonly used analytical method, has limitations, such as a prolonged examination, high system costs, and inconsistently reported gait symmetry in patients with knee osteoarthritis (OA). Therefore, we aimed to evaluate the gait symmetry and changes before and after unilateral total knee arthroplasty (TKA) using the Walkway analyzer, a sheet-type gait analyzer. Methods: The healthy group included 38 participants from the Locomotor Frailty and Sarcopenia Registry study with lower limb pain or Kellgren–Lawrence classification grade 3 or 4 OA. The OA group included 34 participants from the registry study who underwent unilateral TKA. The walking speed, step length, step width, cadence, stride time, stance time, swing phase time, double-limb support phase time, stride, step length, and step width were analyzed per side using the Walkway gait analyzer. Results: No significant differences between the right and left sides were observed in the healthy group. In the OA group, the time indices and stance phase (p = 0.011) and the double-limb support phase time (p = 0.039) were longer on the contralateral side and the swing phase was longer on the affected side (p = 0.004) pre-operatively. However, these differences disappeared post-operatively. There were no significant differences in the spatial indices. Thus, this study revealed that patients undergoing unilateral TKA had an asymmetric gait pre-operatively, with a time index compensating for the painful side, and an improved symmetric gait post-operatively. Conclusions: The Walkway analyzer employs a simple test that requires only walking; hence, it is expected to be used for objective evaluation in actual clinical practice. [ABSTRACT FROM AUTHOR]

Background: The two most commonly instrumented gait analysis tools used are Optical Motion Capture systems (OMC) and Inertial Measurement Units (IMU). To date, OMC based gait analysis is considered the gold-standard. Still, it is space-, cost-, and time-intense. On the other hand IMU systems are more cost- and time effective but simulate the whole foot as a single segment. To get a more detailed model of the foot and ankle, a new 2-segment foot model using IMU was developed, comparable to the multi-segment foot models assessed by OMC. Research question: Can an IMU based 2-segment foot model be developed to provide a more detailed representation of the foot and ankle kinematics? Methods: To establish a 2-segment foot model, in addition to the previous 1-segment foot model an IMU sensor was added to the calcaneus. This allowed the differentiation between the hindfoot and forefoot kinematics. 30 healthy individuals (mean age 27 ± 7 years) were recruited to create a norm data set of a healthy cohort. Moreover, the kinematic data of the 2-segment foot model were compared to those of the traditional 1-segment foot model using statistical parametric mapping. Results: The 2-segment foot model proved to be applicable. Furthermore, it allowed for a more detailed representation of the foot and ankle joints, similar to other multi-segment foot model. The healthy cohort's norm data set showed a homogeneous motion pattern for gait. Conclusion: The 2-segment foot model allows for an extension of IMU-based gait analysis. Futures studies must prove the reliability and validity of the 2-segment foot model in healthy and pathologic situations. Level of evidence: Level II. [ABSTRACT FROM AUTHOR]

Background: Systems that capture motion under laboratory conditions limit validity in real-world environments. Mobile motion capture solutions such as Inertial Measurement Units (IMUs) can progress our understanding of "real" human movement. IMU data must be validated in each application to interpret with clinical applicability; this is particularly true for diverse populations. Our IMU analysis method builds on the OpenSim IMU Inverse Kinematics toolkit integrating the Versatile Quaternion-based Filter and incorporates realistic constraints to the underlying biomechanical model. We validate our processing method against the reference standard optical motion capture in a case report with participants with transfemoral amputation fitted with a Percutaneous Osseointegrated Implant (POI) and without amputation walking over level ground. We hypothesis that by using this novel pipeline, we can validate IMU motion capture data, to a clinically acceptable degree. Results: Average RMSE (across all joints) between the two systems from the participant with a unilateral transfemoral amputation (TFA) on the amputated and the intact sides were 2.35° (IQR = 1.45°) and 3.59° (IQR = 2.00°) respectively. Equivalent results in the non-amputated participant were 2.26° (IQR = 1.08°). Joint level average RMSE between the two systems from the TFA ranged from 1.66° to 3.82° and from 1.21° to 5.46° in the non-amputated participant. In plane average RMSE between the two systems from the TFA ranged from 2.17° (coronal) to 3.91° (sagittal) and from 1.96° (transverse) to 2.32° (sagittal) in the non-amputated participant. Coefficients of Multiple Correlation (CMC) results between the two systems in the TFA ranged from 0.74 to > 0.99 and from 0.72 to > 0.99 in the non-amputated participant and resulted in 'excellent' similarity in each data set average, in every plane and at all joint levels. Normalized RMSE between the two systems from the TFA ranged from 3.40% (knee level) to 54.54% (pelvis level) and from 2.18% to 36.01% in the non-amputated participant. Conclusions: We offer a modular processing pipeline that enables the addition of extra layers, facilitates changes to the underlying biomechanical model, and can accept raw IMU data from any vendor. We successfully validate the pipeline using data, for the first time, from a TFA participant using a POI and have proved our hypothesis. [ABSTRACT FROM AUTHOR]

Introduction: Fu's subcutaneous needling (FSN) is a new type of acupuncture that uses subcutaneous tissue to oscillate from side to side to improve muscle pathology status and can be effective in treating Knee osteoarthritis. Nonetheless, whether the clinical effect is similar to that of most commonly used drugs is unclear. Thus, this study aims to determine the pain-relieving effect and improvement in the joint function of the FSN therapy by comparing it with that of a positive control drug (celecoxib). Furthermore, this clinical trial also aims to evaluate the effect of FSN on gait and lower limb muscle flexibility, which can further explore the scientific mechanisms of the FSN therapy. Methods and analysis: This study is a randomized, parallel-controlled, single-center prospective clinical study that includes 60 participants, with an FSN group (n = 30) and a drug group (n = 30). The Fu's subcutaneous needling (FSN) group undergo the FSN therapy 3 times a week for 2 weeks, while the drug group receives 0.2 g/day oral celecoxib for 2 weeks, with a follow-up period of 4 weeks after the completion of treatment. The primary outcome is the difference in the visual analog scale score after 2 weeks of treatment compared with baseline. The Western Ontario and McMaster Universities (WOMAC) Osteoarthritis Index, joint active range of motion test, three-dimensional gait analysis, and shear wave elastic imaging technology analysis in lower limb muscles are also performed to demonstrate clinical efficacy. Ethics and dissemination: The trial is performed following the Declaration of Helsinki. The study protocol and consent form have been approved by the Ethics Committee of Guangdong Provincial Hospital of Chinese Medicine. All patients will give informed consent before participation and the trial is initiated after approval. The results of this trial will be disseminated through publication in peer-reviewed journals. Trial registration number: NCT06328153. [ABSTRACT FROM AUTHOR]

Background: Functional assessments are crucial to evaluate treatment outcomes in clinical and animal studies on rotator cuff injuries. While gait analysis is commonly used to assess animal models of rotator cuff tears, it is less relevant for human patients as the human shoulder is typically assessed in a non-weight-bearing condition. The present study introduces the skilled reaching test as a shoulder functional assessment tool for rats, which allows for evaluation without weight bearing. Methods: In the control group, 8 male Sprague–Dawley rats received rotator cuff tear surgery without repair. In the rotator cuff repair group, 20 rats received rotator cuff repair at 4 weeks post rotator cuff tear. For the skilled reaching test, rats were trained to extend their forelimbs to fetch food pellets, and the number of trials, number of attempts and the success rate were recorded. The gait analysis and skilled reaching test were performed at baseline, 4 weeks post-tear, 1, 2, 4, and 8 weeks post-repair. The repeated measures analysis of variance was used to evaluate the effects of time on the shoulder function. The significance level was set at 0.05. Results: The skilled reaching test required 216 h to conduct, while the gait analysis took 44 h. In the rotator cuff repair group, gait performance significantly deteriorated at 1 week post-repair and restored to 4 weeks post-tear levels at 4 weeks post-repair. Regarding the skilled reaching test, the number of attempts, number of trials and the success rate decreased at 1 week post-repair. Subsequently, there was a brief rebound in performance observed at 2 weeks post-repair, followed by a continued decline in the number of attempts and trials. By 8 weeks post-repair, only the success rate had restored to levels similar to those observed at 4 weeks post-tear. Conclusion: The skilled reaching test can detect functional deficiencies following rotator cuff tear and repair, while it requires high time and labour costs. [ABSTRACT FROM AUTHOR]

Background: Falls are common in a range of clinical cohorts, where routine risk assessment often comprises subjective visual observation only. Typically, observational assessment involves evaluation of an individual's gait during scripted walking protocols within a lab to identify deficits that potentially increase fall risk, but subtle deficits may not be (readily) observable. Therefore, objective approaches (e.g., inertial measurement units, IMUs) are useful for quantifying high resolution gait characteristics, enabling more informed fall risk assessment by capturing subtle deficits. However, IMU-based gait instrumentation alone is limited, failing to consider participant behaviour and details within the environment (e.g., obstacles). Video-based eye-tracking glasses may provide additional insight to fall risk, clarifying how people traverse environments based on head and eye movements. Recording head and eye movements can provide insights into how the allocation of visual attention to environmental stimuli influences successful navigation around obstacles. Yet, manual review of video data to evaluate head and eye movements is time-consuming and subjective. An automated approach is needed but none currently exists. This paper proposes a deep learning-based object detection algorithm (VARFA) to instrument vision and video data during walks, complementing instrumented gait. Method: The approach automatically labels video data captured in a gait lab to assess visual attention and details of the environment. The proposed algorithm uses a YoloV8 model trained on with a novel lab-based dataset. Results: VARFA achieved excellent evaluation metrics (0.93 mAP50), identifying, and localizing static objects (e.g., obstacles in the walking path) with an average accuracy of 93%. Similarly, a U-NET based track/path segmentation model achieved good metrics (IoU 0.82), suggesting that the predicted tracks (i.e., walking paths) align closely with the actual track, with an overlap of 82%. Notably, both models achieved these metrics while processing at real-time speeds, demonstrating efficiency and effectiveness for pragmatic applications. Conclusion: The instrumented approach improves the efficiency and accuracy of fall risk assessment by evaluating the visual allocation of attention (i.e., information about when and where a person is attending) during navigation, improving the breadth of instrumentation in this area. Use of VARFA to instrument vision could be used to better inform fall risk assessment by providing behaviour and context data to complement instrumented e.g., IMU data during gait tasks. That may have notable (e.g., personalized) rehabilitation implications across a wide range of clinical cohorts where poor gait and increased fall risk are common. [ABSTRACT FROM AUTHOR]

Background: Lumbar degenerative conditions are a major cause of back pain and disability in individuals aged 45 and above. Gait analysis utilizes sensor technology to collect movement data, aiding in the evaluation of various gait aspects like spatiotemporal parameters, joint angles, neuromuscular activity, and joint forces. It is widely used in conditions such as cerebral palsy and knee osteoarthritis. This research aims to assess the effectiveness of 3D gait analysis in evaluating surgical outcomes and postoperative rehabilitation for lumbar degenerative disorders. Methods: A prospective self-controlled before-after study (n = 85) carried out at our Hospital (Sep 2018 - Dec 2021) utilized a 3D motion analysis system to analyze gait in patients with lumbar degenerative diseases. The study focused on the multifidus muscle, a crucial spinal muscle, during a minimally invasive lumbar interbody fusion surgery conducted by Shandong Weigao Pharmaceutical Co., Ltd. Pre- and postoperative assessments included time-distance parameters (gait speed, stride frequency, stride length, stance phase), hip flexion angle, and stride angle. Changes in 3D gait parameters post-surgery and during rehabilitation were examined. Pearson correlation coefficient was employed to assess relationships with the visual analog pain scale (VAS), Oswestry Disability Index (ODI), and Japanese Orthopedic Association (JOA) scores. Patient sagittal alignment was evaluated using "Surgimap" software from two types of lateral radiographs to obtain parameters like pelvic incidence (PI), pelvic tilt (PT), sacral slope (SS), lumbar lordosis (LL), intervertebral space height (DH), posterior height of the intervertebral space (PDH) at the operative segment, and anterior height of the intervertebral space (ADH). Results: By the 6th week post-operation, significant improvements were observed in the VAS score, JOA score, and ODI score of the patients compared to preoperative values (P < 0.05), along with notable enhancements in 3D gait quantification parameters (P < 0.05). Pearson correlation analysis revealed a significant positive correlation between improvements in 3D gait quantification parameters and VAS score, JOA score, and ODI value (all P < 0.001). Conclusion: 3D gait analysis is a valuable tool for evaluating the efficacy of surgery and rehabilitation training in patients. [ABSTRACT FROM AUTHOR]

Background: Kinetic and kinematic gait analysis is increasingly practised as a part of lameness evaluation in dogs. The aim of this study was to examine the normal short- and long-term variation in forelimb gait in sound control dogs (CD) at a walk using seven selected variables of objective kinetic and kinematic gait analyses. Also, to compare the findings in CD to a group of forelimb lame dogs with elbow osteoarthritis (OAD). An additional aim was to test a kinetic based graphic method for lameness detection; symmetry squares (SS). A prospective longitudinal study was carried out on client owned CD and OAD. Clinical and orthopaedic evaluations were performed to ensure soundness and detect and grade lameness. Seven kinetic and kinematic variables and SS were tested for lameness evaluation. The CD were divided into two subgroups, CD1 and CD2, and examined twice: CD1 with two months interval and CD2 with 3–4 h interval. The OAD group was evaluated once and compared to the CD groups' first examination. Results: Thirteen CD and 19 OAD were included. For CD1 and CD2, there were no significant differences in any examined variable between examination occasions. Total peak force/impulse symmetry and fore-hind peak force/impulse symmetry differed significantly between OAD and CD. Symmetry squares had a 74% agreement to subjective orthopaedic evaluations. Conclusions: In CD, no difference in the examined variables was seen between examination occasions. Four out of seven objective variables differed significantly between CD and OAD. The graphic SS method might have diagnostic potential for lameness detection, making it possible to detect a shift from lame to non-lame limbs. Potentially, this might be especially helpful in bilaterally lame dogs, which often represent a clinical challenge in lameness evaluation. [ABSTRACT FROM AUTHOR]

Background: Recently, the use of inertial measurement units (IMUs) in quantitative gait analysis has been widely developed in clinical practice. Numerous methods have been developed for the automatic detection of gait events (GEs). While many of them have achieved high levels of efficiency in healthy subjects, detecting GEs in highly degraded gait from moderate to severely impaired patients remains a challenge. In this paper, we aim to present a method for improving GE detection from IMU recordings in such cases. Methods: We recorded 10-meter gait IMU signals from 13 healthy subjects, 29 patients with multiple sclerosis, and 21 patients with post-stroke equino varus foot. An instrumented mat was used as the gold standard. Our method detects GEs from filtered acceleration free from gravity and gyration signals. Firstly, we use autocorrelation and pattern detection techniques to identify a reference stride pattern. Next, we apply multiparametric Dynamic Time Warping to annotate this pattern from a model stride, in order to detect all GEs in the signal. Results: We analyzed 16,819 GEs recorded from healthy subjects and achieved an F1-score of 100%, with a median absolute error of 8 ms (IQR [3–13] ms). In multiple sclerosis and equino varus foot cohorts, we analyzed 6067 and 8951 GEs, respectively, with F1-scores of 99.4% and 96.3%, and median absolute errors of 18 ms (IQR [8–39] ms) and 26 ms (IQR [12–50] ms). Conclusions: Our results are consistent with the state of the art for healthy subjects and demonstrate a good accuracy in GEs detection for pathological patients. Therefore, our proposed method provides an efficient way to detect GEs from IMU signals, even in degraded gaits. However, it should be evaluated in each cohort before being used to ensure its reliability. [ABSTRACT FROM AUTHOR]

Background: Gait deficits are very common after stroke and therefore an important aspect in poststroke rehabilitation. A currently little used method in gait rehabilitation after stroke is the activation of the flexor reflex (FR) by electrical stimulation of the sole of foot while walking. The aim of this study was to investigate the effect of FR stimulation on gait performance and gait parameters in participants with stroke within a single session of flexor reflex stimulation using Incedo™. Methods: Twenty-five participants with subacute (n = 14) and chronic (n = 11) stroke were enrolled in the study. Motor functions were tested with a 10-m walk test (10mWT), a 2-min walk test (2minWT), and a gait analysis. These tests were performed with and without Incedo™ within a single session in randomized order. Results: In the 10mWT, a significant difference was found between walking with Incedo™ (15.0 ± 8.5 s) versus without Incedo™ (17.0 ± 11.4 s, p = 0.01). Similarly, the 2minWT showed a significant improvement with Incedo™ use (90.0 ± 36.4 m) compared to without Incedo™ (86.3 ± 36.8 m, p = 0.03). These results indicate that while the improvements are statistically significant, they are modest and should be considered in the context of their clinical relevance. The gait parameters remained unchanged except for the step length. A subgroup analysis indicated that participants with subacute and chronic stroke responded similarly to the stimulation. There was a correlation between the degree of response to electrostimulation while walking and degree of improvement in 2minWT (r = 0.50, p = 0.01). Conclusions: This study is the first to examine FR activation effects in chronic stroke patients and suggests that stimulation effects are independent of the time since stroke. A larger controlled clinical trial is warranted that addresses issues as the necessary number of therapeutical sessions and for how long stimulation-induced improvements outlast the treatment period. Trial registration: The trial was retrospectively registered in German Clinical Trials Register. Clinical trial registration number: DRKS00021457. Date of registration: 29 June 2020. [ABSTRACT FROM AUTHOR]

Background: Instrumented gait analysis (IGA) is an assessment and research tool with proven impacts on clinical decision-making for the management of ambulant children and young people with cerebral palsy (CYPwCP) but is underused and variably understood by relevant clinicians. Clinicians' difficulties in gaining expertise and confidence in using IGA are multifactorial and related to access for clinical decision-making, limited training opportunities and inability to translate this training into clinical practice. Methods: The primary aim of this study is to test the feasibility of an educational intervention to advance clinicians' application of gait analysis in CYPwCP, to inform a definitive trial. The secondary aim is to measure the effect that appropriate IGA training has on physiotherapists' knowledge, skills, confidence and behaviours. This will be a two-arm feasibility randomised controlled trial with an experimental and control group. The 6-week on-line intervention uses a multicomponent approach grounded in behavioural change techniques. A repeated measures design will be adopted, whereby participants will complete outcome measures at baseline, immediately after the intervention and at 4 months. The primary outcome measures (trial feasibility-related outcomes) are recruitment and engagement. The secondary outcome measures (trial research-related outcomes) are knowledge, skills, confidence and practice change. Outcome measures will be collected via online questionnaires and during observed skill assessments. Analysis of data will use descriptive statistics, two-way mixed ANOVA model and qualitative content analysis. Discussion: This study will determine feasibility of the definitive randomised control trial of educational intervention delivered to advance clinicians' application of gait analysis in CYPwCP. This study offers the shift in emphasis from regarding IGA as a tool to a focus on clinicians' requirements for access, training and a well-defined role to optimise utilisation of IGA. The impact of this should be better engagement with IGA and clinical practice change. This study will contribute to a body of educational research into clinical education of healthcare professionals and IGA training offering insight into high levels of evaluation evidence including clinical behaviour change. Trial registration: Protocol has been registered with the Open Science Framework (osf.io/nweq6) in June 2023. [ABSTRACT FROM AUTHOR]

Background: Sensor-based gait analysis provides a robust quantitative tool for assessing gait impairments and their associated factors in Parkinson's disease (PD). Anxiety is observed to interfere with gait clinically, but this has been poorly investigated. Our purpose is to utilize gait analysis to uncover the effect of anxiety on gait in patients with PD. Methods: We enrolled 38 and 106 PD patients with and without anxiety, respectively. Gait parameters were quantitively examined and compared between two groups both in single-task (ST) and dual-task (DT) walking tests. Multiple linear regression was applied to evaluate whether anxiety independently contributed to gait impairments. Results: During ST, PD patients with anxiety presented significantly shorter stride length, lower gait velocity, longer stride time and stance time, longer stance phase, smaller toe-off (TO) and heel-strike (HS) angles than those without anxiety. While under DT status, the differences were diminished. Multiple linear regression analysis demonstrated that anxiety was an independent factor to a serials of gait parameters, particularly ST-TO (B = -2.599, (-4.82, -0.38)), ST-HS (B = -2.532, (-4.71, -0.35)), ST-TO-CV (B = 4.627, (1.71, 7.64)), ST-HS-CV(B = 4.597, (1.66, 7.53)), ST stance phase (B = 1.4, (0.22, 2.58)), and DT stance phase (B = 1.749, (0.56, 2.94)). Conclusion: Our study discovered that anxiety has a significant impact on gait impairments in PD patients, especially exacerbating shuffling steps and prolonging stance phase. These findings highlight the importance of addressing anxiety in PD precision therapy to achieve better treatment outcomes. [ABSTRACT FROM AUTHOR]

Background: Foot and ankle unloading is essential in various clinical contexts, including ulcers, tendon ruptures, and fractures. Choosing the right assistive device is crucial for functionality and recovery. Yet, research on the impact of devices beyond crutches, particularly ankle-foot orthoses (AFOs) designed to unload the ankle and foot, is limited. This study investigates the effects of three types of devices—forearm crutches, knee crutch, and AFO—on biomechanical, metabolic, and subjective parameters during walking with unilateral ankle-foot unloading. Methods: Twenty healthy participants walked at a self-selected speed in four conditions: unassisted able-bodied gait, and using three unloading devices, namely forearm crutches, iWalk knee crutch, and ZeroG AFO. Comprehensive measurements, including motion capture, force plates, and metabolic system, were used to assess various spatiotemporal, kinematic, kinetic, and metabolic parameters. Additionally, participants provided subjective feedback through questionnaires. The conditions were compared using a within-subject crossover study design with repeated measures ANOVA. Results: Significant differences were found between the three devices and able-bodied gait. Among the devices, ZeroG exhibited significantly faster walking speed and lower metabolic cost. For the weight-bearing leg, ZeroG exhibited the shortest stance phase, lowest braking forces, and hip and knee angles most similar to normal gait. However, ankle plantarflexion after push-off using ZeroG was most different from normal gait. IWalk and crutches caused significantly larger center-of-mass mediolateral and vertical fluctuations, respectively. Participants rated the ZeroG as the most stable, but more participants complained it caused excessive pressure and pain. Crutches were rated with the highest perceived exertion and lowest comfort, whereas no significant differences between ZeroG and iWalk were found for these parameters. Conclusions: Significant differences among the devices were identified across all measurements, aligning with previous studies for crutches and iWalk. ZeroG demonstrated favorable performance in most aspects, highlighting the potential of AFOs in enhancing gait rehabilitation when unloading is necessary. However, poor comfort and atypical sound-side ankle kinematics were evident with ZeroG. These findings can assist clinicians in making educated decisions about prescribing ankle-foot unloading devices and guide the design of improved devices that overcome the limitations of existing solutions. [ABSTRACT FROM AUTHOR]

Background: This study analysed changes in gait and pedobarography and subjective and functional outcomes after isolated Chopart joint injury. Methods: The results of 14 patients were reviewed. Kinematic 3D gait analysis, comparative bilateral electromyography (EMG) and pedobarography were performed. Results: On the injured side, the 3D gait analysis showed a significantly increased internal rotation and decreased external rotation of the hip and significantly decreased adduction and decreased range of motion (ROM) for the ankle. On the healthy side, the pedobarography revealed a significantly increased mean force in the forefoot, an increased peak maximum force and an increased maximum pressure in the metatarsal. When standing, significantly more weight was placed on the healthy side. The EMG measurements showed no significant differences between the healthy and injured legs. Conclusions: After isolated Chopart injuries, significant changes in gait and pedobarography can be seen over the long term. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was to demonstrate closer-to-normal knee kinematics following primary total knee arthroplasty (TKA) performed establishing asymmetric gap balancing intraoperatively. Material and method: Two age-, sex-, BMI-matched groups of patients underwent medially stabilized TKA because of isolated knee disease. Group A (12 patients) underwent "unrestricted" kinematic alignment (uKA) according to Howell while group B (15 patients) received robot-assisted "simplified" KA (sKA) with an alignment goal (Hip-Knee-Ankle axis-HKA) ± 5° respect to the mechanical axis. Intraoperatively, in group B, the flexion gap at 90° was first set at an average of 1.5 mm (0–5 mm; SD 4.4 mm) tighter in the medial compartment with respect to the lateral; in the same way, the extension gap was then set at an average of 2.0 mm (0–4.5 mm; SD 3.1 mm) tighter in the medial compartment with respect to the lateral. All patients, including a non-arthritic cohort (group C: 5 controls) underwent gait analysis using an instrumented treadmill (WalkerView–WV) equipped with an instrumented belt armed with a 3D video camera. The WV software evaluated multiple spatiotemporal and kinematic parameters, including: (1) contact time (s); (2) knee ROM during gait cycle; (3) step length percentage with respect to total gait (%) and pure step length (cm). Statistical analyses included t-Test and ANOVA and were conducted by using SPSS. Results: At the final FU, significant differences were noted during gait between the two TKA groups (uKA-sKA) and the controls. Both TKA groups showed superior mean contact time on the surgical knee (uKA 1 s; sKA 0.97 s) as compared to the controls (0.72 s) (P = 0.002) while no differences were found between them (P = 0.11). TKA groups showed a lower, maximum ROM in the surgical knee (mean uKA 36º; mean sKA 49º) relative to the controls (mean 57º) (P < 0.05) but a statistical difference was found between them (P = 0.003). Both TKA groups showed a higher step length percentage with respect to the total gait and a shorter step length on the surgical side (uKA: mean 8.28% and mean step length 35.5 cm; sKA: mean 8.38% and mean step length 34.6 cm) in comparison to the controls (mean 3.38%; mean step length 71.4 cm) (P < 0.05) while no statistical differences were found between them. Conclusion: To our knowledge, this was the first study to exhibit the kinematic advantages of a slightly asymmetric gap balancing during KA TKA. Combining a medially-stabilized implant design and a surgical technique aiming to obtain a tighter medial compartment represents a promising approach to improve outcomes after TKA. [ABSTRACT FROM AUTHOR]

Background: Knee osteoarthritis (KOA) is an irreversible degenerative disease that characterized by pain and abnormal gait. Radiography is typically used to detect KOA but has limitations. This study aimed to identify changes in plantar pressure that are associated with radiological knee osteoarthritis (ROA) and to validate them using machine learning algorithms. Methods: This study included 92 participants with variable degrees of KOA. A modified Kellgren–Lawrence scale was used to classify participants into non-ROA and ROA groups. The total feature set included 210 dynamic plantar pressure features captured by a wearable in-shoe system as well as age, gender, height, weight, and body mass index. Filter and wrapper methods identified the optimal features, which were used to train five types of machine learning classification models for further validation: k-nearest neighbors (KNN), support vector machine (SVM), random forest (RF), AdaBoost, and eXtreme gradient boosting (XGBoost). Results: Age, the standard deviation (SD) of the peak plantar pressure under the left lateral heel (f_L8PPP_std), the SD of the right second peak pressure (f_Rpeak2_std), and the SD of the variation in the anteroposterior displacement of center of pressure (COP) in the right foot (f_RYcopstd_std) were most associated with ROA. The RF model with an accuracy of 82.61% and F1 score of 0.8000 had the best generalization ability. Conclusion: Changes in dynamic plantar pressure are promising mechanical biomarkers that distinguish between non-ROA and ROA. Combining a wearable in-shoe system with machine learning enables dynamic monitoring of KOA, which could help guide treatment plans. [ABSTRACT FROM AUTHOR]

Background: The biomechanics of the hindfoot in ankle osteoarthritis (OA) are not yet fully understood. Here, we aimed to identify hindfoot motion in a gait analysis using a multi-segment foot model (MFM) according to ankle OA stage and the presence of subtalar compensation defined by hindfoot alignment. Methods: We retrospectively reviewed the medical records, plain radiographs, and gait MFM data of 54 ankles admitted to our hospital for the treatment of advanced ankle OA. Spatiotemporal gait parameters and three-dimensional motions of the hindfoot segment were analyzed according to sex, age, body mass index, Takakura classification, and the presence of subtalar compensation. Twenty ankles were categorized as compensated group, and 34 ankles as decompensated group. Results: No spatiotemporal gait parameters differed significantly according to the presence of subtalar compensation or ankle OA stage. Only normalized step width differed significantly (P = 0.028). Average hindfoot motion (decompensation vs. compensation) did not differ significantly between the sagittal and transverse planes. Graphing of the coronal movement of the hindfoot revealed collapsed curves in both groups that differed significantly. Compared with Takakura stages 3a, 3b, and 4, cases of more advanced stage 3b had a smaller sagittal range of motion than those of stage 3a (P = 0.028). Coronal movement of the hindfoot in cases of Takakura stage 3a/3b/4 showed a relatively flat pattern. Conclusions: The spatiotemporal parameters were not affected by the hindfoot alignment resulting from subtalar compensation. The sagittal range of hindfoot motion decreased in patients with advanced ankle OA. Once disrupted, the coronal movement of the subtalar joint in ankle OA did not change regardless of ankle OA stage or hindfoot compensation state. [ABSTRACT FROM AUTHOR]

Background: To clarify the value of gait analysis and its consistency with traditional scoring scales for the evaluation of knee joint function after total knee arthroplasty (TKA). Methods: This study included 25 patients with knee osteoarthritis (KOA) who underwent bilateral TKA, and 25 conditionally matched healthy individuals, categorised into the experimental and control groups, respectively. Patients in the experimental group underwent gait analysis and Western Ontario and McMaster University Osteoarthritis Index (WOMAC) evaluation before and 1 year after TKA. Weight-bearing balance and walking stability were assessed using discrete trends of relevant gait indicators. Pearson's correlation analysis was performed on the gait and WOMAC score data of the experimental group before and after TKA. Results: One year after TKA, patients' gait indices (except gait cycle) were significantly better than before surgery, but significantly worse than that of the control group (P < 0.01). The shape of patients' plantar pressure curves did not return to normal. Additionally, the discrete trend of related gait indicators reflecting weight-bearing balance and walking stability were smaller than before TKA, but still greater than that of the control group. The WOMAC scores of patients 1 year after TKA were significantly lower than those before TKA (P < 0.001), and the efficacy index was > 80%. The WOMAC scores and gait analysis results were significantly correlated before TKA (P < 0.05). Conclusions: Gait analysis should be used in conjunction with scoring scales to assess joint functions. [ABSTRACT FROM AUTHOR]

Background: The hallux plays a crucial role in maintaining standing balance and facilitating forward and backward movements during gait. Case presentation: A 21-year-old Japanese patient, suffering from a traumatic hallux deficit with only a portion of the basal phalanx intact, underwent rehabilitation treatment. The thenar area exhibited instability, leading to impaired balance and walking difficulties. Biomechanical assessment revealed the need for a rehabilitation strategy for the foot, as well as the knee, hip, and trunk. A rehabilitation protocol was designed to enhance medial foot loading during walking and standing, including balance and trunk strength training. After a 12-week rehabilitation period, the patient's gait showed significant improvement. Specifically, the load response and single-support phases of the gait cycle on the affected side increased from 46.9% to 49.3%, while the pre-swing phase decreased from 14.6% to 11.6%. The vertical component of the ground reaction force rose from 599.8 to 647.5 N. The enhanced stability from balance training and increased muscle strength contributed to the patient's improved walking and balance. Conclusion: A patient with a traumatic hallux deficit underwent conservative treatment through strategic rehabilitation according to biomechanical assessment. This case report underscores the value of biomechanical gait analysis in the conservative management of similar conditions. [ABSTRACT FROM AUTHOR]

Background: Malignant femoral soft tissue tumors are occasionally resected together with the femoral nerves, but this can cause loss of knee extensor muscle activity. To the best of our knowledge, no previous reports have detailed the gait analysis of such cases in combination with electromyography. Herein, we report the gait analysis of a patient who underwent left groin synovial sarcoma and left femoral nerve resection 12 years ago. Case presentation: We analyzed the gait of a 38-year-old man who was able to walk unaided after the resection of a synovial sarcoma in the left groin together with the ipsilateral femoral nerve. The muscle activities of the affected medial (MH) and lateral hamstrings (LH), and lateral heads of the gastrocnemius (GL) were increased during 50–75% of the stance phase. The hip flexion angle of the affected limb was smaller, and the ankle plantar flexion angle of the affected limb was larger than that of the non-affected limb. This means that in the affected limb, the hip and ankle angles were adjusted to prevent knee collapse, and the MH, LH, and GL muscles contributed in the mid- and late-stance phases. Moreover, we found that the hamstring and gastrocnemius of the affected limb worked together to keep the ipsilateral knee extended in the mid-stance phase and slightly flexed in the late-stance phase. Conclusions: Patients capable of walking after femoral nerve resection may control their hamstrings and gastrocnemius muscles collaboratively to prevent ipsilateral knee collapse in the mid- and late-stance phases. [ABSTRACT FROM AUTHOR]

Objective: Evaluation of the accuracy and effectiveness of 3D printed guides to assist femoral tunnel preparation in individualised reconstruction of the anterior cruciate ligament. Methods: Sixty patients who attended the Affiliated Hospital of Binzhou Medical College for autologous hamstring single bundle reconstruction of the anterior cruciate ligament from October 2018 to October 2020 were selected and randomly divided into two groups, including 31 cases in the 3D printing group (14 males and 17 females, mean age 41.94 ± 10.15 years) and 29 cases in the control group (13 males and 16 females, mean age 37.76 ± 10.34 years). Patients in both groups were assessed for intraoperative femoral tunnel accuracy, the number of intraoperative positioning and the time taken to prepare the femoral tunnel, the length of the anteromedial approach incision, the pre-planned bone tunnel length and intraoperative bone tunnel length in the 3D printed group, IKDC score and Lysholm score preoperatively and at 3, 6 and 12 months postoperatively, the Lachman、pivot-shift test preoperatively and at 6 months postoperatively, gait analysis to assess internal and external rotation in flexion of the knee at 12 months postoperatively and postoperative complications in both groups. Results: There was no statistical difference in functional knee scores and anteromedial approach incision length between the 3D printed and control groups (p > 0.05), while there was a statistical difference in the accuracy of tunnel positioning, the time taken to prepare the femoral bone tunnel and the degree of external rotation of the knee in flexion between the two groups (p < 0.05). There was no statistical difference between the preoperative planning of the bone tunnel length and the intraoperative bone tunnel length (p > 0.05). Complications: One case in the 3D printing group developed intermuscular vein thrombosis in the affected lower limb after surgery, which disappeared after treatment, while three cases in the control group developed intermuscular vein thrombosis in the affected lower limb. No complications such as bone tunnel rupture, deep vein thrombosis in the lower limb and infection occurred in either group. Conclusion: 3D printed guides assisted with individualized ACL reconstruction may improve the accuracy of femoral tunnel positioning, which is safe and effective, while reducing the operative time and the number of intraoperative positioning, without increasing the length of incision, and may obtain higher functional scores and rotational stability of the knee joint, which is in line with the concept of individualized ACL reconstruction. [ABSTRACT FROM AUTHOR]

Background: Neurological gait disorders are mainly classified based on clinical observation, and therefore difficult to objectify or quantify. Movement analysis systems provide objective parameters, which may increase diagnostic accuracy and may aid in monitoring the disease course. Despite the increasing wealth of kinematic movement and balance parameter data, the discriminative value for the differentiation of neurological gait disorders is still unclear. We hypothesized that kinematic motion and balance parameter metrics would be differently altered across neurological gait disorders when compared to healthy controls. Methods: Thirty one patients (9 normal pressure hydrocephalus < NPH > , 16 cervical myelopathy < CM > , 6 lumbar stenosis < LST >) and 14 healthy participants were investigated preoperatively in an outpatient setting using an inertial measurement system (MyoMotion) during 3 different walking tasks (normal walking, dual-task walking with simultaneous backward counting, fast walking). In addition, the natural postural sway of participants was measured by pedobarography, with the eyes opened and closed. The range of motion (ROM) in different joint angles, stride time, as well as sway were compared between different groups (between-subject factor), and different task conditions (within-subject factor) by a mixed model ANOVA. Results: Kinematic metrics and balance parameters were differently altered across different gait disorders compared to healthy controls. Overall, NPH patients significantly differed from controls in all movement parameters except for stride time, while they differed in balance parameters only with regard to AP movement. LST patients had significantly reduced ROMs of the shoulders, hips, and ankles, with significantly altered balance parameters regarding AP movement and passed center-of-pressure (COP) distance. CM patients differed from controls only in the ROM of the hip and ankle, but were affected in nearly all balance parameters, except for force distribution. Conclusion: The application of inertial measurement systems and pedobarography is feasible in an outpatient setting in patients with different neurological gait disorders. Rather than defining singular discriminative values, kinematic gait and balance metrics may provide characteristic profiles of movement parameter alterations in the sense of specific ´gait signatures´ for different pathologies, which could improve diagnostic accuracy by defining objective and quantifiable measures for the discrimination of different neurological gait disorders. Trial registration: The study was retrospectively registered on the 27th of March 2023 in the 'Deutsches Register für Klinische Studien' under the number DRKS00031555. [ABSTRACT FROM AUTHOR]

Introduction: Gait impairments in Parkinson's disease (PD) are treated with dopaminergic medication or deep-brain stimulation (DBS), although the magnitude of the response is variable between individuals. Computer vision-based approaches have previously been evaluated for measuring the severity of parkinsonian gait in videos, but have not been evaluated for their ability to identify changes within individuals in response to treatment. This pilot study examines whether a vision-based model, trained on videos of parkinsonism, is able to detect improvement in parkinsonian gait in people with PD in response to medication and DBS use. Methods: A spatial–temporal graph convolutional model was trained to predict MDS-UPDRS-gait scores in 362 videos from 14 older adults with drug-induced parkinsonism. This model was then used to predict MDS-UPDRS-gait scores on a different dataset of 42 paired videos from 13 individuals with PD, recorded while ON and OFF medication and DBS treatment during the same clinical visit. Statistical methods were used to assess whether the model was responsive to changes in gait in the ON and OFF states. Results: The MDS-UPDRS-gait scores predicted by the model were lower on average (representing improved gait; p = 0.017, Cohen's d = 0.495) during the ON medication and DBS treatment conditions. The magnitude of the differences between ON and OFF state was significantly correlated between model predictions and clinician annotations (p = 0.004). The predicted scores were significantly correlated with the clinician scores (Kendall's tau-b = 0.301, p = 0.010), but were distributed in a smaller range as compared to the clinician scores. Conclusion: A vision-based model trained on parkinsonian gait did not accurately predict MDS-UPDRS-gait scores in a different PD cohort, but detected weak, but statistically significant proportional changes in response to medication and DBS use. Large, clinically validated datasets of videos captured in many different settings and treatment conditions are required to develop accurate vision-based models of parkinsonian gait. [ABSTRACT FROM AUTHOR]

Background: Patients with anterior cruciate ligament (ACL) deficiency (ACLD) tend to have altered lower extremity dynamics. Little is known about the changes in dynamic function and activation during jogging in patients with ACLD. Methods: Twenty patients with an injured ACL before ACL reconstruction (ACLD group) and nine healthy male volunteers (control group) were recruited. Each volunteer repeated the jogging experiment five times. Based on the experimental data measured, a musculoskeletal multibody dynamics model was employed to simulate the tibiofemoral joint dynamics during jogging. Eighteen muscles were used for analysis. The obtained dynamics data were used for clustering and curve difference analysis. Results: The 18 muscles studied were divided into 3 categories. All the quadriceps, the soleus, the gastrocnemius, and the popliteus were classified as label 1. All the hamstrings were classified as label 2, and the sartorius muscles were classified as label 3. Among them, the classification of the short head of the biceps femoris was significantly different between the two groups (P < 0.001). The force curves of all 18 muscles and the between-group differences were studied according to clustered categories. Most muscle force in label 1 was approaching zero in the terminal stance phase, which was significantly lower than that in the control group (P < 0.05). The muscle force in label 2 had areas with significant differences in the stance phase. Muscle force in label 3 was significantly lower than that in the control group in the pre-swing phase. Conclusions: This study showed that there are various changes of muscle function and activation in patients with ACLD. Through clustering and curve analysis, the joint reactions and changes of different muscle forces in the gait cycle between the ACLD and control groups could be further clarified. [ABSTRACT FROM AUTHOR]

Background: Gait decline in older adults is related to falling risk, some of which contribute to injurious falls requiring medical attention or restriction of activity of daily living. Among injurious falls, distal radius fracture (DRF) is a common initial fragility fracture associated with the subsequent fracture risk in postmenopausal females. The recent invention of an inertial measurement unit (IMU) facilitates the assessment of free-living gait; however, little is known about the daily gait characteristics related to the risk of subsequent fractures. We hypothesized that females with DRF might have early changes in foot kinematics in daily gait. The aim of this study was to evaluate the daily-life gait characteristics related to the risk of falls and fracture. Methods: In this cross-sectional study, we recruited 27 postmenopausal females with DRF as their first fragility fracture and 28 age-matched females without a history of fragility fractures. The participants underwent daily gait assessments for several weeks using in-shoe IMU sensors. Eight gait parameters and each coefficient of variance were calculated. Some physical tests, such as hand grip strength and Timed Up and Go tests, were performed to check the baseline functional ability. Results: The fracture group showed lower foot angles of dorsiflexion and plantarflexion in the swing phase. The receiver operating characteristic curve analyses revealed that a total foot movement angle (TFMA) < 99.0 degrees was the risk of subsequent fracture. Conclusions: We extracted the daily-life gait characteristics of patients with DRF using in-shoe IMU sensors. A lower foot angle in the swing phase, TFMA, may be associated with the risk of subsequent fractures, which may be effective in evaluating future fracture risk. Further studies to predict and prevent subsequent fractures from daily-life gait are warranted. [ABSTRACT FROM AUTHOR]

Background: There are a lot of tools to use for fall assessment, but there is not yet one that predicts the risk of falls in the elderly. This study aims to evaluate the use of the G-STRIDE prototype in the analysis of fall risk, defining the cut-off points to predict the risk of falling and developing a predictive model that allows discriminating between subjects with and without fall risks and those at risk of future falls. Methods: An observational, multicenter case–control study was conducted with older people coming from two different public hospitals and three different nursing homes. We gathered clinical variables (Short Physical Performance Battery (SPPB), Standardized Frailty Criteria, Speed 4 m walk, Falls Efficacy Scale-International (FES-I), Time-Up Go Test, and Global Deterioration Scale (GDS)) and measured gait kinematics using an inertial measure unit (IMU). We performed a logistic regression model using a training set of observations (70% of the participants) to predict the probability of falls. Results: A total of 163 participants were included, 86 people with gait and balance disorders or falls and 77 without falls; 67,8% were females, with a mean age of 82,63 ± 6,01 years. G-STRIDE made it possible to measure gait parameters under normal living conditions. There are 46 cut-off values of conventional clinical parameters and those estimated with the G-STRIDE solution. A logistic regression mixed model, with four conventional and 2 kinematic variables allows us to identify people at risk of falls showing good predictive value with AUC of 77,6% (sensitivity 0,773 y specificity 0,780). In addition, we could predict the fallers in the test group (30% observations not in the model) with similar performance to conventional methods. Conclusions: The G-STRIDE IMU device allows to predict the risk of falls using a mixed model with an accuracy of 0,776 with similar performance to conventional model. This approach allows better precision, low cost and less infrastructures for an early intervention and prevention of future falls. [ABSTRACT FROM AUTHOR]

Background: Control system design for a microprocessor-controlled hip–knee–ankle–foot (HKAF) prosthesis is a challenge since hip disarticulation amputees lack the entire leg and, therefore, only have pelvis movement as user-guided input. This research proposes a method for determining hip joint angles from pelvis movement in a control system for the next generation of powered prostheses. Method: Three-dimensional pelvic motion and stance time of 10 transfemoral (TF) prosthetic users were used to identify important features and to develop an algorithm to calculate hip angles from pelvis movement based on correlation and linear regression results. The algorithm was then applied to a separate (independent) TF group to validate algorithm performance. Results: The proposed algorithm calculated viable hip angles during walking by utilizing pelvic rotation, pelvic tilt, and stance time. Small angular differences were found between the algorithm results and motion capture data. The greatest difference was for hip maximum extension angle (2.5 ± 2.0°). Conclusions: Since differences between algorithm output and motion data were within participant standard deviations, the developed algorithm could be used to determine the desired hip angle from pelvis movements. This study will aid the future development of gait control systems for new active HKAF prostheses. [ABSTRACT FROM AUTHOR]

Background: Rodent models are commonly employed to validate preclinical disease models through the evaluation of postoperative behavior and allodynia. Our study investigates the dynamic interplay between pain and functional recovery in the context of traumatic osteotomy and surgical repair. Specifically, we established a rat model of tibial osteotomy, followed by internal fixation using a 5-hole Y-plate with 4 screws, to explore the hypothesis that histological bone healing is closely associated with functional recovery. Objective: Our primary objective was to assess the correlation between bone healing and functional outcomes in a rat model of tibial osteotomy and plate fixation. Methods: Seventeen male Sprague–Dawley rats underwent a metaphyseal transverse osteotomy of the proximal tibia, simulating a fracture-like injury. The resultant bone defect was meticulously repaired by realigning and stabilizing the bone surfaces with the Y-plate. To comprehensively assess recovery and healing, we performed quantitative and qualitative evaluations at 2, 4, 6, and 8 weeks post-surgery. Evaluation methods included micro-CT imaging, X-ray analysis, and histological examination to monitor bone defect healing. Concurrently, we employed video recording and gait analysis to evaluate functional recovery, encompassing parameters such as temporal symmetry, hindlimb duty factor imbalance, phase dispersion, and toe spread. Results: Our findings revealed complete healing of the bone defect at 8 weeks, as confirmed by micro-CT and histological assessments. Specifically, micro-CT data showed a decline in fracture volume over time, indicating progressive healing. Histological examination demonstrated the formation of new trabecular bone and the resolution of inflammation. Importantly, specific gait analysis parameters exhibited longitudinal changes consistent with bone healing. Hindlimb duty factor imbalance, hindlimb temporal symmetry, and phase dispersion correlated strongly with the healing process, emphasizing the direct link between bone healing and functional outcomes. Conclusions: The establishment of this tibia osteotomy model underscores the association between bone healing and functional outcomes, emphasizing the feasibility of monitoring postoperative recovery using endpoint measurements. Our overarching objective is to employ this model for assessing the local efficacy of drug delivery devices in ameliorating post-surgical pain and enhancing functional recovery. [ABSTRACT FROM AUTHOR]

Background: The diagnosis of Parkinson's disease (PD) and evaluation of its symptoms require in-person clinical examination. Remote evaluation of PD symptoms is desirable, especially during a pandemic such as the coronavirus disease 2019 pandemic. One potential method to remotely evaluate PD motor impairments is video-based analysis. In this study, we aimed to assess the feasibility of predicting the Unified Parkinson's Disease Rating Scale (UPDRS) score from gait videos using a convolutional neural network (CNN) model. Methods: We retrospectively obtained 737 consecutive gait videos of 74 patients with PD and their corresponding neurologist-rated UPDRS scores. We utilized a CNN model for predicting the total UPDRS part III score and four subscores of axial symptoms (items 27, 28, 29, and 30), bradykinesia (items 23, 24, 25, 26, and 31), rigidity (item 22) and tremor (items 20 and 21). We trained the model on 80% of the gait videos and used 10% of the videos as a validation dataset. We evaluated the predictive performance of the trained model by comparing the model-predicted score with the neurologist-rated score for the remaining 10% of videos (test dataset). We calculated the coefficient of determination (R2) between those scores to evaluate the model's goodness of fit. Results: In the test dataset, the R2 values between the model-predicted and neurologist-rated values for the total UPDRS part III score and subscores of axial symptoms, bradykinesia, rigidity, and tremor were 0.59, 0.77, 0.56, 0.46, and 0.0, respectively. The performance was relatively low for videos from patients with severe symptoms. Conclusions: Despite the low predictive performance of the model for the total UPDRS part III score, it demonstrated relatively high performance in predicting subscores of axial symptoms. The model approximately predicted the total UPDRS part III scores of patients with moderate symptoms, but the performance was low for patients with severe symptoms owing to limited data. A larger dataset is needed to improve the model's performance in clinical settings. [ABSTRACT FROM AUTHOR]

Background: Wearable sensors have become a complementary means for evaluation of body function and gait in lower limb osteoarthritis. This study aimed to review the applications of wearable sensors for gait analysis after total knee arthroplasty (TKA). Methods: Five databases, including Web of Science Core Collection, Embase, Cochrane, Medline, and PubMed, were searched for articles published between January 2010 and March 2023, using predetermined search terms that focused on wearable sensors, TKA, and gait analysis as broad areas of interest. Results: A total of 25 articles were identified, involving 823 TKA patients. Methodologies varied widely across the articles, with inconsistencies found in reported patient characteristics, sensor data and experimental protocols. Patient-reported outcome measures (PROMs) and gait variables showed various recovery times from 1 week postoperatively to 5 years postoperatively. Gait analysis using wearable sensors and PROMs showed differences in controlled environments, daily life, and when comparing different surgeries. Conclusion: Wearable sensors offered the potential to remotely monitor the gait function post-TKA in both controlled environments and patients' daily life, and covered more aspects than PROMs. More cohort longitudinal studies are warranted to further confirm the benefits of this remote technology in clinical practice. [ABSTRACT FROM AUTHOR]

Backgrounds: Gait disorder is associated with cognitive functional impairment, and this disturbance is more pronouncedly when performing additional cognitive tasks. Our study aimed to characterize gait disorders in mild cognitive impairment (MCI) under three dual tasks and determine the association between gait performance and cognitive function. Methods: A total of 260 participants were enrolled in this cross-sectional study and divided into MCI and cognitively normal control. Spatiotemporal and kinematic gait parameters (31 items) in single task and three dual tasks (serial 100-7, naming animals and words recall) were measured using a wearable sensor. Baseline characteristics of the two groups were balanced using propensity score matching. Important gait features were filtered using random forest method and LASSO regression and further described using logistic analysis. Results: After matching, 106 participants with MCI and 106 normal controls were recruited. Top 5 gait features in random forest and 4 ~ 6 important features in LASSO regression were selected. Robust variables associating with cognitive function were temporal gait parameters. Participants with MCI exhibited decreased swing time and terminal swing, increased mid stance and variability of stride length compared with normal control. Subjects walked slower when performing an extra dual cognitive task. In the three dual tasks, words recall test exhibited more pronounced impact on gait regularity, velocity, and dual task cost than the other two cognitive tests. Conclusion: Gait assessment under dual task conditions, particularly in words recall test, using portable sensors could be useful as a complementary strategy for early detection of MCI. [ABSTRACT FROM AUTHOR]

Background: Hereditary spastic paraplegias (HSPs) cause characteristic gait impairment leading to an increased risk of stumbling or even falling. Biomechanically, gait deficits are characterized by reduced ranges of motion in lower body joints, limiting foot clearance and ankle range of motion. To date, there is no standardized approach to continuously and objectively track the degree of dysfunction in foot elevation since established clinical rating scales require an experienced investigator and are considered to be rather subjective. Therefore, digital disease-specific biomarkers for foot elevation are needed. Methods: This study investigated the performance of machine learning classifiers for the automated detection and classification of reduced foot dorsiflexion and clearance using wearable sensors. Wearable inertial sensors were used to record gait patterns of 50 patients during standardized 4 × 10 m walking tests at the hospital. Three movement disorder specialists independently annotated symptom severity. The majority vote of these annotations and the wearable sensor data were used to train and evaluate machine learning classifiers in a nested cross-validation scheme. Results: The results showed that automated detection of reduced range of motion and foot clearance was possible with an accuracy of 87%. This accuracy is in the range of individual annotators, reaching an average accuracy of 88% compared to the ground truth majority vote. For classifying symptom severity, the algorithm reached an accuracy of 74%. Conclusion: Here, we show that the present wearable gait analysis system is able to objectively assess foot elevation patterns in HSP. Future studies will aim to improve the granularity for continuous tracking of disease severity and monitoring therapy response of HSP patients in a real-world environment. [ABSTRACT FROM AUTHOR]

Background: To study the gait parameters in asymptomatic volunteers and investigate the correlation between the gait and several radiographic sagittal profiles. Methods: Asymptomatic volunteers (20–50 years of age) were included and allocated into three subgroups depending on pelvic incidence (low, normal, and high). Standing whole spine radiographs and gait analysis data were obtained. The Pearson Coefficient Correlation was used to determine the relationship between the gait and radiographic profiles. Results: A total of 55 volunteers (28 male and 27 females) were included. The mean age was 27.35 ± 6.37 years old. The average sacral slope (SS), pelvic tilt (PT), pelvic incidence (PI), and PI-LL mismatch (PI-LL) were 37.78 ± 6.59, 14.51 ± 9.19 degrees, and 52.29 ± 10.87 degrees and − 0.36 ± 11.41, respectively. The mean velocity and stride of all the volunteers were 119.00 ± 30.12 cm/s and 130.25 ± 7.72 cm, correspondingly. The correlation between each of the radiographical and gait parameters was low (ranging from − 0.24 to 0.26). Conclusion: Gait parameters were not differenced significantly between each of the PI subgroups in asymptomatic volunteers. Spinal sagittal parameters also showed a low correlation with gait parameters. [ABSTRACT FROM AUTHOR]

Background: The lower limb mechanical axis was used to assess the severity of knee osteoarthritis (KOA) with varus/valgus deformity and the accuracy of targeted lower limb alignment correction after operation by conventional X-rays. There are lots of parameters to assess the gait in elder patients such as velocity, stride length, step width and swing/stance ratio by knee joint movement analysis system. However, the correlation between the lower limb mechanical axis and gait parameters is not clear. This study is aimed at obtaining the accuracy of the lower limb mechanical axis by the knee joint movement analysis system and the correlation between the lower limb mechanical axis and gait parameters. Methods: We analysed 3D knee kinematics during ground gait of 99 patients with KOA and 80 patients 6 months after the operations with the vivo infrared navigation 3D portable knee joint movement analysis system (Opti-Knee®, Innomotion Inc, Shanghai, China). The HKA (Hip-Knee-Ankle) value was calculated and compared to X-ray findings. Results: HKA absolute variation after the operation was 0.83 ± 3.76°, which is lower than that before the operation (5.41 ± 6.20°, p = 0.001) and also lower than the entire cohort (3.36 ± 5.72). Throughout the cohort, a significant correlation with low coefficients (r = -0.19, p = 0.01) between HKA value and anterior-posterior displacement was found. In comparing the HKA values measured on the full-length alignment radiographs and 3D knee joint movement analysis system (Opti-Knee), there was a significant correlation with moderate to high coefficients (r = 0.784 to 0.976). The linear correlation analysis showed that there was a significant correlation between the values of HKA measured by X-ray and movement analysis system (R2 = 0.90, p < 0.01). Conclusions: Data with equivalent results as HKA, the 6DOF of the knee and ground gait data could be provided by infrared navigation based 3D portable knee joint movement analysis system comparing with the conventional X-rays. There is no significant effect of HKA on the kinematics of the partial knee joint. [ABSTRACT FROM AUTHOR]

Background: Cognitive impairment is a critical aspect of our aging society. Yet, it receives inadequate intervention due to delayed or missed detection. Dual-task gait analysis is currently considered a solution to improve the early detection of cognitive impairment in clinical settings. Recently, our group proposed a new approach for the gait analysis resorting to inertial sensors placed on the shoes. This pilot study aimed to investigate the potential of this system to capture and differentiate gait performance in the presence of cognitive impairment based on single- and dual-task gait assessments. Methods: We analyzed demographic and medical data, cognitive tests scores, physical tests scores, and gait metrics acquired from 29 older adults with mobility limitations. Gait metrics were extracted using the newly developed gait analysis approach and recorded in single- and dual-task conditions. Participants were stratified into two groups based on their Montreal Cognitive Assessment (MoCA) global cognitive scores. Statistical analysis was performed to assess differences between groups, discrimination ability, and association of gait metrics with cognitive performance. Results: The addition of the cognitive task influenced gait performance of both groups, but the effect was higher in the group with cognitive impairment. Multiple dual-task costs, dual-task variability, and dual-task asymmetry metrics presented significant differences between groups. Also, several of these metrics provided acceptable discrimination ability and had a significant association with MoCA scores. The dual-task effect on gait speed explained the highest percentage of the variance in MoCA scores. None of the single-task gait metrics presented significant differences between groups. Conclusions: Our preliminary results show that the newly developed gait analysis solution based on foot-worn inertial sensors is a pertinent tool to evaluate gait metrics affected by the cognitive status of older adults relying on single- and dual-task gait assessments. Further evaluation with a larger and more diverse group is required to establish system feasibility and reliability in clinical practice. Trial registration: ClinicalTrials.gov (identifier: NCT04587895) [ABSTRACT FROM AUTHOR]

Introduction: Gait disturbance in central nervous system (CNS) demyelinating disorders, including multiple sclerosis (MS) and neuromyelitis optica (NMO) is one of the most troublesome problems that has a direct impact on the quality of life. However, the associations between gait disturbance and other clinical variables of these two diseases have not been fully elucidated. Objective: This study aimed to evaluate gait disturbance using a computerized gait analysis system and its association with various clinical variables in patients with MS and NMO. Methods: A total of 33 patients (14 with MS and 19 with NMO) with minor disabilities, who were able to walk independently and had passed their acute phase, were enrolled in the study. Gait analysis were performed using a computer-based instrumented walkway system. (Walk-way MG-1000, Anima, Japan) Clinical variables, such as disease duration, medication, body mass index (BMI), hand grip power, and muscle mass were recorded. The Montreal Cognitive Assessment (MOCA), Beck Depression Inventory score-II (BDI), and fatigue scale were measured using the Functional Assessment of Chronic Illness Therapy-fatigue scale (FACIT-fatigue) scale. A trained neurologist scored the Expanded Disability Status Scale (EDSS). Results: Gait speed was the single parameter that showed a significant positive correlation with MOCA (p < 0.001). The stance phase time was the single parameter that showed a significant negative correlation with EDSS (p < 0.001). Hand grip strength showed a significant positive correlation with skeletal muscle mass as assessed by bioimpedance analysis (p < 0.05). The FACIT-fatigue scale score showed a significant negative correlation with the BDI (p < 0.001). Conclusion: In our patients with MS/NMO with mild disability, cognitive impairment was significantly correlated with gait speed, and the degree of disability was significantly correlated with stance phase time. Our findings may imply that early detection of a decrease in gait speed and an increase in stance phase time can predict the progression of cognitive impairment in patients with MS/NMO with mild disability. [ABSTRACT FROM AUTHOR]

Background: An incomplete spinal cord injury (SCI) refers to remaining sensorimotor function below the injury with the possibility for the patient to regain walking abilities. However, these patients often suffer from diverse gait deficits, which are not objectively assessed in the current clinical routine. Wearable inertial sensors are a promising tool to capture gait patterns objectively and started to gain ground for other neurological disorders such as stroke, multiple sclerosis, and Parkinson's disease. In this work, we present a data-driven approach to assess walking for SCI patients based on sensor-derived outcome measures. We aimed to (i) characterize their walking pattern in more depth by identifying groups with similar walking characteristics and (ii) use sensor-derived gait parameters as predictors for future walking capacity. Methods: The dataset analyzed consisted of 66 SCI patients and 20 healthy controls performing a standardized gait test, namely the 6-min walking test (6MWT), while wearing a sparse sensor setup of one sensor attached to each ankle. A data-driven approach has been followed using statistical methods and machine learning models to identify relevant and non-redundant gait parameters. Results: Clustering resulted in 4 groups of patients that were compared to each other and to the healthy controls. The clusters did differ in terms of their average walking speed but also in terms of more qualitative gait parameters such as variability or parameters indicating compensatory movements. Further, using longitudinal data from a subset of patients that performed the 6MWT several times during their rehabilitation, a prediction model has been trained to estimate whether the patient's walking speed will improve significantly in the future. Including sensor-derived gait parameters as inputs for the prediction model resulted in an accuracy of 80%, which is a considerable improvement of 10% compared to using only the days since injury, the present 6MWT distance, and the days until the next 6MWT as predictors. Conclusions: In summary, the work presented proves that sensor-derived gait parameters provide additional information on walking characteristics and thus are beneficial to complement clinical walking assessments of SCI patients. This work is a step towards a more deficit-oriented therapy and paves the way for better rehabilitation outcome predictions. [ABSTRACT FROM AUTHOR]

Background: Total knee arthroplasty (TKA) is one of the most performed orthopedic procedures worldwide. While excellent efficacy has been reported, about 20% of patients are not satisfied with the result. A potential cause is the problematic reproduction of knee kinematics. This systematic review examines gait analysis studies in primary medial pivot (MP) and posterior stabilized (PS) TKAs to investigate the differences between the two prosthesis designs. Methods: A systematic review was conducted by following PRISMA guidelines. Five databases (PubMed, Medline, Embase, Scopus and the Cochrane Database of Systematic Reviews) were analyzed, and eligible articles were evaluated in terms of the levels of evidence. The methodological quality of the articles was assessed by using the MINORS scoring. This review was registered in PROSPERO. Results: Nine studies were included. Gait analysis was performed in 197 MP TKA and 192 PS TKA patients. PS TKA cases showed (P < 0.05) a significantly higher peak of knee flexion angle during the swing phase, greater knee flexion angle at toe-off, an increased knee adduction angle, higher knee flexion and extension moment, increased anterior femoral roll during knee flexion and anterior translation on medial and lateral condyle during knee flexion compared to MP TKA. MP TKA showed statistically significant (P < 0.05) higher knee rotational moment and greater tibiofemoral external rotation motion during knee flexion than PS TKA. No statistically significant difference (P > 0.05) was reported regarding gait spatial–temporal parameters. The Forgotten Joint Score (FJS) and Western Ontario and McMaster Universities Comparison in terms of Arthritis Index (WOMAC) score (mean stiffness) showed that MP TKA yielded significantly better results than PS TKA. Conclusions: This systematic review revealed significant kinematic and kinetic differences between MP and PS TKA at all gait analysis phases. Furthermore, the considerable difference between TKA design and the kinematics of healthy knee were highlighted in this study. Level of evidence: III. [ABSTRACT FROM AUTHOR]