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Purpose: This study aimed to analyze and compare gait patterns and deviations at long-term follow-up in children who received medial open reduction (MOR) before 18 months for unilateral or bilateral hip developmental dysplasia (DDH). Methods: A retrospective chart review was conducted on children who underwent MOR. The study population was divided into two groups: the unilateral group, including unilateral (five children with unilateral) and bilateral (five children with bilateral DDH). Ten healthy children were recruited for the control group. Spatiotemporal, kinematic, stiff-knee gait (SKG), and kinetic gait characteristics were analyzed. Results: Stance time was significantly shorter in both the unilateral (median [IQR]; 590 ms, [560.0–612.5] and bilateral (575 ms, [550–637.5]) groups than in the control group (650, [602.5–677.5]) (p < 0.001), whereas swing time did not differ substantially (p = 0.065) There was no considerable difference in the mean knee flexion at swing between the unilateral (31.6°, [30–36]) and control (30.11°, [27.8–33.6] groups (p > 0.05), but the bilateral group (28.5°, [24.9–32.1]) showed the lower values than the other groups (p < 0.001 for bilateral vs unilateral group; p = 0.008 bilateral vs unilateral group). All the SKG parameters significantly differed among the groups in multi-group comparisons (p < 0.001 for each parameter). Three children had borderline SKG, and two had not-stiff limbs in the unilateral group. In the bilateral group, four children had stiff limbs, and one had borderline SKG. Most kinetic gait parameters were not statistically different between groups (p > 0.05). Conclusion: This study has revealed notable deviations in gait patterns of children with DDH treated by MOR at long-term follow-up compared to healthy children's gait. MOR could negatively affect pelvic motion during gait due to impaired functions of the iliopsoas and adductor muscles, and SKG can be encountered secondary to iliopsoas weakness. [ABSTRACT FROM AUTHOR]

Objective: The aim of the study is to evaluate how gait kinematics and muscle activity during robot-assisted gait training are affected by different combinations of parameter settings and a number of instruction types, ranging from no instructions to goal-specific instructions. Design: Robots for gait therapy provide a haptic guidance, but too much guidance can limit the active participation. Therapists can stimulate this active participation either with instructions or by adapting device parameters. How these two factors interact is still unknown. In the present study, we test the interaction of three different parameter settings and four instruction types in a cross-sectional study with 20 children and adolescents without impairment. Gait kinematics and surface electromyography were measured to evaluate the immediate effects. Results: We found that only goal-specific instructions in combination with a low guidance led to a moderate but significant change in gait kinematics. The muscle activity was altered by all instructions, but the biggest effect was found for goal-specific instructions with a 2.5 times higher surface electromyography amplitude compared to no instruction. Conclusions: Goal-specific instructions are a key element of robot assisted gait therapy interventions and device parameter adjustments may be used to modulate their effects. Therapists should pay close attention to how they instruct patients. [ABSTRACT FROM AUTHOR]

Objective: Physical activity is important for health, yet most young adults are insufficiently active. Physical activity is regulated in part, by habit, typically operationalised as automaticity. Little is known about the characteristics of automaticity, or whether broad bandwidth unidimensional measures of automaticity for physical activity are superior to narrower bandwidth multi- dimensional measures. Design: This secondary analysis (N = 238) investigated the nature of automaticity, and relations between the dimensions of automaticity, global automaticity, and physical activity.Main Outcome Measures: The structure of the Generic Multifaceted Automaticity Scale (GMAS) was examined by confirmatory factor analyses. Structural equation models were estimated to evaluate relations between automaticity (measured on the GMAS and the Self- Report Behavioral Automaticity Index, SRBAI) and device- measured activity.Results: The hypothesised 3- factor structure of the GMAS was rejected, in favour of a 2- factor solution. Lack of intention/control and efficiency were associated with global automaticity, but not physical activity. Global automaticity was associated with moderate to vigorous physical activity and daily steps, but not light physical activity.Conclusion: Multi- dimensional measures of automaticity may not provide a more nuanced understanding of automaticity when predicting overall physical activity. [ABSTRACT FROM AUTHOR]

The research that links excessive screen time to adverse health outcomes is based on self-reported screen use. Few studies have documented how passively-sensed smartphone and app use relate to health behaviors like activity and sitting. Furthermore, they have not considered that daily fluctuations in smartphone/app use may have different relationships to these behaviors than a person's usual smartphone/app use. This study evaluated whether physical activity or sedentary (sitting) behavior are associated with either smartphone screen time or specific smartphone app use by adolescents and young adults during the COVID-19 pandemic. Adolescents and young adults aged 13–29 years wore activPAL4 micro activity monitors while their smartphones logged daily screen time and app use durations for nine days. Data were collected in 2020–2021 and analyzed in 2022–2023. Participants (N = 125) had a mean (SD) age of 19.7 (4.3) years. Participants' usual smartphone screen time was negatively associated with daily step counts. Daily deviations in smartphone screen time were negatively associated with daily step counts and moderate-vigorous physical activity durations. Time spent on Instagram, YouTube and, to a lesser extent, TikTok were linked with reduced activity levels. Daily sedentary behavior was not associated with usual or daily screen time. Interventions to promote physical activity during the transition into adulthood may benefit from limiting excessive smartphone screen time. Specific intervention targets could include limiting use of apps with infinite scrolling feeds algorithmically tuned to maintain user engagement, such as Instagram, YouTube and TikTok. [ABSTRACT FROM AUTHOR]

The purpose of this study was to: (1) compare the relative efficacy of different combinations of three behavioral intervention strategies (i.e., personalized reminders, financial incentives, and anchoring) for establishing physical activity habits using an mHealth app and (2) to examine the effects of these different combined interventions on intrinsic motivation for physical activity and daily walking habit strength. A four-arm randomized controlled trial was conducted in a sample of college students (N = 161) who had a self-reported personal wellness goal of increasing their physical activity. Receiving cue-contingent financial incentives (i.e., incentives conditional on performing physical activity within ± one hour of a prespecified physical activity cue) combined with anchoring resulted in the highest daily step counts and greatest odds of temporally consistent walking during both the four-week intervention and the full eight-week study period. Cue-contingent financial incentives were also more successful at increasing physical activity and maintaining these effects post-intervention than traditional non-cue-contingent incentives. There were no differences in intrinsic motivation or habit strength between study groups at any time point. Financial incentives, particularly cue-contingent incentives, can be effectively used to support the anchoring intervention strategy for establishing physical activity habits. Moreover, mHealth apps are a feasible method for delivering the combined intervention technique of financial incentives with anchoring. [ABSTRACT FROM AUTHOR]

Objective: Navigating obstacles involves adjusting walking patterns, particularly when stepping over them. This task may be particularly challenging for people with Parkinson disease (PD) for several reasons. This review aims to compare the spatiotemporal gait parameters of people with and without PD while stepping over obstacles. Literature Survey: A systematic literature search was conducted in six databases (PubMed, Scopus, Web of Science, EBSCO, Embase, and SciELO) from inception to September 2023. Methodology: Studies were selected that evaluated gait parameters of people with and without PD while walking over obstacles. Two independent researchers evaluated the eligibility and extracted gait parameters during obstacle crossing. The risk of bias was assessed using the Joanna Briggs Institute Critical Appraisal Checklist. Heterogeneity was assessed using I2‐tests. Random effects models were determined for effect sizes as standardized mean differences (SMD). Synthesis: Twenty‐five studies were included in the review and 17 in the meta‐analysis. Most of the studies (58%) showed a low risk of bias. People with PD exhibit a shorter step when landing after crossing an obstacle (SMD = −0.50 [−0.69 to −0.31]). Compared to people without PD, people with PD also widen their support base (SMD = 0.27 [0.07–0.47]) and reduce gait velocity (SMD = −0.60 [−0.80 to −0.39]) when crossing the obstacle. Conclusions: People with PD adopt a more conservative motor behavior during obstacle crossing than those without PD, with a shorter step length when landing after crossing an obstacle, greater step width and lower crossing speed. [ABSTRACT FROM AUTHOR]

Background/Objectives. A notable decline in physical activity from late adolescence to early adulthood affects young women especially. This study aimed to investigate adherence to an unsupervised virtual-guided high-intensity interval training (HIIT) exercise program among young women in Spain. Methods. A total of 106 participants were recruited and randomized to the Women's Involvement in Steady Exercise (WISE) trial exercise program, administered remotely via a mobile app, and a control group. The primary outcome was adherence measured through daily steps. Secondary variables were patient-reported outcomes of physical activity, quality of sleep, and quality of life, assessed with the International Physical Activity Questionnaire (IPAQ), the Pittsburgh Sleep Quality Index (PSQI), and the Health Lifestyle and Personal Control Questionnaire (HLPCQ), respectively. The assessments were performed over 6 months, before the intervention (T0), at the halfway of the program (T1), and at the end (T2). Results. Daily steps revealed a decrease from baseline to final assessment in both groups. Secondary outcomes indicated a shift in physical activity levels, showing a transition from low to moderate and high activity perception. While sleep quality deteriorated post-intervention, quality of life showed no changes. Conclusions. The WISE trial highlights the potential and challenges of an unsupervised virtual-guided HIIT program for young women. While an improvement in physical activity levels was noticed, it also led to a decrease in daily steps and poorer sleep quality. These findings suggest a complex relationship between exercise and lifestyle factors, which could potentially have the greatest impact. [ABSTRACT FROM AUTHOR]

Machine learning (ML) has been used in human gait data for appropriate assistive device prediction. However, their uptake in the medical setup still remains low due to their black box nature which restricts clinicians from understanding how they operate. This has led to the exploration of explainable ML. Studies have recommended local interpretable model‐agnostic explanation (LIME) because it builds sparse linear models around an individual prediction in its local vicinity hence fast and also because it could be used on any ML model. LIME is however, is not always stable. The research aimed to enhance LIME to attain stability by avoid the sampling step through combining Gaussian mixture model (GMM) sampling. To test performance of the GMM‐LIME, supervised ML were recommended because study revealed that their accuracy was above 90% when used on human gait. Neural networks were adopted for GaitRec dataset and Random Forest (RF) was adopted and applied on HugaDB datasets. Maximum accuracies attained were multilayer perceptron (95%) and RF (99%). Graphical results on stability and Jaccard similarity scores were presented for both original LIME and GMM‐LIME. Unlike original LIME, GMM‐LIME produced not only more accurate and reliable but also consistently stable explanations. [ABSTRACT FROM AUTHOR]

Background: Concurrent with population ageing, falls have become a significantly more challenging public health issue among older adults. Three years of data collected recently from a nursing home in northern Taiwan reveals an increasing trend in fall density that is primarily associated with aging, physiological decline, chronic diseases, polypharmacy, osteoporosis, and lack of exercise. The percentage of nursing home residents at high risk of falls is currently at 12.6%, and the fall rate has been reported as reaching as high as 30% annually. Purpose: A fall prevention program was implemented to reduce the fall incidence rate to 18%, with secondary goals of improving fall prevention awareness, behavior, self-efficacy, lower limb muscle strength, balance, and gait by 10% on average, respectively, between pre-test and post-test. Resolution: From September 30, 2023 to February 29, 2024, a health promotion activity and fall prevention exercise course were implemented using an interdisciplinary team collaboration model over a six-week period, providing individualized exercise for the participants. Result: The study included 20 older adults with an average age of 88 years. Most (90%; n = 18) had chronic diseases, 25% (n = 5) were on more than nine medications, 70% (n = 14) had reduced bone mass, and 40% (n = 8) were at high risk of falls, with a fall incidence rate of 30% during the immediately preceding year. Post-intervention, the fall incidence rate dropped to 5%, fall prevention awareness, behavior, and self-efficacy increased by 18.3%, and lower limb muscle strength, balance, and gait improved by 11.7%. The post-test results in fall prevention awareness, behavioral changes, self-efficacy, and lower limb strength, balance, and gait were all significantly better than pre-test results, with all results achieving statistical significance. Conclusion: The project results support the positive effects of the developed intervention effectively on elderly physical fitness and fall risk, providing valuable insights for the implementation of fall prevention strategies in nursing homes. [ABSTRACT FROM AUTHOR]

Musculoskeletal modeling is a cost-effective way to design and test wearable robots, ensuring maximum efficiency for individuals. This article explores the simulation of exoskeletons to support the lower limbs and reduce the metabolic cost of walking. The exoskeleton consists of a flexible joint as an actuator made up of four elastomers that store the negative power of the knee joint during the walking cycle as energy, and release it to assist the wearer in the next phase of walking. The Computed Muscle Control (CMC) algorithm in OpenSim is used to find joint torque, total metabolic savings, and the resulting changes in muscle activity. Subsequently, the behavior of implementing the passive exoskeleton is evaluated and the results are compared to a semi-active robot on lower body limbs. The study concluded that while the passive robot exerts extra force on the hamstring muscles in the first half of the swing phase and increases the torque applied to the knee joint. It decreases the activity of the quadriceps muscles in the second half. To compensate for this problem exoskeletons are commonly equipped with a motor. However, this article's findings suggest that utilizing the motorized robot, while decreasing the torque in the targeted joint, actually boosts the performance of surrounding muscles and consumes more metabolic energy than in a passive state. [ABSTRACT FROM AUTHOR]

Background: The sedentary aspects of many U.S. occupations and the amount of time American workers spend in the workplace make it an ideal location to implement health promotion programs. Methods: This study assessed the effectiveness of a free smartphone app with a goal-setting feature to increase physical activity (PA) and impact anthropometric, body mass (BM), and body composition (BC) changes among overweight and obese women within a community health workforce. Eighteen overweight and obese (body mass index [BMI] = 32.18 ± 4.48 kg/m2), adult (50.73 ± 8.76 years), female volunteers, tracked daily steps with a free smartphone app (StridekickTM) over an 8-week period. Pre- and post-program body composition (BC) measurements included: relative (%) body fat (BF), fat mass (FM), fat-free mass (FFM), and lean mass (LM), using dual X-ray absorptiometry (DEXA scan), and five anthropometric measurements (biceps, waist, abdomen, hips, and thigh). Findings: Pre- to post-program average daily steps resulted in significant anthropometric changes for biceps, hips, and thigh measures, with encouraging changes in FFM, LM, and relative (%) BF. The goal-setting feature of the app did not result in significant differences between the experimental and control groups. No differences were noted in FM, BMI, waist, and abdomen or step goals compared with steps completed. Conclusions: An occupational PA health promotion intervention program that tracked daily steps through the StridekickTM smartphone app resulted in anthropometric, BM, and BC changes. Application to Practice: The workplace is an ideal location to affect change in health behaviors via a free smartphone app to increase PA and improve health. [ABSTRACT FROM AUTHOR]

An Ankle-foot orthosis (AFO) is a structure that spans from the lower leg to the foot and controls ankle joint movement. It prevents or assists the human body's lower leg and foot in replicating a normal human gait. The purpose of AFO is to achieve a stable gait by controlling the musculoskeletal system adequately. The mechanical features of AFO stiffness will play an essential role in helping gait, if this stiffness is not matching to the patient's conditions, gait will decrease and knee joint motion will be compromised. In general, trimline cut were introduced in the AFO medial and lateral side to control the stiffness of orthosis. However, this will result in stress concentration in the ankle region and lead to failure of AFO. In this study first evaluate the effects of trimline cut in AFOs using finite element analysis with three geometrical shapes like circle, elliptical and slot were introduced on the dorsal side. The stress concentration and stiffness of AFOs in the ankle region were computed. The stiffness of the basic model and trimline cut AFO model were compared and found elliptical trimline cut model is optimum one. The experimental analysis was performed using 3D Printed AFOs and calculated stiffness. It was observed that finite element analysis results, stress concentration of trimline cut models were reduced maximum of 2 % with basic model (without trimline cut)., whereas, in the experimental study of 3D-Printed AFO of trimline cut model, stiffness were reduced around 16 % compared with basic models. This study clearly indicates that, geometrical shapes trimline cut influencing on stiffness of AFOs. It will give the insight's for orthosis designers to make custom design of AFOs in particularly foot drop conditions to optimized the stiffness of orthosis. [ABSTRACT FROM AUTHOR]

The analysis of gait is an important tool for evaluating postoperative outcomes of a Total Knee Replacement (TKR). There are few studies which have evaluated the gait parameters of a Kinematic retaining (Kr) prosthesis. This study therefore aims to investigate the kinetic and kinematic differences of running and walking, in the ankle, knee and hip joints in patients who underwent a Kr TKR. This study assessed the gait of 12 patients with physica lima Kr TKRs at 1 year follow up and 8 healthy controls using 3D video analysis. Data was collected on the kinetics and kinematics of walking and running at the ankle, knee and hip. Comparison was made between the operated and non-operated limbs of the patients, and between the operated and control limbs. Gait analysis showed no statistically significant difference in the hip, ankle and knee angles or moments between the non-operated and operated legs during walking and running. However, there was a statistically significant difference between the knee angles of initial contact, maximum flexion during stance and swing in the TKR knees vs controls in walking and running. Similarly, there was also a statistically significantly higher max knee flexion moment between operated knees and controls in both walking and running. This study has shown that a quadriceps avoidance gait persists in patients after TKR, and that there was symmetry and reciprocated gait parameters in non-operated limbs. These findings suggest that Kr TKRs could be capable of replicating normal knee kinematics when running and walking. [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]

Humans and birds use very different running styles. Unlike humans, birds adopt "grounded running" at intermediate speeds--a running gait where at least one foot always maintains ground contact. Avian grounded running is a paradox: Animals usually minimize locomotor energy expenditure, but birds prefer grounded running despite incurring higher energy costs. Using predictive gait simulations of the emu (Dromaius novaehollandiae), we resolve this paradox by demonstrating that grounded running represents an optimal gait for birds, from both energetics and muscle excitations perspectives. Our virtual experiments decoupled effects of posture and tendon elasticity, biomechanically relevant anatomical features that cannot be isolated in real birds. The avian body plan prevents (near) vertical leg postures, making the running style used by humans impossible. Under this anatomical constraint, grounded running is optimal if the muscles produce the highest forces in crouched postures, as is true in most birds. Shared anatomical features suggest that, as a behavior, avian grounded running first evolved within non-avian dinosaurs. [ABSTRACT FROM AUTHOR]

Oxygen consumption (V˙O2) is an important measure for exercise test, such as walking and running, that can be measured outdoors using portable spirometers or metabolic analyzers. However, these devices are not feasible for regular use by consumers as they intervene with the user's physical integrity, and are expensive and difficult to operate. To circumvent these drawbacks, indirect estimation of V˙O2 using neural networks combined with motion features and heart rate measurements collected with consumer-grade sensors has been shown to yield reasonably accurate V˙O2 for intra-subject estimation. However, estimating V˙O2 with neural networks trained with data from other individuals than the user, known as inter-subject estimation, remains an open problem. In this paper, five types of neural network architectures were tested in various configurations for inter-subject V˙O2 estimation. To analyse predictive performance, data from 16 participants walking and running at speeds between 1.0 m/s and 3.3 m/s were used. The most promising approach was Xception network, which yielded average estimation errors as low as 2.43 ml×min−1×kg−1, suggesting that it could be used by athletes and running enthusiasts for monitoring their oxygen consumption over time to detect changes in their movement economy. [ABSTRACT FROM AUTHOR]

Increased propulsion force (PF) in the paretic limb is associated with improved walking speed in patients with stroke. However, late braking force (LBF), an additional braking force occurring between PF onset and toe-off, is present in a subset of stroke patients. Few studies have investigated the changes in LBF and walking speed in these patients. This study aimed to elucidate the patterns of change in PF and LBF during fast gait in hemiplegics and identify potential compensatory strategies based on the LBF patterns. Data from 100 patients with stroke walking at both comfortable (mean, 0.79 ± 024 m/s) and fast speeds (mean, 1.06 ± 0.35 m/s) were analyzed retrospectively stroke using a 3D motion analyzer. PF was higher during fast-speed walking than that during comfortable-speed walking in all patients, while LBF showed both decreasing and increasing trends during fast-speed walking. In the LBF increasing pattern, a reduction in in-phase coordination of the shank and foot during the pre-swing phase was observed, along with an increase in pelvic hike during fast-speed walking compared to those in the decreasing LBF pattern. Our findings demonstrate that alterations in LBF patterns are associated with gait deviations in patients with stroke at fast speeds. [ABSTRACT FROM AUTHOR]

Background: Plantar fasciitis (PF) is the most common cause of heel pain affecting both young active patients and older sedentary individuals. It most often arises as a result of degenerative changes in the proximal plantar fascia. Aim: The purpose of this study was to investigate the effect of extracorporeal shockwave on gait parameters in patients with plantar fasciitis. Design: A randomized controlled clinical trial. Setting: The outpatient physiotherapy clinic of the teaching hospital Shibin El Kom. Methods: Participants were randomly divided into two equal groups. Group (A) (study group): received extracorporeal shockwave therapy one session per week and traditional treatment (ultrasound, stretching exercises, and strengthening exercises) three sessions per week for 4 weeks. Group (B)(the control group): received traditional treatment (ultrasound, stretching exercises, and strengthening exercises) 3 sessions per week for 4 weeks. The pre- and post-treatment development of the patients was evaluated by visual analog scale (VAS) to measure pain, foot function index (FFI) to measure foot function, and Kinovea software to analyze gait parameters (stride length, stride time, walking speed, and cadence). Results: Both groups showed improvement in all study variables, but the study group showed more improvement. There was a statistically significant decrease in VAS (p = 0.001), a significant decrease in FFI (p = 0.001), a significant increase in stride length (p = 0.001), a significant decrease in stride time (p = 0.001), a significant increase in walking speed (p = 0.001), and a significant increase in cadence (p = 0.01) post-treatment compared to group (B). Conclusion: Extracorporeal shockwave treatment is regarded as a useful treatment for improving gait parameters in patients with plantar fasciitis. Clinical rehabilitation impact: Extracorporeal shockwave therapy improved gait parameters in patients with plantar fasciitis as it increases stride length, walking speed, cadence, and decreases stride time. So, it is recommended to be included in the rehabilitation program for patients with plantar fasciitis and gait disabilities. [ABSTRACT FROM AUTHOR]

In human walking, the left and right legs move alternately, half a stride out of phase with each other. Although various parameters, such as stride frequency and length, vary with walking speed, the antiphase relationship remains unchanged. In contrast, during walking in left-right asymmetric situations, the relative phase shifts from the antiphase condition to compensate for the asymmetry. Interlimb coordination is important for adaptive walking and we expect that interlimb coordination is strictly controlled during walking. However, the control mechanism remains unclear. In the present study, we derived a quantity that models the control of interlimb coordination during walking using two coupled oscillators based on the phase reduction theory and Bayesian inference method. The results were not what we expected. Specifically, we found that the relative phase is not actively controlled until the deviation from the antiphase condition exceeds a certain threshold. In other words, the control of interlimb coordination has a dead zone like that in the case of the steering wheel of an automobile. It is conjectured that such forgoing of control enhances energy efficiency and maneuverability. Our discovery of the dead zone in the control of interlimb coordination provides useful insight for understanding gait control in humans. Analyses of the synchronization mechanism between the legs during walking using two coupled oscillators and Bayesian inference method reveal the presence of a "dead zone," where the control of interlimb coordination is ineffective. [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]

With the rapid development of the internet of things, the simple preparation of sensors has become a challenge. The present work presents the simple preparation of flexible sensors by using the fused deposition modeling (FDM) 3D printing combined with the microwave radiation‐assisted treatment of the thermoplastic polyurethane (TPU) with carbon nanotubes (CNTs) as conductive fillers to create the flexible sensors. The as‐prepared TPU/CNT composites exhibit the 7.27 MPa tensile strength and 401% elongation at break, similar to those of the pure TPU. After 200 tensile cycles, the TPU/CNT composites can still stably convert pressure into electrical signals, which can be used as flexible sensors with high sensitivity (0.879 kPa−1). In addition, shoe insoles and finger cover with sensing performance are fabricated through the FDM 3D printing technology, demonstrating the potential of the sensors to monitor human gait, finger straightening, and bending movements. The as‐proposed method involves the embedding CNTs as conductive fillers on the surface of TPU to form the TPU/CNT composite conductive layers on the surface of TPU, which is beneficial for maintaining the elasticity of the polymer matrix. The challenges in preparing stable, low‐cost, and scalable flexible sensors and highlights of the advantages of 3D printing technology in manufacturing flexible piezoresistive sensors are also deeply discussed. [ABSTRACT FROM AUTHOR]

Introduction: Freezing of gait (FOG) is a disabling and heterogeneous symptom in patients with Parkinson's disease (PD). Among them, dopamine-induced FOG is rare and difficult to identify. The treatment of dopamine-induced FOG is complex. Case presentation: We herein presented a case of PD patient who complicated with refractory FOG. It was identified as dopamine-induced FOG during levodopa challenge test. Her symptoms were alleviated after we reduced the total equivalent dosage of levodopa. Conclusion: Our report emphasizes the importance of levodopa challenge test in identifying different types of FOG, which is very important for further adjusting treatment. [ABSTRACT FROM AUTHOR]

Background/Objectives: Treatment of advanced knee osteoarthritis with total knee arthroplasty typically results in an improvement in function, gait, and quality of life, which tend to be affected by the condition. It is, however, necessary to determine the baseline factors that could influence the patients' postoperative outcome. Methods: This is a single-center prospective observational study of patients with advanced knee osteoarthritis (Kellgren–Lawrence grade 3 or 4) treated with total knee arthroplasty. Gait parameters were recorded at baseline and at various postoperative time points using a wireless device. Progression of function was assessed using the Knee Society Score questionnaire and quality of life by means of the EQ-5D and Knee Injury and Osteoarthritis Outcome Score questionnaires. Progression of gait and quality of life was analyzed in all patients, distinguishing between those where baseline velocity was < 1 m/s and those where it was ≥1 m/s. The potential correlation between baseline and postoperative parameters was also evaluated. Results: All 119 patients showed a significant improvement in their gait, function, and quality of life parameters at one year from the procedure (p < 0.05). No statistically significant differences were found in any of the postoperative subscales, regardless of baseline velocity (< o ≥ 1 m/s) or between any of the baseline or postoperative parameters (r < 0.29). Conclusions: Baseline gait parameters in patients with advanced knee osteoarthritis do not appear to bear a statistically significant relationship with function or quality of life outcomes following total knee arthroplasty. Such parameters exhibit a significant improvement one year after surgery. [ABSTRACT FROM AUTHOR]

Coordinated movement of four limbs is a hallmark of healthy locomotion. No measures exist to quantify four-limb coordination. This study aimed to investigate temporal four-limb coordination and proposed a new metric for quantifying the inter-limb phase of rhythmic locomotion-related movements. Kinetic data of arm and leg movements generated during walking (self-selected speed) from healthy adults were used to extract the phases (φ) between all possible limb pairings. The φ series were used to calculate each pair's Phase Coordination Index (PCI). The PCI quantifies the accuracy and consistency of generating anti-phased rhythmic movements (lower PCI values mean better coordination). We also calculated the Quadruple-PCI (Q-PCI) by combining all φ values of all limb pairs. We found a significant correlation between the PCI values of all limb pairings and the Q-PCI (pairs involving arms: Pearson's R > 0.79, p < 0.001; leg–leg: Pearson's R = 0.3, p < 0.01). The PCI values that involve arms (median values between 6.5% and 8.3%) were significantly higher than the leg–leg PCI (median values between 3.8% and 4.1%), and the Q-PCI (median values between 8.3% and 9.7%) was significantly higher than all other PCI values. We also found a negative correlation between the arm swing amplitude and the PCI values (Spearman's Rho of different limb pairings ranging from −0.25 to −0.5, p < 0.05), suggesting that higher arm swing amplitude leads to better coordination. Four-limb coordination analysis is a novel method for comprehensive assessment of gait coordination, which is often compromised among persons with disabilities. [ABSTRACT FROM AUTHOR]

Background: Stroke-induced immunosuppression (SII) represents a negative rehabilitative prognostic factor associated with poor motor performance at discharge from a neurorehabilitation unit (NRB). This study aims to evaluate the association between SII and gait impairment at NRB admission. Methods: Forty-six stroke patients (65.4 ± 15.8 years, 28 males) and 42 healthy subjects (HS), matched for age, sex, and gait speed, underwent gait analysis using an inertial measurement unit at the lumbar level. Stroke patients were divided into two groups: (i) the SII group was defined using a neutrophil-to-lymphocyte ratio ≥ 5, and (ii) the immunocompetent (IC) group. Harmonic ratio (HR) and short-term largest Lyapunov's exponent (sLLE) were calculated as measures of gait symmetry and stability, respectively. Results: Out of 46 patients, 14 (30.4%) had SII. HR was higher in HS when compared to SII and IC groups (p < 0.01). HR values were lower in SII when compared to IC subjects (p < 0.01). sLLE was lower in HS when compared to SII and IC groups in the vertical and medio-lateral planes (p ≤ 0.01 for all comparisons). sLLE in the medio-lateral plane was higher in SII when compared to IC subjects (p = 0.04). Conclusions: SII individuals are characterized by a pronounced asymmetric gait and a more impaired dynamic gait stability. Our findings underline the importance of devising tailored rehabilitation programs in patients with SII. Further studies are needed to assess the long-term outcomes and the role of other clinical features on gait pattern. [ABSTRACT FROM AUTHOR]

Gait instability is critical in medicine and healthcare, as it has associations with balance disorder and physical impairment. With the development of sensor technology, despite the fact that numerous wearable gait detection and recognition systems have been designed to monitor users' gait patterns, they commonly spend a lot of time and effort to extract gait metrics from signal data. This study aims to design an artificial intelligence-empowered and economic-friendly gait monitoring system. A pair of intelligent shoes with a single inertial sensor and a smartphone application were developed as a gait monitoring system to detect users' gait cycle, stand phase time, swing phase time, stride length, and foot clearance. We recruited 30 participants (24.09 ± 1.89 years) to collect gait data and used the Vicon motion capture system to verify the accuracy of the gait metrics. The results show that the gait monitoring system performs better on the assessment of the gait metrics. The accuracy of stride length and foot clearance is 96.17% and 92.07%, respectively. The artificial intelligence-empowered gait monitoring system holds promising potential for improving gait analysis and monitoring in the medical and healthcare fields. [ABSTRACT FROM AUTHOR]

Background: The quantification of electromyographic activity using surface electrodes is invaluable for understanding gait disorders in patients with central nervous system lesions. We propose to evaluate a commercially available low-cost system compared to a reference system in participants with stroke-related movement disorders in functional situations. Methods: Three hemiparetic participants performed three functional tasks: two treadmill walks at different speeds and a sit-to-stand test. The vastus lateralis and gastrocnemius medialis muscles were equipped with two EMG sensors. The comparison between the two EMG systems was based on 883 identified cycles. Spearman's correlation coefficients (SCs), linear correlation coefficients (LCCs), and cross-correlation coefficients (CCCs) were calculated. Results: The main results indicate good to very good similarity of the EMG signals collected from the two tested sEMG systems. In the comfortable-walking condition, an SC of 0.894 ± 0.091 and an LCC of 0.909 ± 0.094 were noted. In the fast-walking condition, an SC of 0.918 ± 0.064 and an LCC of 0.935 ± 0.056 were observed. For the 1 min sit-to-stand test, an SC of 0.880 ± 0.058 and an LCC of 0.881 ± 0.065 were noted. Conclusions: This study demonstrates good to very good similarity between the two sEMG systems, enabling the analysis of muscle activity during functional tasks. [ABSTRACT FROM AUTHOR]

Parkinson's disease (PD) is the second most common movement disorder in the world. It is characterized by motor and non-motor symptoms that have a profound impact on the independence and quality of life of people affected by the disease, which increases caregivers' burdens. The use of the quantitative gait data of people with PD and deep learning (DL) approaches based on gait are emerging as increasingly promising methods to support and aid clinical decision making, with the aim of providing a quantitative and objective diagnosis, as well as an additional tool for disease monitoring. This will allow for the early detection of the disease, assessment of progression, and implementation of therapeutic interventions. In this paper, the authors provide a systematic review of emerging DL techniques recently proposed for the analysis of PD by using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The Scopus, PubMed, and Web of Science databases were searched across an interval of six years (between 2018, when the first article was published, and 2023). A total of 25 articles were included in this review, which reports studies on the movement analysis of PD patients using both wearable and non-wearable sensors. Additionally, these studies employed DL networks for classification, diagnosis, and monitoring purposes. The authors demonstrate that there is a wide employment in the field of PD of convolutional neural networks for analyzing signals from wearable sensors and pose estimation networks for motion analysis from videos. In addition, the authors discuss current difficulties and highlight future solutions for PD monitoring and disease progression. [ABSTRACT FROM AUTHOR]

Background: Gait event detection is crucial for assessment, evaluation and provision of biofeedback during rehabilitation of walking. Existing online gait event detection algorithms mostly rely on add-on sensors, limiting their practicality. Instrumented treadmills offer a promising alternative by utilizing the Center of Pressure (CoP) signal for real-time gait event detection. However, current methods have limitations, particularly in detecting cross-step events during perturbed walking conditions. Methods: We present and validate a CoP-based algorithm to detect gait events and cross-steps in real-time, which combines thresholding and logic techniques. The algorithm was evaluated on CoP datasets from healthy participants (age range 21–61 years), stroke survivors (age range 20–67 years), and people with unilateral transtibial amputation (age range 28–63 years) that underwent perturbation-based balance assessments, encompassing different walking speeds. Detected gait events from a simulated real-time processing operation were compared to offline identified counterparts in order to present related temporal absolute mean errors (AME) and success rate. Results: The proposed algorithm demonstrated high accuracy in detecting gait events during native gait, as well as cross-step events during perturbed walking conditions. It successfully recognized the majority of cross-steps, with a detection success rate of 94%. However, some misclassifications or missed events occurred, mainly due to the complexity of cross-step events. AME for heel strikes (HS) during native gait and cross-step events averaged at 78 ms and 64 ms respectively, while toe off (TO) AME were 126 ms and 111 ms respectively. A statistically significant difference in the algorithm's success rate score in detecting gait events during cross-step intervals was observed across various walking speeds in a sample of 12 healthy participants, while there was no significant difference among groups. Conclusion: The proposed algorithm represents an advancement in gait event detection on instrumented treadmills. By leveraging the CoP signal, it successfully identifies gait events and cross-steps in the simulated real-time processing operation, providing valuable insights into human locomotion. The algorithm's ability to accommodate diverse CoP patterns enhance its applicability to a wide range of individuals and gait characteristics. The algorithm's performance was consistent across different populations, suggesting its potential for diverse clinical and research settings, particularly in the domains of gait analysis and rehabilitation practices. [ABSTRACT FROM AUTHOR]

Purpose Methods Results Conclusion Level of Evidence The aim of this study was to investigate the influence of medial meniscus posterior root avulsion (MMPRA) before and after surgical treatment on the biomechanics of the knee joint, including suture repair forces during daily and crutch‐assisted gait movements.MMPRA were investigated in eight human cadaver knee joint specimens by a dynamic knee joint simulator with daily (normal gait, gait with additional rotational movement, standing up, sitting down) and rehabilitation‐associated movements (crutch‐assisted gait with limited flexion range of motion [30°] and 30% [toe‐touch weight‐bearing, TTWB] and 50% of body weight [partial weight‐bearing, PWB]) with simulated physiologic muscle forces. Each specimen was tested in intact, torn and repaired (transtibial suture) state. The biomechanical parameters were: medial mean contact pressure and area, knee joint kinematics, medial displacement of the posterior meniscus horn and loading on the anchoring suture.Significant reduction of the contact area due to the avulsion was observed in all movements except for PWB and sitting down. MMPRA repair significantly increased the contact areas during all movements, bringing them to levels statistically indistinguishable from the initial state. MMPRA resulted in a medial displacement up to 12.8 mm (sitting down) and could be reattached with a residual displacement ranging from 0.7 mm (PWB) to 5.7 mm (standing up), all significantly (p < 0.001) reduced compared to the torn state. The mean peak anchoring suture load increased from TTWB (77 N), PWB (91 N) to normal gait (194 N), gait rotation (207 N), sitting (201 N; p < 0.01) and to standing up (232 N; p = 0.03).Surgical treatment of MMPRA allows restoration of physiological knee joint biomechanics. Crutch‐assisted movements reduce the loading of the repair suture, thus likewise the risk for failure. From a biomechanical point of view, crutch‐assisted movements are recommended for the early rehabilitation phase after MMPRA repair.Level V. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the effectiveness of radial extracorporeal shock wave therapy (r ESWT) as an additional treatment modality for spastic equinus deformity in chronic hemiplegic patients. Methods: 100 eligible stroke patients with calf muscles spasticity were randomized into 2 groups. Group I: 50 patients exposed to rESWT 1.500 pulses, 0.10 mJ to 0.3mJ/mm2, with a frequency 4 Hz once weekly for one month. Group II: 50 patients exposed to Sham rESWT once weekly for one month. Clinical, electrophysiological & musculoskeletal ultrasound assessments were done for all patients. Results: After controlling baseline as covariate, the trend for modified Ashworth scale (MAS), Passive ankle dorsiflexion motion (PADFM), 10 meters walk test (10-MWT), and Ratio of maximum H reflex to maximum M response (H/M ratio) after one & two months was significantly different between the two groups, with improvement of all clinical and electrophysiological parameters in group I. Conclusion: ESWT represents a useful non-invasive, additional modality for the reduction of foot spasticity and equinus deformity in stroke patients. Implications for Rehabilitation: Extracorporeal shock wave therapy represents a useful non-invasive, additional modality for reduction of foot spasticity and equinus deformity in chronic stroke patients. The application of such a modality improves limb posture, range of motion, and muscle extensibility. Early extracorporeal shock wave rehabilitative intervention in stroke patients reduces fat infiltration and fibrosis replacement of spastic muscle. [ABSTRACT FROM AUTHOR]

This document is an editorial for a special issue on recent advances in the biomechanics of human movement and its clinical applications. It discusses the challenges of linking research projects to clinical practice and highlights the gaps between potential research activities and clinical applications. The special issue includes 10 articles on various aspects of the research field, providing insights into topics such as postural control adaptations in Parkinson's disease, gait analysis, and the relationship between humans and robots. These articles reflect current progress in the research field and offer valuable information for clinical applications. The document also emphasizes the importance of considering electromyographs (EMGs) and electroencephalograms (EEGs) in clinical practice, as well as the potential applications of artificial intelligence (AI) in biomechanics. It encourages further exploration of new research directions in human movement and its clinical applications. [Extracted from the article]

Featured Application: The applications of this study are significant for elderly gait training and potential gait rehabilitation. AR technology can provide real-time feedback and guided exercises to help improve balance and walking patterns, reducing fall risk among the elderly. Additionally, AR-based rehabilitation can aid in post-stroke recovery and injury rehabilitation by offering personalized feedback and adaptive exercises to enhance gait stability and coordination. Aging often leads to elderly gait characterized by slower speeds, shorter strides, and increased cycle; improving gait can significantly enhance the quality of life. Early gait training can help reduce gait impairment later on. Augmented reality (AR) technologies have shown promise in gait training, providing real-time feedback and guided exercises to improve walking patterns and gait parameters. The aim of this study was to observe the effects of gradual spatial and temporal cues provided by a synchronized walking avatar on the gait of elderly participants. This experiment involved 19 participants aged over 70 years, who walked while interacting with a synchronized walking avatar that provided audiovisual spatial and temporal cues. Spatial cueing and temporal cueing were provided through distance changes and phase difference changes, respectively. The WalkMate AR system was used to synchronize the avatar's walking cycle with the participants', delivering auditory cues matched to foot contacts. This study assessed the immediate and carry-over effects of changes in distance and phase difference on stride length, cycle time, and gait speed. The results indicate that gradual spatial and temporal cueing significantly influences elderly gait parameters, with potential applications in gait rehabilitation and training. [ABSTRACT FROM AUTHOR]

Gait guidance systems that synchronize the gait rhythm with an avatar in a mixed reality (MR) environment are attracting attention owing to their rehabilitation applications. More effective gait guidance can be achieved by changing body sensations for the sense of embodiment (SoE), which refers to the feeling of owning, controlling, and being inside a body in MR. This study investigated full-body synchronous motion between a human and a virtual avatar to enhance the SoE in walking with actual position changes in the real world. The full-body motion and gait rhythm were measured using body-worn inertial measurement units and a visual avatar was provided through a transparent head-mounted display. The results showed that the SoE of the participants was enhanced under higher synchronization conditions. In addition, questionnaire results showed that the SoE in the synchronous condition was significantly higher than that in the asynchronous condition, and the SoE in the self-avatar condition was significantly higher than that in the other-avatar condition. This indicates that a higher synchronization level with the appearance of an avatar leads to a stronger SoE in the human perception mechanism, which is important for potential application in medical or other fields. [ABSTRACT FROM AUTHOR]

The purpose of this quasiexperimental study was to test the effects of wearing the NewGait rehabilitative device on walking abilities in individuals with foot drop. The study involved 16 participants with foot drops caused by stroke (11 participants), multiple sclerosis (one participant), and peripheral neuropathies (four individuals). During a single testing session, participants walked 12 m at their self‐selected speed in four experimental conditions: walking without any orthotic device; walking while wearing a regular plastic posterior leaf ankle foot orthosis (AFO); walking with the NewGait device assisting ankle dorsiflexion only; and walking with the NewGait device assisting the hip, knee, and ankle joint motions. Body motions during walking were recorded using a 3D system for motion analysis and analyzed with a set of spatiotemporal and kinematic parameters and a gait decomposition index. The gait decomposition index indicated sagittal interjoint coordination in the three joint pairs (hip–knee, knee–ankle, and hip–ankle) of the paretic (foot drop) leg during walking and was validated in a previous study. Overall, wearing all three orthotic devices improved the gait velocity, ankle dorsiflexion, and foot clearance compared to gait trials in which no assistive devices were used. However, wearing the AFO significantly restricted the plantarflexion range of motion and decreased interjoint coordination as measured by joint decomposition. In contrast, the NewGait device altered the ankle plantarflexion motions but also increased coordinated movement (reduced the decomposition) in most lower‐extremity joint pairs and conditions. Therefore, the NewGait rehabilitative device can be considered superior to a regular AFO in correcting gait deviations caused by foot drop. [ABSTRACT FROM AUTHOR]

Background: Positive effects of brace treatments in adolescent idiopathic scoliosis patients on gait were proven. Aim: Therefore, this study examined whether the influence of brace therapy in combination with Schroth therapy influencing the plantar pressure distribution, pre and post intensive rehabilitative inpatient treatment. Design: Prospective cohort study, longitudinal. Setting: Scoliosis rehabilitation clinic "Asklepios Katharina-Schroth-Klinik" (Bad Sobernheim, Germany). Population: Twenty (14f/6m) patients (12–16 years) had a medically diagnosed moderate idiopathic scoliosis (Cobb angle 20–50°, Median 30°) and an indication for combined brace and Schroth therapy with an inpatient stay (4 weeks) at the Asklepios Katharina Schroth Clinic (Germany). Methods: At the beginning (T1) and at the end of the stay (T2), the plantar pressure distribution with (A) and without wearing a brace (B) was recorded (walking distance 10 m). Results: No significant differences between the left and right foot were found at baseline (T1). The T1 - T2 comparison of one foot revealed significant differences (p ≤ 0.05 − 0.001, respectively) for (A): mean pressure right midfoot, loaded area total left foot, left midfoot, left inner ball of foot, right midfoot, impulse total right foot, right midfoot and for (B): mean pressure right midfoot, right outer ball of foot, loaded area total right foot, right heel, right midfoot, impulse right heel, right midfoot, right outer ball of foot. Conclusions: A combined brace and Schroth therapy maintains the initial symmetrical plantar pressure distribution over the duration of four weeks since the significant differences fall within the range of measurement error. Clinical rehabilitation impact: The insole measuring system can be used to objectively support therapeutic gait training as part of rehabilitation and to assess insole fitting based on foot shape. Due to its convenient handling and rapid data acquisition, it may be a suitable method for interim or follow-up diagnostics in the treatment of idiopathic scoliosis. [ABSTRACT FROM AUTHOR]

Background: Idiopathic normal pressure hydrocephalus (iNPH) is a prevalent neurological disorder, but its diagnosis remains challenging. Dual-task (DT) walking performance is a reliable indicator of iNPH but less is known about the role of cognitive reserve (CR) in predicting DT walking performance. Aims: The objective of this study was to evaluate the contribution of CR on DT walking in healthy controls (HC) and in iNPH patients (iNPH-P). Methods: 68 iNPH-P (77.2 +/- 6.7 years old) and 28 HC (74.5 +/- 5.7 years old) were evaluated on their single-task walking (Vsimple) and on 4 DT walking (walking and counting or counting backwards, naming animals, naming words beginning with the letter P) (Vcount, VcountB, Vanimals and Vletter respectively). The contribution of CR on the different DT walking speeds was compared between HC and iNPH-P. In iNPH-P, the contribution of CR on the walking speeds was compared with regard to other cognitive, functional, and socio-demographic variables. Results: Simple linear regression demonstrated a moderate influence of CR on single and DT walking speed in iNPH-P (β > 0.3, p <.001) but not in HC where the relation was not significant. In iNPH-P, results showed that CR played a major role in explaining each of the single and DT walking speeds with NPH-scale. Conclusion: As CR could be improved through the life cycle, these results support the idea of developing and supporting physical activity programs that will enrich social, physical, and cognitive resources to protect against age-related functional decline, especially in iNPH-P patients where the age-related deficits are greater. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study is to explore the feasibility of using machine learning approaches to objectively differentiate the mobilization patterns, measured via accelerometer sensors, of patients pre- and post-intervention. Methods: The intervention tested the implementation of a Frailty Care Bundle to improve mobilization, nutrition and cognition in older orthopedic patients. The study recruited 120 participants, a sub-group analysis was undertaken on 113 patients with accelerometer data (57 pre-intervention and 56 post-intervention), the median age was 78 years and the majority were female. Physical activity data from an ankle-worn accelerometer (StepWatch 4) was collected for each patient during their hospital stay. These data contained daily aggregated gait variables. Data preprocessing included the standardization of step counts and feature computation. Subsequently, a binary classification model was trained. A systematic hyperparameter optimization approach was applied, and feature selection was performed. Two classifier models, logistic regression and Random Forest, were investigated and Shapley values were used to explain model predictions. Results: The Random Forest classifier demonstrated an average balanced accuracy of 82.3% (± 1.7%) during training and 74.7% (± 8.2%) for the test set. In comparison, the logistic regression classifier achieved a training accuracy of 79.7% (± 1.9%) and a test accuracy of 77.6% (± 5.5%). The logistic regression model demonstrated less overfitting compared to the Random Forest model and better performance on the hold-out test set. Stride length was consistently chosen as a key feature in all iterations for both models, along with features related to stride velocity, gait speed, and Lyapunov exponent, indicating their significance in the classification. Conclusion: The best performing classifier was able to distinguish between patients pre- and post-intervention with greater than 75% accuracy. The intervention showed a correlation with higher gait speed and reduced stride length. However, the question of whether these alterations are part of an adaptive process that leads to improved outcomes over time remains. [ABSTRACT FROM AUTHOR]

Progressive gait impairment is common among aging adults. Remote phenotyping of gait during daily living has the potential to quantify gait alterations and evaluate the effects of interventions that may prevent disability in the aging population. Here, we developed ElderNet, a self-supervised learning model for gait detection from wrist-worn accelerometer data. Validation involved two diverse cohorts, including over 1000 participants without gait labels, as well as 83 participants with labeled data: older adults with Parkinson's disease, proximal femoral fracture, chronic obstructive pulmonary disease, congestive heart failure, and healthy adults. ElderNet presented high accuracy (96.43 ± 2.27), specificity (98.87 ± 2.15), recall (82.32 ± 11.37), precision (86.69 ± 17.61), and F1 score (82.92 ± 13.39). The suggested method yielded superior performance compared to two state-of-the-art gait detection algorithms, with improved accuracy and F1 score (p < 0.05). In an initial evaluation of construct validity, ElderNet identified differences in estimated daily walking durations across cohorts with different clinical characteristics, such as mobility disability (p < 0.001) and parkinsonism (p < 0.001). The proposed self-supervised method has the potential to serve as a valuable tool for remote phenotyping of gait function during daily living in aging adults, even among those with gait impairments. [ABSTRACT FROM AUTHOR]

Background: End-stage post-traumatic osteoarthritis of the ankle joint may require arthrodesis if conservative treatment fails and a decision against total ankle replacement is made. We aimed to compare the sex-specific differences in outcomes and objectify them using validated specific scores. Methods: Between 2010 and 2021, 221 patients underwent ankle arthrodesis at our institution, including 143 men (MAA) and 78 women (FAA). In addition to demographic data, the aetiology of osteoarthritis, the Foot Function Index (FFI-D), the Olerud-Molander Score (OMAS), and the Short Form-12 questionnaire (SF-12) were collected in this monocentric study. The mean follow-up time was 5.8 years. End-stage osteoarthritis was mostly due to ankle fractures as a result of sprains, falls, and road traffic accidents. Results: Post-operatively, the mean FFI-D for pain was 17.3 (MAA: 14.7; FAA 22.2) and 43.9 for function (MAA: 41.1; FAA 49.5); the mean OMAS was 58.2; and the mean SF-12 physical component score was 42.5. Women achieved significantly worse results in all scores; only the mental component summary of the SF-12 did not differ between the sexes (p > 0.05). Approximately 34% of women stated that the result in terms of gait pattern was worse than expected (MAA 16.1%; p < 0.05). Again, significantly more men stated that the result was better than expected (MAA: 48.3%; FAA: 31.5%, p < 0.05). Conclusions: The fact that the clinical results were significantly worse in women after ankle arthrodesis should be considered when determining the indication. However, the expectations of men and women also need to be individually adjusted. [ABSTRACT FROM AUTHOR]

Introduction: Perturbation walking (PW) has been shown to improve gait, however its effect on the cortical control of gait might provide insights on neural mechanisms underlying falls in adults with osteoarthritis. The objective of this study is to investigate the effect of PW on prefrontal cortical (PFC) activation in older women with (OA) and without osteoarthritis (HOA). We hypothesized that there would be an increase in PFC activation during PW relative to comfortable walking (CW) and higher increase in PFC activation during PW in HOA compared to OA. Methods: Twenty community-dwelling older women (66.7 ± 5.41 years old) walked on an instrumented treadmill that provided perturbations at pseudorandom intervals between 5-25 s using a counterbalanced design. Functional Near Infrared Spectroscopy was used to quantify PFC oxygenated hemoglobin (HbO2) and deoxyhemoglobin (Hb) levels, while standing prior to the task as a baseline. A linear mixed effects model was conducted to investigate the effects of cohort (HOA vs OA), task (PW vs CW), and their interaction on HbO2 (mM) and Hb (mM) levels. Results: HbO2 and Hb levels differed significantly between CW and PW tasks for both cohorts (P < 0.001) and demonstrated significant task by cohort interaction (P < 0.05). In addition, we found changes in walking performance (stride time, stride length, stride width and stance time) during and after PW. Spearman correlation demonstrated a strong association between increased stance time, increased body mass index and decreased PFC activation during PW. No other significant results were found. Discussion: This study found increase in PFC activation during PW and gait adaptation after a short bout of PW in HOA and OA. This increase in PFC activation was higher in HOA compared to OA, particularly during PW tasks, and was consistent with theory of limitations in mobility affecting neural activation in older adults. Further work remains to examine how pain, obesity, and mobility impacts cortical control in older adults with and without osteoarthritis. [ABSTRACT FROM AUTHOR]

Introduction: Gait analysis, an expanding research area, employs non-invasive sensors andmachine learning techniques for a range of applications. In this study, we investigate the impact of cognitive decline conditions on gait performance, drawing connections between gait deterioration in Parkinson's Disease (PD) and healthy individuals dual tasking. Methods: We employ Explainable Artificial Intelligence (XAI) specifically Layer-Wise Relevance Propagation (LRP), in conjunction with Convolutional Neural Networks (CNN) to interpret the intricate patterns in gait dynamics influenced by cognitive loads. Results: We achieved classification accuracies of 98% F1 scores for PD dataset and 95.5% F1 scores for the combined PD dataset. Furthermore, we explore the significance of cognitive load in healthy gait analysis, resulting in robust classification accuracies of 90% ± 10% F1 scores for subject cognitive load verification. Our findings reveal significant alterations in gait parameters under cognitive decline conditions, highlighting the distinctive patterns associated with PD-related gait impairment and those induced by multitasking in healthy subjects. Through advanced XAI techniques (LRP), we decipher the underlying features contributing to gait changes, providing insights into specific aspects affected by cognitive decline. Discussion: Our study establishes a novel perspective on gait analysis, demonstrating the applicability of XAI in elucidating the shared characteristics of gait disturbances in PD and dual-task scenarios in healthy individuals. The interpretability offered by XAI enhances our ability to discern subtle variations in gait patterns, contributing to a more nuanced comprehension of the factors influencing gait dynamics in PD and dual-task conditions, emphasizing the role of XAI in unraveling the intricacies of gait control. [ABSTRACT FROM AUTHOR]

Parkinson's disease (PD) presents diverse symptoms and comorbidities, complicating its diagnosis and management. The primary objective of this cross-sectional, monocentric study was to assess digital gait sensor data's utility for monitoring and diagnosis of motor and gait impairment in PD. As a secondary objective, for the more challenging tasks of detecting comorbidities, non-motor outcomes, and disease progression subgroups, we evaluated for the first time the integration of digital markers with metabolomics and clinical data. Using shoe-attached digital sensors, we collected gait measurements from 162 patients and 129 controls in a single visit. Machine learning models showed significant diagnostic power, with AUC scores of 83–92% for PD vs. control and up to 75% for motor severity classification. Integrating gait data with metabolomics and clinical data improved predictions for challenging-to-detect comorbidities such as hallucinations. Overall, this approach using digital biomarkers and multimodal data integration can assist in objective disease monitoring, diagnosis, and comorbidity detection. [ABSTRACT FROM AUTHOR]

Stiff knee gait (SKG) occurrence after a stroke is associated with various abnormal muscle activities; however, the interactions among these muscles are unclear. This study aimed to elucidate the muscle synergy characteristics during walking in patients with SKG after a stroke. This cross-sectional study included 20 patients with poststroke SKG (SKG group), 16 patients without poststroke SKG (non-SKG group), and 15 healthy adults (control group). Participants walked a 10-m distance at a comfortable speed, and electromyographic data were recorded from six lower-limb muscles. Non-negative matrix factorization was employed to derive time-varying activity (C), muscle weights (W), and the percentage of total variance accounted for (tVAF) for muscle synergies. The SKG group showed a higher tVAF than the control group. The initial stance module (including knee extensors) showed increased activity during the swing phase. The initial swing module (including hip flexors and ankle dorsiflexors) exhibited a higher activity during the single-support phase but a lower activity during the swing phase. The synergy structure in patients with SKG after stroke was simplified, with specific abnormalities in synergy activities. SKG may arise from several synergy alterations involving multiple muscles, indicating that approaches focused on controlling individual muscle activities are unsuitable. [ABSTRACT FROM AUTHOR]

Patients with advanced Parkinson's disease often suffer from severe gait and balance problems, impacting quality of live and persisting despite optimization of standard therapies. The aim of this review was to systematically review the efficacy of STN-DBS programming techniques in alleviating gait disturbances in patients with advanced PD. Searches were conducted in PubMed, Embase, and Lilacs databases, covering studies published until May 2024. The review identified 36 articles that explored five distinct STN-DBS techniques aimed at addressing gait and postural instability in Parkinson's patients: low-frequency stimulation, ventral STN stimulation for simultaneous substantia nigra activation, interleaving, asymmetric stimulation and a short pulse width study. Among these, 21 articles were included in the meta-analysis, which revealed significant heterogeneity among studies. Notably, low-frequency STN-DBS demonstrated positive outcomes in total UPDRS-III score and FOG-Q, especially when combined with dopaminergic therapy. The most favorable results were found for low-frequency STN stimulation. The descriptive analysis suggests that unconventional stimulation approaches may be viable for gait problems in patients who do not respond to standard therapies. [ABSTRACT FROM AUTHOR]

Introduction: There has been an advent in the use of Mobile Apps in the academic space. The pandemic hastened their usage, and forced us to rapidly innovate in order to meet the educational needs of our students. Also, Mobile Apps have been known to facilitate self-learning, make it enjoyable, and personalize the pace of learning of the individual. Given the level of skill-learning in Physiotherapy education, the use of Mobile Apps can pose a challenge, as well as offer an opportunity to explore its scope to enhance learning, and create innovative pedagogic strategies. There are a very few learning mobile apps that have been assessed in Physiotherapy education. Aim: To develop, establish content validity and internal consistency of a curriculum based App on the kinesiology of normal Gait for bachelor of physiotherapy students, and to evaluate the App with regards to use, quality, engagement, and overall experience. Materials & methods: In the first phase, a mobile app based on a bachelor of physiotherapy Gait curriculum was developed and validated using Delphi procedure, with 80% agreement criteria, by a group of experts. Subsequently, the App was rated by 200 users on: engagement, aesthetics, information, subjective quality. Results: The content validity index following 2 rounds of Delphi was found to be 0.88. Also, therapists found the App easy to use, and 80% gave it a rating of > 3 stars. Conclusion: Creating, designing, implementing, and evaluating the efficacy of a Gait App as a means to teaching the GAIT component to physiotherapy students was found to be appealing and beneficial. [ABSTRACT FROM AUTHOR]

Purpose: Gait disturbances are common in human low back pain (LBP) patients, suggesting potential applicability to rodent LBP models. This study aims to assess the influence of disc-associated LBP on gait in female Sprague Dawley rats and explore the utility of the open-source Gait Analysis Instrumentation and Technology Optimized for Rodents (GAITOR) suite as a potential alternative tool for spontaneous pain assessment in a previously established LBP model. Materials and Methods: Disc degeneration was surgically induced using a one-level disc scrape injury method, and microcomputed tomography was used to assess disc volume loss. After disc injury, axial hypersensitivity was evaluated using the grip strength assay, and an open field test was used to detect spontaneous pain-like behavior. Results: Results demonstrated that injured animals exhibit a significant loss in disc volume and reduced grip strength. Open field test did not detect significant differences in distance traveled between sham and injured animals. Concurrently, animals with injured discs did not display significant gait abnormalities in stance time imbalance, temporal symmetry, spatial symmetry, step width, stride length, and duty factor compared to sham. However, comparisons with reference values of normal gait reported in prior literature reveal that injured animals exhibit mild deviations in forelimb and hindlimb stance time imbalance, forelimb temporal symmetry, and hindlimb spatial symmetry at some time points. Conclusions: This study concludes that the disc injury may have very mild effects on gait in female rats within 9 weeks post-injury and recommends future in depth dynamic gait analysis and longer studies beyond 9 weeks to potentially detect gait. [ABSTRACT FROM AUTHOR]

Background: Individuals may exhibit altered foot pronation during gait when fatigue sets in. Therefore, a more evidence-based understanding of these fatigue-induced changes may be helpful for future gait analysis and return-to-play tests since fatigue can provide new insights that might explain a person's complaints. Methods: A total of 25 healthy individuals (12♂, 13♀; 24.3 ± 2.7 years; 174.9 ± 9.09 cm; 70 ± 14.2 kg; BMI: 22.7 ± 2.8) participated in this controlled non-randomized study of unilateral fatigue of the right foot's stabilizing muscles with regard to the pronation of the foot, measured by navicular drop (ND) in static (statND; standing) and dynamic (dynND; walking) states. The left foot served as the control. Surface electromyography was used to verify fatigue. Results: While the statND did not change, the dynND increased significantly by 1.44 ± 2.1 mm (=22.3%) after the foot-stabilizing muscles experienced fatigue. No correlation was found between the statND and dynND. Conclusions: Muscular fatigue can affect foot pronation. The dynND appears to be more representative of the loads in everyday life, whereby most studies use the statND. [ABSTRACT FROM AUTHOR]

This study examined the effect of age and surface on patellofemoral joint (PFJ) stress magnitude and waveform during stair ascent and descent tasks. A total of 12 young and 12 older adults had knee biomechanics quantified while they ascended and descended stairs on normal, slick, and uneven surfaces. The peak of stance (0–100%) PFJ stress and associated components were submitted to a two-way repeated measures ANOVA, while the PFJ stress waveform was submitted to statistical parametric mapping two-way ANOVA. During stair ascent, older adults exhibited greater PFJ stress waveforms, from 55 to 59% and 74 to 84% of stance (p < 0.001) as well as greater PFJ stress–time integral across stance (p = 0.003), and later peak PFJ stress, than young adults (p = 0.002). When ascending on the uneven surface, participants exhibited smaller PFJ stress from 9 to 24% of stance compared to the normal surface, but greater PFJ stress from 75 to 88% and from 63 to 68% of stance (p < 0.001) as well as greater PFJ stress–time integrals compared to normal and slick surfaces (p < 0.032). During stair descent, older adults exhibited a smaller PFJ contact area range (p = 0.034) and peak knee flexion angle (p = 0.022) than young adults. When descending on the slick surface, participants exhibited smaller PFJ stress from 5 to 18% of stance, but greater stress, from 92 to 98% of stance (both: p < 0.001), compared to the normal surface. Negotiating slick and uneven stairs may produce knee biomechanics that increase PFJ stress, and the larger, later PFJ stress exhibited by older adults may further increase their risk of PFJ pain. [ABSTRACT FROM AUTHOR]