Search

Vertical loading rate (VLR) and pelvic floor muscle activity (PFA) increase with running velocity, which may indicate a relationship between VLR and PFA. Foot strike pattern has been shown to influence VLR while running, but little is known about its influence on PFA. Twenty healthy women ran on a treadmill for 2 conditions: with a rearfoot strike and with a forefoot strike. PFA was measured with electromyography. Running kinematics associated with VLR were collected using inertial measurement units and tibial accelerometers. Change scores between conditions were calculated for average PFA and running kinematics: peak vertical tibial acceleration, vertical excursion of the center of mass (VO), and cadence. Paired t tests assessed differences between running conditions for all variables. Pearson correlations assessed the relationships between changes in PFA and running kinematics. PFA was significantly higher during the forefoot compared with the rearfoot strike condition. Change in vertical tibial acceleration was positively correlated with change in PFA during the right stance. Change in cadence was negatively correlated, and change in vertical excursion of the center of mass was positively correlated with change in PFA during left stance. The average PFA increased during the forefoot strike pattern condition. Changes in PFA were correlated with changes in running kinematics associated with VLR. [ABSTRACT FROM AUTHOR]

Time series biomechanical data inform our understanding of normal gait mechanics and pathomechanics. This study examines the utility of different quantitative methods to distinguish vertical ground reaction forces (VGRFs) from experimentally distinct gait strategies. The goals of this study are to compare measures of VGRF data—using the shape factor method and a Fourier series-based analysis—to (1) describe how these methods reflect and distinguish gait patterns and (2) determine which Fourier series coefficients discriminate normal walking, with a relatively stiff-legged gait, from compliant walking, using deep knee flexion and limited vertical oscillation. This study includes a reanalysis of previously presented VGRF data. We applied the shape factor method and fit 3- to 8-term Fourier series to zero-padded VGRF data. We compared VGRF renderings using Euclidean L2 distances and correlations stratified by gait strategy. Euclidean L2 distances improved with additional harmonics, with limited improvement after the seventh term. Euclidean L2 distances were greater in shape factor versus Fourier series renderings. In the 8 harmonic model, amplitudes of 9 Fourier coefficients—which contribute to VGRF features including peak and local minimum amplitudes and limb loading rates—were different between normal and compliant walking. The results suggest that Fourier series-based methods distinguish between gait strategies. [ABSTRACT FROM AUTHOR]

Previous research has shown that there are differences in mechanical energy, kinematics, and muscle activation when comparing walking on level and incline surfaces, especially on inclines above 15%. Muscle activations are significantly different while walking on extreme inclines, suggesting a different coordination pattern. We utilized continuous relative phase to assess walking kinematic coordination with respect to increased incline angles. Twelve healthy, college-aged individuals walked for 7 inclines of 1 minute each on a motorized treadmill at 3 mph at 0%, 5%, 10%, 15%, 20%, 25%, and 30% inclines. Kinematic data were collected during the last 20 seconds of each stage (120 Hz). Segmental and joint angles and angular velocities in the sagittal plane were calculated, from which continuous relative phase was determined for 3 joint couples: hip–knee, hip–ankle, and knee–ankle. There were significant differences in the coordination patterns during the first part of the contact phase in the hip–knee and hip–ankle couplings between the 0% and 30% inclines, with all 3 joint couplings becoming more in-phase at inclines above 15%. Importantly, the hip–knee coupling changed significantly from more out-of-phase to more in-phase between 10% and 15% incline. Shifting lower-extremity joint coordination in response to extreme inclines identifies potential coordinative strategies to achieve steep walking. [ABSTRACT FROM AUTHOR]

This cross-sectional study examined the immediate effects of four types of real-time feedback during overground gait performed using inertial measurement units on gait kinematics in healthy young participants. Twelve healthy young pamcipants (mean age: 27.1 years) performed 60-s gait trials with each of the following real-time feedback: walking spontaneously (no feedback trial); increasing the ankle plantar-flexion angle during the late stance (ankle trial); increasing the leg extension angle, defined the location of the ankle joint relative to the hip joint in the sagittal plane, during late stance (leg trial); and increasing the knee flexion angle during the swing phase (knee trial). Tilt angles and accelerations of the pelvis and lower limb segments were measured using seven inertial measurement units pre- and postfeedback trials. The differences in gait parameters pre- and postfeedback according to the types of feedback were compared using one-factor repeated-measures analysis of variance, Friedman test, and post hoc test. Real-time feedback in the ankle trial increased gait speed, step length, and ankle plantar-flexion angle compared to the no feedback trial (p. ≤ .001). Meanwhile. real-time feedback in the leg trial increased step length and hip extension angle compared to the no feedback trial (p ≤ .001) and showed a tendency to increase gait speed and leg extension angle. Real-time feedback using inertial measurement units increased gait speed immediately with specific changes in gait kinematics in healthy participants. This study might imply the possibility of clinical application for overground gait training. and further studies are needed to clarify the effectiveness for older people. [ABSTRACT FROM AUTHOR]

BACKGROUND: Rotator cuff muscle degeneration (muscle atrophy, fibrosis and fatty infiltration) is a common condition after rotator cuff tears, which seriously affects shoulder function and surgical outcomes. Ginsenoside Rg1 has biological effects such as anti-oxidation, anti-apoptosis and lipid-lowering. However, the effect of ginsenoside Rg1 on muscle degeneration after rotator cuff tear has not been reported. OBJECTIVE: To investigate the effect of ginsenoside Rg1 on muscle degeneration after massive rotator cuff tear in mice. METHODS: Sixty C57BL/6J mice were randomly divided into sham group, model group, ginsenoside Rg1 low dose group and ginsenoside Rg1 high dose group, with 15 mice in each group. The skin of the right shoulder of mice in the sham group was cut and sutured. Massive rotator cuff tear mouse models of the right shoulder were established in the other three groups. Supraspinatus tendon and suprascapular nerve compression were administrated. Mice in the sham and model groups were intraperitoneally injected with 0.5 mL of saline after operation, while those in the ginsenoside Rg1 low and high dose groups were intraperitoneally injected with ginsenoside Rg1 30 and 60 mg/kg respectively, once a day, for 6 weeks. Mice were assessed for limb function by gait analysis the day after the last injection. After euthanasia, the supraspinatus muscle on the operated side was taken to measure the muscle atrophy rate and muscle contractility. Muscle tissue was stained with oil red O and Masson. RT-PCR was used to detect the expression of atrophy, fibrosis, and fatty infiltration related genes. RESULTS AND CONCLUSION: Compared with the model group, low- and high-dose ginsenoside Rg1 significantly increased paw print area and step length (P < 0.05). Compared with the model group, low- and high-dose ginsenoside Rg1 significantly increased myofiber cross-sectional area and supraspinatus contractility (P < 0.05), and significantly decreased wet muscle mass reduction ratio, fatty infiltration area ratio, and collagen fiber area ratio (P < 0.05). Compared with the model group, low- and high-dose ginsenoside Rg1 significantly decreased the expression of atrophy, fibrosis, and fatty infiltration related genes (P < 0.05). There was no significant difference in paw print area, supraspinatus muscle contractility, and myofiber cross-sectional area between ginsenoside Rg1 low and high dose groups (P > 0.05), and all other indexes were better in the ginsenoside Rg1 high dose group than in the ginsenoside Rg1 low dose group (P < 0.05). To conclude, ginsenoside Rg1 could significantly reduce muscle atrophy, fibrosis and fatty infiltration following massive rotator cuff tear in mice, which is beneficial to improve muscle strength and limb function. [ABSTRACT FROM AUTHOR]

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]

Flatfoot is an orthopedic malformation where the inner foot arch flattens during motion, potentially leading to chronic musculoskeletal issues. Monitoring foot conditions is essential, as existing screening methods often need more objectivity and cost‐effectiveness. This research develops an insole‐based screening device using self‐powered triboelectric nanogenerators (TENGs) as tactile sensors and Arduino hardware setup. TENG converts mechanical energy into electrical energy, offering simple fabrication, cost‐effectiveness, longevity, and high‐output power benefits. The device records the electrical output generated by foot movements via Arduino and sends data via Bluetooth to the processing tool. Machine learning algorithms employing the Random Forest Classifier process the data to detect flatfoot conditions accurately after training sessions. For data collection, 100 participants are asked to march and walk for the same duration and distance, ensuring consistent output. Analysis reveals that the insoles' middle sensors produce higher electricity levels in individuals with flatfoot, showing a uniform pressure distribution across the foot and contact in the arch area. In contrast, individuals with normal feet exert more pressure on the toe and heel foot areas. The system achieves an overall accuracy of 82%, demonstrating the insole's potential as a commercial flatfoot detection device. [ABSTRACT FROM AUTHOR]

Background Objectives Methods Results Conclusions Reduced cerebrospinal fluid (CSF) clearance may play a vital role in the pathogenesis of normal pressure hydrocephalus (NPH), but the radiologic marker is yet to be elucidated.This open‐label study presents two novel neuroimaging biomarkers based on enlarged perivascular spaces (ePVS) of the sub‐insular territory: the Hedgehog and Hedgehog‐Halo (H‐H) sign, designed to predict gait symptom severity and tap response in NPH.We retrospectively reviewed 203 patients with possible NPH with baseline magnetic resonance imaging and gait analyses before and after lumbar puncture (LP). The Hedgehog/H‐H sign was scored using T2‐weighted images. The clinical severity at baseline and post‐tap gait improvement was compared in patients with and without Hedgehog/H‐H sign. The association between Hedgehog/H‐H sign and post‐tap gait outcomes was assessed using multivariate regression. The diagnostic performance of Hedgehog/H‐H sign was compared with conventional radiological markers.Patients with H‐H showed higher global disability and more severe gait impairment than those without any signs. Following LP, patients with Hedgehog/H‐H sign significantly improved in various gait parameters, unlike those with neither sign. Additionally, sub‐insular ePVS was significantly associated with post‐tap gait improvement after adjusting covariates. Finally, the Hedgehog/H‐H sign showed a higher performance than conventional markers in predicting post‐tap gait response.The Hedgehog/H‐H sign is a useful neuroimaging biomarker related to the severity and tap response in NPH. This biomarker can be readily applied in clinical practice before undergoing LP, independent of conventional radiological signs. Further research is warranted to determine applicability in predicting post‐shunt gait response. [ABSTRACT FROM AUTHOR]

ABSTRACT Objective Methods Results Conclusion The gait analysis of patients after surgery for tumors around the knee joint relies on the use of a three‐dimensional motion capture system. However, obtaining long‐term, free‐standing, real‐world gait data with three‐dimensional gait analysis is challenging. In this study, we utilized a portable gait analyzer to collect gait data from patients who underwent rotating hinge knee megaprosthesis (RHK) and total knee arthroplasty (TKA), this study aims to compare via gait analysis patients who underwent megaprosthesis with patients with TKA.A retrospective study was conducted on eight patients with knee bone tumors (RHK group) and ten patients with knee osteoarthritis who underwent standard TKA (TKA group) from January 2018 to January 2022. Gait analysis, was conducted using the Intelligent Device for Energy Expenditure and Activity (IDEEA), and the results were compared with those of a healthy control group. The lower limb alignment of the RHK and TKA groups was evaluated, and the KSS scores of the two groups were collected and compared. Energy consumption during a 20‐m walk was measured and compared among the RHK, TKA, and healthy control groups using one‐way ANOVA. Paired t‐tests were used to compare the operated and nonoperated limbs within groups.All patients exhibited slower walking speeds and cadence than the healthy control participants (p < 0.01), While no significant differences were found between the RHK and TKA groups. The single support time (521.15 ± 94.56 ms) of the RHK‐operated limb was significantly shorter than that of the nonoperated limb (576.53 ± 77.40 ms, p = 0.004). The pulling acceleration of the RHK group (0.71 ± 0.27 G) was lower than that of the TKA group (1.04 ± 0.31 G, p = 0.029). The push‐off angle in the RHK group (24.91° ± 10.91°) was significantly greater than that in the TKA group (10.64° ± 5.41°, p = 0.007). The RHK group showed significant differences between the operated and nonoperated limbs in terms of swing power, ground impact, footfall, and push‐off. The RHK (0.03 ± 0.01 kcal/min/kg) and TKA (0.029 ± 0.01 kcal/min/kg) groups had significantly greater energy expenditures than did the healthy control group (0.02 ± 0.00 kcal/min/kg, p < 0.05). The comparison of HKA angles and KSS scores between the TKA and RHK groups showed statistically significant differences.A portable gait analyzer appears to be suitable for evaluating the effects of RHK. RHK patients demonstrate more pronounced gait abnormalities than TKA patients, reflected in greater energy expenditure, implying reduced walking efficiency. This suggests the need for increased energy expenditure in RHK patients to compensate for abnormal knee joint conditions during walking and maintain body balance. [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]

Diabetic foot ulcers (DFUs) present a substantial health risk across diverse age groups, creating challenges for healthcare professionals in the accurate classification and grading. DFU plays a crucial role in automated health monitoring and diagnosis systems, where the integration of medical imaging, computer vision, statistical analysis, and gait information is essential for comprehensive understanding and effective management. Diagnosing DFU is imperative, as it plays a major role in the processes of diagnosis, treatment planning, and neuropathy research within automated health monitoring and diagnosis systems. To address this, various machine learning and deep learning‐based methodologies have emerged in the literature to support healthcare practitioners in achieving improved diagnostic analyses for DFU. This survey paper investigates various diagnostic methodologies for DFU, spanning traditional statistical approaches to cutting‐edge deep learning techniques. It systematically reviews key stages involved in diabetic foot ulcer classification (DFUC) methods, including preprocessing, feature extraction, and classification, explaining their benefits and drawbacks. The investigation extends to exploring state‐of‐the‐art convolutional neural network models tailored for DFUC, involving extensive experiments with data augmentation and transfer learning methods. The overview also outlines datasets commonly employed for evaluating DFUC methodologies. Recognizing that neuropathy and reduced blood flow in the lower limbs might be caused by atherosclerotic blood vessels, this paper provides recommendations to researchers and practitioners involved in routine medical therapy to prevent substantial complications. Apart from reviewing prior literature, this survey aims to influence the future of DFU diagnostics by outlining prospective research directions, particularly in the domains of personalized and intelligent healthcare. Finally, this overview is to contribute to the continual evolution of DFU diagnosis in order to provide more effective and customized medical care. This article is categorized under:Application Areas > Health CareTechnologies > Machine LearningTechnologies > Artificial Intelligence [ABSTRACT FROM AUTHOR]

Step counting devices were previously shown to be efficient in a variety of applications such as athletic training or patient's care programs. Various sensor placements and algorithms were previously experimented, with a best mean absolute percentage error (MAPE) close to 1% in simple mono-activity walking conditions. In this study, an existing running shoe was first instrumented with an inertial measurement unit (IMU) and used in the context of multi-activity trials, at various speeds, and including several transition phases. A total of 21 participants with diverse profiles (gender, age, BMI, activity style) completed the trial. The data recorded was used to develop a step counting algorithm based on a deep learning approach, and further validated against a k-fold cross validation process. The results revealed that the step counts were highly correlated to gyroscopes and accelerometers norms, and secondarily to vertical acceleration. Reducing input data to only those three vectors showed a very small decrease in the prediction performance. After the fine-tuning of the algorithm, a MAPE of 0.75% was obtained. Our results show that such very high performances can be expected even in multi-activity conditions and with low computational resource needs making this approach suitable for embedded devices. [ABSTRACT FROM AUTHOR]

Background: Both high body mass index (BMI) and anterior cruciate ligament reconstruction (ACLR) independently influence knee osteoarthritis risk. Preliminary evidence shows the combination of these risk factors leads to poorer recovery and altered biomechanical outcomes after ACLR, but few studies have directly evaluated early changes in cartilage health between normal-BMI and high-BMI groups in this population. Purpose: To evaluate ultrasound-based measures of cartilage strain and compositional changes (via echo-intensity [EI]) in response to an incline walking stress test between normal-BMI and high-BMI individuals with ACLR. A secondary evaluation was conducted of associations between habitual walking biomechanics (ie, ground-reaction forces, sagittal knee kinetics and kinematics) and cartilage strain and EI outcomes. Study Design: Controlled laboratory study. Methods: Gait biomechanics and femoral trochlear ultrasound analyses were evaluated in 64 participants with ACLR who had normal BMI (BMI < 27.0; n = 40) and high BMI (BMI ≥ 27.0; n = 24). Ultrasound images were collected bilaterally before and after an incline treadmill walk, and medial and lateral trochlear strain and EI changes pre-post exercise were used to compare BMI groups and limbs. Gait outcomes included ground-reaction forces, peak sagittal plane knee moments, angles, and excursions and were used to determine associations with cartilage outcomes in the entire cohort. Results: High-BMI individuals with ACLR exhibited greater medial trochlear cartilage strain in the ACLR limb compared with normal-BMI individuals (approximately 6%; P <.01). In those with high BMI, the ACLR limb exhibited greater medial trochlear strain relative to non-ACLR limbs (approximately 4%; P <.05), but between-limb differences were not observed in the normal-BMI group (P >.05). Medial trochlear EI changes were greater bilaterally in those with high BMI compared with normal-BMI ACLR counterparts (approximately 10%; P <.01). Last, individuals who walked with greater peak knee flexion angles exhibited less medial cartilage strain (Δ R 2 = 0.06; P =.025). Conclusion: The data suggested that high BMI affects cartilage functional properties after ACLR, whereas smaller knee flexion angles were associated with larger medial cartilage strain. Clinical Relevance: High-BMI individuals with ACLR may represent a subset of patients exhibiting earlier declines in cartilage functional integrity in response to loading, necessitating additional or more targeted interventions to mitigate disease development. [ABSTRACT FROM AUTHOR]

The anterior cruciate ligament plays a crucial role in maintaining stability within the knee joint, particularly for athletes who frequently experience its rupture. This study presents a novel approach using personalized three-dimensional (3D) parametric finite element modeling of the knee joint to simulate the treatment following anterior cruciate ligament reconstruction (ACLR) in both forward walking (FW) and drop landing (DL) tasks. The study encompasses two distinct cohorts: five healthy athletes and five ACLR patients. Biomechanical motion analysis was conducted on both cohorts, with the ACLR patient group evaluated at 6 and 9 months post-surgery. A comprehensive 3D parametric model of the knee joint was meticulously crafted. The findings reveal a notable reduction in stress on crucial knee structures such as the autograft, meniscus, and cartilages over time for both FW and DL tasks following ACLR, with a reduction in tissue tension of approximately 9.5% and 37% for FW and DL, respectively. This personalized model not only facilitates the investigation of knee joint tissue biomechanics post-ACLR but also aids in estimating the return-to-sports timeline for patients. By accommodating individual tissue geometries and incorporating patient-specific kinetic data, this model enhances our comprehension of post-ACLR biomechanics across various functional tasks, thereby optimizing rehabilitation strategies. [ABSTRACT FROM AUTHOR]

We estimated the severity of cerebellar ataxia by analyzing gait rhythm. We measured the step times in patients with pure cerebellar ataxia and healthy controls and then analyzed the distribution of the ratios of adjacent times. Gait rhythm displayed the best adaptation when expressed as the sum of the power law and lognormal distributions in both groups, and the groups could be distinguished by the exponent of the power law distribution, reflecting the fractal property of gait rhythm. Gait rhythm might reflect different features of impairment in patients with cerebellar ataxia, making it a useful continuous scale for cerebellar ataxia. • We identified a novel pattern of gait rhythm distribution caused by cerebellar ataxia. • A linear combination of power law and lognormal components optimized the fitting of the cumulative gait rhythm distribution. • The power law was indicative of the fractal property of gait rhythm. • The two components correlated SARA kinetic and gait/posture subscores, respectively. • Gait rhythm analysis could provide a useful continuous scale for cerebellar ataxia. [ABSTRACT FROM AUTHOR]

Purpose: Flexible flatfoot (FF) can interrupt children's activity through uneven pressure distribution to the medial column of the foot and may require surgery. Medialising calcaneal osteotomy (MCO) helps restore the foot‒tripod complex. The objective was to compare pedobarography and ankle‒foot kinematics in children with symptomatic FF after MCO to those in controls. Methods: Gait analysis was performed on 21 children with FF (37 feet, age 13.7 ± 4.9 years) 4.5 ± 3.4 years after MCO and on 21 controls (42 feet, age 12.1 ± 1.1 years). Ankle‒foot kinematics and pedobarography parameters (maximum pressure, impulse, contact area, and percentage of contact time in the stance phase) of ten anatomic foot regions from an average of five gait trials were compared. The functional outcome was determined by the AOFAS-AHFS score in the FF group. Results: The average AOFAS-AHFS score was 96. The FF group had a larger contact area and expressed more force on the medial column of the foot. The maximum pressure, impulse, contact area, and percentage of contact time in the stance phase in the midfoot region for the FF and control groups were 0.66 ± 0.5 vs. 0.24 ± 0.4 N/cm2 (p = 0.005), 0.12 ± 0.1 vs. 0.03 ± 0.1 Ns/cm2 (p = 0.02), 47.1 ± 13.4 vs. 30.1 ± 7.1 cm2 (p < 0.001), and 53.7 ± 17.4 vs. 68.2 ± 15.7% (p = 0.007), respectively. The kinematics of the FF exhibited a greater range of abduction and eversion during the mid- and terminal-stance phases of the gait cycle. Conclusions: The MCO procedure did not normalise the pressure on the midfoot in FF to the level of that in the controls, and the deformity persisted in the forefoot. [ABSTRACT FROM AUTHOR]

Most exoskeletons designed to assist users in load-bearing tasks face a mechanical dilemma in their conception. Designers may find a compromise between stiff active actuators-based architectures which are powerful but bulky and compliant actuator-based designs which are much less assistive but less constraining for users. This article presents a new open-source simulation-based design tool and a human-centered method that lets orthosis designers explore different device configurations and evaluate some performance criteria. This framework was applied in three different young-adult subjects. The effects of design personalization on user morphology and gait were studied. First, an ankle–foot orthosis designed to support a 20 kg backpack was defined according to the user's height, weight, and walking speed. Then, a simulation of the subjects fitted with their customized design walking at a self-selected speed on flat ground carrying this additional load was performed. First, the results showed that the designed method inspired by natural joint stiffness behavior provided viable personalized mechanisms. Second, significant reductions in peak joint torque and mean joint activity were observed when comparing muscle-generated torques while the subject was wearing the 20 kg backpack with ankle–foot orthoses on both legs or without. Finally, it shows the value of an open-access tool for exploring the coupling of passive and active actuators to generate lighter and more compliant designs. [ABSTRACT FROM AUTHOR]

Introduction: We studied the postural behaviour of a 52-year-old professional mountain climber who underwent bilateral amputation of all five toes after severe frostbite. Methods: Two tasks were examined: static posturography (SP) and gait initiation (GI), both performed barefoot and with prosthetic shoes. During SP, the participant kept the upright stance for 30 s while an optoelectronic system with reflective markers recorded feet position and body sway, and two force plates measured the Center of Pressure (CoP) displacement and Ground Reaction Force (GRF) of each foot. During GI, the participant stood on the force plates for at least 10 s and then spontaneously started walking, while optoelectronic system was used to monitor heel-off events; wireless EMG probes recorded the anticipatory postural adjustments (APAs) in trunk and lower limb muscles. Results: Compared to shod condition, during barefoot SP the participant showed a reduced anteroposterior (AP) and mediolateral (ML) extension of the Base of Support (BoS), and the whole-body CoP shifted about 7 mm more anteriorly, approaching the "safer" geometric center of the BoS. Despite this difference, the AP and ML ranges of CoP oscillations were similar in both conditions. In GI, the trunk dorsal muscles showed different APA patterns: when barefoot they were excitatory in the trailing and inhibitory in the leading side while they were bilaterally inhibitory when shod. Discussion: In parallel to CoP shift toward a "safer" position in SP, in barefoot GI the body rotation toward the trailing side may reveal a more "cautious" approach; this also shows that different postural strategies may be adopted in GI by one and the same individual. [ABSTRACT FROM AUTHOR]

Background: The relationship of running biomechanics, footwear, and injury has been studied extensively in adults. There has been little research on the effects of footwear on running biomechanics in youth. Hypothesis: Running biomechanics of youth will be significantly affected by changes in footwear. Minimal shoe running will demonstrate similarities to barefoot. Study Design: Crossover study design: randomized trial. Level of Evidence: Level 2. Methods: A total of 14 active male youth (8-12 years old) participants with no previous exposure to minimalist shoes or barefoot running had running biomechanics (lower extremity sagittal plane kinematics and vertical ground reaction forces [vGRFs]) collected and analyzed in 3 footwear conditions (barefoot, traditional, and minimal shoe). Results: The average vertical loading rate (AVLR) was significantly greater running barefoot (173.86 bodyweights per second [BW/s]) and in the minimal shoe (138.71 BW/s) compared with the traditional shoe (78.06 BW/s), (P < 0.01). There were significant differences between shoe conditions for knee flexion at initial contact (P < 0.01), knee sagittal plane excursion (P < 0.01), peak dorsiflexion (P < 0.01), and dorsiflexion at initial contact (P = 0.03). No participants displayed a forefoot-strike during this study. Conclusion: The introduction of barefoot and minimalist running in habitually shod youth significantly affected the running biomechanics of youth and caused immediate alterations in both lower extremity kinematics and vGRFs. Running barefoot or in minimal shoes dramatically increased the AVLR, which has been associated with injury, compared with a traditional shoe. Clinical Relevance: This study evaluated the effects of footwear on overground running biomechanics, including AVLR, in pre- and early-adolescent youth males. Based on our findings, clinicians should exercise caution in barefoot or minimal shoe transition among young, habitually shod, runners due to the immediate and dramatic increases in AVLRs. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the effectiveness of multimodal features based on gait analysis and eye tracking for elderly people screening with subjective cognitive decline in the community. Methods: In the study, 412 cognitively normal older adults aged over 65  years were included. Among them, 230 individuals were diagnosed with non-subjective cognitive decline and 182 with subjective cognitive decline. All participants underwent assessments using three screening tools: the traditional SCD9 scale, gait analysis, and eye tracking. The gait analysis involved three tasks: the single task, the counting backwards dual task, and the naming animals dual task. Eye tracking included six paradigms: smooth pursuit, median fixation, lateral fixation, overlap saccade, gap saccade, and anti-saccade tasks. Using the XGBoost machine learning algorithm, several models were developed based on gait analysis and eye tracking to classify subjective cognitive decline. Results: A total of 161 gait and eye-tracking features were measured. 22 parameters, including 9 gait and 13 eye-tracking features, showed significant differences between the two groups (p  <  0.05). The top three eye-tracking paradigms were anti-saccade, gap saccade, and median fixation, with AUCs of 0.911, 0.904, and 0.891, respectively. The gait analysis features had an AUC of 0.862, indicating better discriminatory efficacy compared to the SCD9 scale, which had an AUC of 0.762. The model based on single and dual task gait, antisaccade, gap saccade, and median fixation achieved the best efficacy in SCD screening (AUC  =  0.969). Conclusion: The gait analysis, eye-tracking multimodal assessment tool is an objective and accurate screening method that showed better detection of subjective cognitive decline. This finding provides another option for early identification of subjective cognitive decline in the community. [ABSTRACT FROM AUTHOR]

AbstractWearable technologies such as inertial measurement units (IMUs) can be used to evaluate human gait and improve mobility, but sensor fixation is still a limitation that needs to be addressed. Therefore, aim of this study was to create a machine learning algorithm to predict gait events using a single IMU mimicking the carrying of a smartphone. Fifty-two healthy adults (35 males/17 females) walked on a treadmill at various speeds while carrying a surrogate smartphone in the right hand, front right trouser pocket, and right jacket pocket. Ground-truth gait events (e.g. heel strikes and toe-offs) were determined bilaterally using a gold standard optical motion capture system. The tri-dimensional accelerometer and gyroscope data were segmented in 20-ms windows, which were labelled as containing or not the gait events. A long-short term memory neural network (LSTM-NN) was used to classify the 20-ms windows as containing the heel strike or toe-off for the right or left legs, using 80% of the data for training and 20% of the data for testing. The results demonstrated an overall accuracy of 92% across all phone positions and walking speeds, with a slightly higher accuracy for the right-side predictions (∼94%) when compared to the left side (∼91%). Moreover, we found a median time error <3% of the gait cycle duration across all speeds and positions (∼77 ms). Our results represent a promising first step towards using smartphones for remote gait analysis without requiring IMU fixation, but further research is needed to enhance generalizability and explore real-world deployment. [ABSTRACT FROM AUTHOR]

ABSTRACT Background Methods Results Conclusion There is little research done on ground reaction forces (GRF) in terms of 3D impulses after total hip replacement (THR). This study aimed to investigate the GRFs and 3D impulses in four sub‐phases of stance during gait in the patients undergoing THR.A total of 10 pain‐free THR patients and 10 healthy people were recruited. This is an observational and retrospective study. The gait data was collected between 2008 and 2014 and analyzed between 2020 and 2024. All the participants were included in the three‐dimensional gait analysis. Gait parameters, phase durations, GRFs and impulses' key values during gait were calculated in four sub‐phases of stance. Statistical comparisons were performed with generalized linear models including age, gender, body mass index and walking speed as interactive factors.It is found that (1) cadence, walking speed, stride length and step width in THR group were significantly decreased in compared with control group; (2) the THR decreased loading response duration in operative side and pre‐swing duration in non‐operative side compared with the control group, but the THR's two sides have similar duration proportions in sub‐stance phases; (3) the THR group had lower GRFs than the control group in vertical direction but higher in the medial–lateral direction; (4) in operative side, the THR's impulses in loading response phase were lower than the control group in anterior–posterior direction, and (5) in non‐operative side, the THR's impulse in pre‐swing phase in anterior–posterior direction was higher than the control side.The THR group showed slower walking speeds than the control group. The reasons could be from the decreased impulse in loading response phase, the decreased 2nd peak of GRF and the decreased pre‐swing impulse in vertical direction in operative side. Clinicians are suggested to consider the information provided when designing relevant rehabilitation exercises on the related muscles and functions. [ABSTRACT FROM AUTHOR]

Kinematic analysis is a central component of movement biomechanics, describing the relative motion of joint segments during different activities, in different subject cohorts, and at different timepoints. Establishing whether two sets of kinematic signals represent fundamentally similar or different underlying motion patterns is especially challenging, given 1) the lack of consensus around reference frame and joint axis definition, and 2) the substantial effect that minimal variations in frame position and orientation are known to have on signal magnitude and characteristics. As such, enormous variability in the reporting of tibiofemoral kinematics has resulted in joint movement patterns that remain controversially discussed. Previously, we demonstrated the ability of the REference FRame Alignment MEthod (REFRAME) to reorientate and reposition differently aligned local segment frames to achieve convergence in signals representing the same underlying motion, thereby offering a novel approach to consistently report joint motion. In this study, for the first time, we apply REFRAME to assess the rotational and translational in vivo tibiofemoral motion of ten healthy subjects during stair descent based on kinematic signals collected using a moving videofluoroscope. Kinematics were analysed before and after different REFRAME implementations, revealing generally neutral ab/adduction behaviour, accompanied by varying degrees of a sinusoidal int/external tibial rotation pattern over the activity cycle. Our data demonstrate that different selected implementations of REFRAME are able to highlight different characteristics of the motion patterns: Minimisation of the translational root-mean-square revealed proximodistal translation patterns with overall neutral progression, while anteroposterior translation showed seemingly different levels of correlation with flexion/extension in different subjects. On the other hand, REFRAME minimisation of translational variances exposed differences in the relative mean displacement between the femoral and tibial origins between subjects, highlighting differences in mean centre of rotation positions. This early application of REFRAME for providing an understanding of tibiofemoral kinematics demonstrates the potential of this novel approach to bring clarity to an otherwise complex representation of highly variable time-series signals, while highlighting the philosophical challenges of clinically interpretating kinematic signals in the first place. [ABSTRACT FROM AUTHOR]

Introduction: With little to no regulation of the supplement markets and a paucity of quality information regarding clinical utility of individual marketed supplements, it is difficult for veterinarians to provide any evidence-based recommendations to owners. The current study aimed to provide clinically useful comparative efficacy data on certain marketed supplements. Methods: Using a prospective, block-randomized, double-blinded, placebo-controlled design, one hundred and one pet dogs with clinical hip OA-associated pain with one side worse than the other (index limb) were randomly assigned to one of four treatment groups: Green lipped Mussel plus Krill oil extracts (Antinol® Rapid, EAB-277); Biota orientalis extracts (4CYTE™ Epiitalis® Forte); an NSAID (meloxicam); or placebo (sunflower oil). Peak vertical force (PVF, expressed as a percentage of bodyweight) of the index limb, orthopedic assessment score (OAS) and hematology and blood chemistry values were evaluated before treatment (week 0), at 2, 4 and 6 weeks during treatment. Results: At 6 weeks, the changes from baseline in PVF of the index limb in the EAB-277 and meloxicam groups were significantly greater than the change in the placebo and 4CYTE™ groups, and the placebo and 4CYTE groups were not different from each other. At 6 weeks, there were significant differences between the groups for overall OAS scores with the lowest scores (least impairment) in the EAB-277 and meloxicam groups, followed by the 4CYTE group and then the placebo group. Discussion: Results of this study indicate that meloxicam and EAB-277 have significant objectively measured benefits in managing OA-related pain in dogs compared to placebo, but 4CYTE does not differ from placebo. [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]

Background: Gait disorder is a prominent motor symptom in Parkinson's disease (PD), objective and quantitative assessment of gait is essential for diagnosing and treating PD, particularly in its early stage. Methods: This study utilized a non-contact gait assessment system to investigate gait characteristics between individuals with PD and healthy controls, with a focus on early-stage PD. Additionally, we trained two machine learning models to differentiate early-stage PD patients from controls and to predict MDS-UPDRS III score. Results: Early-stage PD patients demonstrated reduced stride length, decreased gait speed, slower stride and swing speeds, extended turning time, and reduced cadence compared to controls. Our model, after an integrated analysis of gait parameters, accurately identified early-stage PD patients. Moreover, the model indicated that gait parameters could predict the MDS-UPDRS III score using a machine learning regression approach. Conclusion: The non-contact gait assessment system facilitates the objective and quantitative evaluation of gait disorder in PD patients, effectively distinguishing those in the early stage from healthy individuals. The system holds significant potential for the early detection of PD. It also harnesses gait parameters for a reasoned prediction of the MDS-UPDRS III score, thereby quantifying disease severity. Overall, gait assessment is a valuable method for the early identification and ongoing monitoring of PD. [ABSTRACT FROM AUTHOR]

Slipped Capital Femoral Epiphysis (SCFE) is femoral head slippage off the femoral neck through the physis occurring in children aged 8–16 years. Surgical intervention is required in all paediatric cases and there is no universal agreement on choice of surgical procedure. What are the two-year 3D gait outcomes in children with SCFE who have undergone in-situ pinning (PIN) or modified Dunn procedure (MDP) compared with normative reference values? 17 children with SCFE who had undergone PIN (n=7, slip severity mild to moderate) or MDP (n=10, slip severity moderate to severe) surgical procedures prospectively underwent a 3D gait analysis post-surgery (2∙0 ± 0∙5 years). Ten age-matched children were also recruited to provide normative reference values. The conventional gait model was modified to incorporate Hara hip equations and Lerner pelvic tracking methods. Gait Profile Scores, Gait Variable Scores, kinematics, kinetics and spatiotemporal data were calculated for each group. Overall gait pattern, determined by the Gait Profile Score, indicated that both SCFE groups differed from the normative reference group (PIN 6∙6 ± 2∙5⁰, MDP 6∙2 ± 2∙0⁰ vs. 4∙0 ± 1∙3⁰ norm, p<0∙05). Normalised walking speed was reduced in the MDP group (0∙40 ± 0∙04) compared to the normative reference group (0∙46 ± 0∙06; p=0∙032). Gait patterns of children with SCFE treated with PIN was more markedly altered than that of children with SCFE treated with MDP, despite having lower SCFE severity. Increased external hip rotation observed in the PIN group may be a pre-cursor for osteoarthritis in adulthood. Therefore the use of the corrective MDP which normalises hip rotation may be beneficial for reducing functional impairments. • SCFE in children requires surgical intervention, with no agreement on procedure. • In-situ pinning gait deviations persist as the procedure does not correct slippage. • Modified Dunn procedure results in correction of transverse plane gait deviations. [ABSTRACT FROM AUTHOR]

To investigate whether a smartphone-based gait analysis tool can reliably output gait quality parameters that can be cross-analyzed to establish individual & disease-based changes in gait quality patterns. A cross-sectional study made up of a 48-patients undergoing disability certification at the "Dr. José Castro Villagrana" or the "Dr. David Fragoso Lizalde" Health Centers in Mexico City, Mexico. Their sensorimotor performance was evaluated through an in-house smartphone/IMU based digital tool. Gait was analyzed by means of frequency analysis of the acceleration of the body mass measured at the sternum. A composite gait quality score was determined through principal component analysis based primarily on the explainability and uniformity of gait. Quality independence against demographic variables (age & weight) was tested through ANCOVA. The association between gait quality and gait parameters was analyzed by using multiple linear regression. A multiple regression model developed with a limited set of gait quality parameters successfully predicted gait smoothness with a 97.05 % accuracy with a mean square error of 0.085 between predicted and actual quality scores. The model demonstrates different predictive capacities across disease groups, with Osteoarthrosis + Osteoporosis having the highest R2 at 0.98 (p < 0.001) and Coxarthrosis having the lowest explained R2 at 0.79 (p < 0.001). The assessment of gait quality, in family medicine, with low-cost digital tools is an area of opportunity yet to be explored. This tool can potentially disrupt the current disability workflow between primary and specialty care to have an objective method of assessing gait within a clinical consult. Individual patient-level benchmarking can give us insights into the patient's disease status, develop practical intervention strategies, and control the cost and quality of medical care by predicting an individualized course of disability or rehabilitation. Further studies are needed to validate digital gait assessments as clinical decision support tools for day-to-day clinical operations. Gait Analysis, Smartphone, Primary Health Care, Osteoarthrosis • Gait is a vital biomarker for patient monitoring and diagnosis. • Abnormal gait patterns signify disease progression and rehabilitation needs. • Step length and speed change contribute to mobility impairments in osteoarthrosis. • Disease-based gait patterns can be distinguished through gait quality assessment. • Gait assessment can enable more accurate diagnosis and management in primary care. [ABSTRACT FROM AUTHOR]

The one of the most commonly used reference system for clinical gait analysis is an optical motion capture system (OMC) using a multi-segment foot model. A time- and cost-efficient alternative could be an inertial measurement unit (IMU)-based systems. However, these are limited to a single segment approach for the foot and ankle. Therefore, the current setup was modified to be based on a 2-segment foot model, allowing for a separate analysis of the hind- and midfoot. The study aimed to evaluate the reliability (inter-rater, intra-rater, and test-retest reliability) of an IMU-based 2-segment foot model. Twelve healthy subjects were recruited to test the inter-rater, intra-rater, and test-retest reliability of the new IMU based 2-segment foot model. Gait analysis was performed on a treadmill at a constant speed of 4 km/h. Kinematic data of the tibia/hindfoot, tibia/forefoot and hindfoot/forefoot over 100 % gait cycle were analyzed. The reliability was tested by using statistical parametric mapping (SPM) and the intraclass correlation coefficient (ICC). The SPM showed no significant difference for inter-, intra-rater, and test-retest reliability, but for a small segment of tibia/forefoot dorsiflexion test-retest reliability (2.1° difference). The single standard deviation measurement error for the sagittal and transverse plane was <5° and worse for the frontal plane. The new 2-segment foot model revealed a high inter-rater, intra-rater, and test-retest reliability. It is suitable for use in adult clinical practice. Still, comparative data to the OMC system using a multi-segment foot model are missing. • Assessing the reliability of an IMU-based 2-segment foot model as an extension of the traditionally used 1-segment models. • Resulting kinematic curves for the foot and ankle were tested for differences using statistical parametric mapping. • The 2-segment foot model showed good inter-, intra- and test-retest reliability with no clinical relevant differences. • Gait analysis with IMUs provide a cost and time effective alternative to optical motion capture. [ABSTRACT FROM AUTHOR]

Patients with symptomatic lumbar spinal stenosis (sLSS) are often limited in their walking range because of worsening symptoms, which is thought to induce changes in the gait pattern. The aim of this study was to determine whether changes in gait pattern and muscle activity in these patients are elicited by a walking stress and differ from asymptomatic controls. Twenty patients with sLSS and 19 asymptomatic controls performed a 30-minute walking stress. Gait was assessed using seven inertial sensors and sagittal joint range of motion (ROM) was calculated during different phases of gait. Muscle activation of the gluteus medius, erector spinae and multifidus muscles was measured by surface electromyography (EMG) and integrated EMGs (normalized to the maximum during gait) were calculated. Differences between groups and time points (beginning and end) were assessed using mixed factorial analysis of variance. Patients had less knee extension ROM in terminal stance, less knee flexion ROM in swing and less overall hip flexion/extension ROM than controls (p ≤ 0.03). There were no functionally relevant changes in these parameters during the walking stress. The integrated EMG was greater in all muscles in patients than in controls and increased in both groups during the walking stress in the paraspinal but not in the gluteus medius muscle. There was no interaction between group and time for any of the parameters. Differences in gait pattern and muscle activity between patients with sLSS and controls are generally present, but are not amplified by a walking stress. • Patients with lumbar spinal stenosis had less knee and hip range of motion. • Gluteus medius and paraspinal muscle activity was greater in patients. • Muscle activity increased in patients and controls during the walking stress. • Differences in gait pattern were not amplified by a walking stress. • In symptomatic spinal stenosis, a prolonged walking stress may not be necessary. [ABSTRACT FROM AUTHOR]

Peripheral neuropathy is a common complication of diabetes and increases the risk of falls, possibly through gait (quality) impairments in daily life. Characteristics of gait quality have been associated with peripheral neuropathy in a laboratory setting, but little is known about the more relevant association with gait quality in daily life. What is the association between peripheral neuropathy and gait quality characteristics in daily life in people with diabetes? Data from two cross-sectional studies were combined in an exploratory analysis, including a total of 98 participants with diabetes (mean age: 68 (SD 7) years, 32 females), of which 68 with peripheral neuropathy. Participants wore a tri-axial accelerometer for seven consecutive days. Walking episodes ≥5 seconds were identified and analysed to determine various gait quality characteristics. Associations were assessed using linear regression analyses, adjusted for walking speed and other potential confounders. Peripheral neuropathy was significantly associated with a lower walking speed (people with neuropathy: 0.81 vs without neuropathy: 0.88 m/s; β (95 % confidence interval (CI)): −0.114 (−0.202 to −0.026)), a lower stride frequency (0.81 vs 0.85 strides/s; β (95 % CI): −0.030 (−0.057 to −0.003)), lower gait intensity (i.e. lower root mean square) in vertical direction (1.38 vs 1.63 m/s2; β (95 % CI): −0.074 (−0.143 to −0.006)), and less gait symmetry (i.e. lower harmonic ratio) in vertical direction (1.82 vs 2.27; β (95 % CI): −0.322 (−0.474 to −0.170)). People with peripheral neuropathy had non-significantly poorer gait quality for most of the other 21 gait quality characteristics. Peripheral neuropathy seems to negatively affect several gait quality characteristics measured in daily life. These results need to be replicated in future studies and may help to develop targeted gait training to improve gait quality and potentially reduce fall risk in people with diabetes and peripheral neuropathy. • Sensor based daily-life gait quality was assessed in people with diabetes. • Peripheral neuropathy from diabetes reduces walking speed and stride frequency. • Peripheral neuropathy is associated with lower vertical gait intensity and symmetry. • Peripheral neuropathy negatively affects gait quality in people with diabetes. [ABSTRACT FROM AUTHOR]

Gait analysis is essential for evaluating locomotor function and fall risk, particularly in the elderly and in various musculoskeletal disorders. Traditional gait analysis systems face challenges such as technical difficulties, high cost, and complexity of use. Therefore, there is a need for a more accessible and cost-effective system with a wider clinical applicability. This study aimed to validate the newly developed IB-gait® system (InBody, Republic of Korea), a camera-based gait analysis tool, by comparing it against the VICON system. A total of 28 community-dwelling adults without gait abnormalities (mean age 24.9 years) were enrolled in this study. The participants underwent gait analysis at their self-selected speed using VICON and IB-gait® simultaneously. Nine spatiotemporal gait parameters, including stride length (m), step length (m), stride duration (s), double-limb duration (s), stance phase (s), swing phase (s), cadence (velocity × 120/stride length), and gait velocity (m/s) were measured. The agreement between the two systems was tested using Bland-Altman plots and intraclass correlation coefficients (ICC). The IB-gait® showed a high degree of agreement with the VICON system in most gait parameters. The ICC showed excellent reliability for stride length (0.97), step length (0.92), gait velocity (0.97), cadence (0.97), and stride duration (0.79). However, it showed lower reliability in time-based parameters, including double-limb duration (0.12), stance phase (0.54), swing phase (0.241), and stance/swing phase ratio (0.11). The IB-gait® system appears to be a feasible and cost-effective alternative to VICON system for gait analysis, particularly showing a high level of agreement in the distance-based parameters. Its practicality in clinical settings makes it a valuable tool for widespread use in gait analysis. However, further refinement of time-based parameter measurements and validation in diverse patient populations are needed to enhance its applicability. • IB-gait® showed high agreement with the VICON system in most spatiotemporal parameters. • Reliability was excellent for distance-related parameters. • IB-gait® is an accessible, accurate and useful gait analysis system. [ABSTRACT FROM AUTHOR]

Lower limb exoskeletons represent a relevant tool for rehabilitating gait in patients with lower limb movement disorders. Partial assistance exoskeletons adaptively provide the joint torque needed, on top of that produced by the patient, for a correct and stable gait, helping the patient to recover an autonomous gait. Thus, the device needs to identify the different phases of the gait cycle to produce precisely timed commands that drive its joint motors appropriately. In this study, EMG signals have been used for gait phase detection considering that EMG activations lead limb kinematics by at least 120 ms. We propose a deep learning model based on bidirectional LSTM to identify stance and swing gait phases from EMG data. We built a dataset of EMG signals recorded at 1500 Hz from four muscles from the dominant leg in a population of 26 healthy subjects walking overground (WO) and walking on a treadmill (WT) using a lower limb exoskeleton. The data were labeled with the corresponding stance or swing gait phase based on limb kinematics provided by inertial motion sensors. The model was studied in three different scenarios, and we explored its generalization abilities and evaluated its applicability to the online processing of EMG data. The training was always conducted on 500-sample sequences from WO recordings of 23 subjects. Testing always involved WO and WT sequences from the remaining three subjects. First, the model was trained and tested on 500 Hz EMG data, obtaining an overall accuracy on the WO and WT test datasets of 92.43% and 91.16%, respectively. The simulation of online operation required 127 ms to preprocess and classify one sequence. Second, the trained model was evaluated against a test set built on 1500 Hz EMG data. The accuracies were lower, yet the processing times were 11 ms faster. Third, we partially retrained the model on a subset of the 1500 Hz training dataset, achieving 87.17% and 89.64% accuracy on the 1500 Hz WO and WT test sets, respectively. Overall, the proposed deep learning model appears to be a valuable candidate for entering the control pipeline of a lower limb rehabilitation exoskeleton in terms of both the achieved accuracy and processing times. [ABSTRACT FROM AUTHOR]

Digital gait monitoring is increasingly used to assess locomotion and fall risk. The aim of this work is to analyze the changes in the foot–floor contact sequences of Parkinson's Disease (PD) patients in the year following the implantation of Deep Brain Stimulation (DBS). During their best-ON condition, 30 PD patients underwent gait analysis at baseline ( T 0 ), at 3 months after subthalamic nucleus DBS neurosurgery ( T 1 ), and at 12 months ( T 2 ) after subthalamic nucleus DBS neurosurgery. Thirty age-matched controls underwent gait analysis once. Each subject was equipped with bilateral foot-switches and a 5 min walk was recorded, including both straight-line and turnings. The walking speed, turning time, stride time variability, percentage of atypical gait cycles, stance, swing, and double support duration were estimated. Overall, the gait performance of PD patients improved after DBS, as also confirmed by the decrease in their UPDRS-III scores from 19.4 ± 1.8 to 10.2 ± 1.0 ( T 0 vs. T 2 ) (p < 0.001). In straight-line walking, the percentages of atypical cycles of PD on the more affected side were 11.1 ± 1.5% (at T 0 ), 3.1 ± 1.5% (at T 1 ), and 5.1 ± 2.4% (at T 2 ), while in controls it was 3.1 ± 1.3% (p < 0.0005). In turnings, this percentage was 13.7 ± 1.1% (at T 0 ), 7.8 ± 1.1% (at T 1 ), and 10.9 ± 1.8% (at T 2 ), while in controls it was 8.1 ± 1.0% (p < 0.001). Therefore, in straight-line walking, the atypical cycles decreased by 72% at T 1 , and by 54% at T 2 (with respect to baseline), while, in turnings, atypical cycles decreased by 43% at T 1 , and by 20% at T 2 . The percentage of atypical gait cycles proved an informative digital biomarker for quantifying PD gait changes after DBS, both in straight-line paths and turnings. [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]

Background: Hip biomechanics are crucial in understanding movement disorders and joint pathologies. Pelvic tilt and femoral torsion are key factors influencing hip function and stability. This review aims to elucidate their effects on acetabular orientation, hip range of motion (ROM), and associated compensatory mechanisms. Methods: A comprehensive search of databases, including PubMed, Scopus, and Pedro, was conducted. Studies were selected based on Population, Concept, and Context (PCC) criteria, focusing on those examining the relationship between pelvic tilt, femoral torsion, and hip biomechanics. Eight studies were included, utilizing methodologies such as CT imaging, musculoskeletal modeling, and gait analysis, covering populations ranging from asymptomatic adults to elderly women with pelvic retroversion. Results: The review identified significant effects of pelvic retroversion on acetabular anteversion and hip extension. Some studies found no correlation between pelvic index (PI) and acetabular orientation, while others reported a linear increase in acetabular anteversion with pelvic retroversion. Subjects with pelvic retroversion showed greater hip extension. Additionally, femoral anteversion was linked to increased internal rotation and altered hip joint contact forces during gait, with changes in hip ROM and force distribution. No relationship was found between femoral and acetabular anteversion in patients with hip osteoarthritis. Conclusions: Pelvic tilt and femoral torsion significantly affect hip biomechanics, influencing acetabular orientation, ROM, and compensatory mechanisms. Future studies should include symptomatic populations to explore these relationships further. These findings emphasize the critical need for individualized clinical assessments and further research on symptomatic populations to enhance our understanding of pelvic tilt and femoral torsion's impact on hip biomechanics. [ABSTRACT FROM AUTHOR]

The development of micro-robots based on bionic motion has garnered increasing attention with the advancement of bionic technology. These micro-robots can be employed in various tasks, such as military applications, disaster search and rescue, in vivo drug delivery, minimally invasive surgery, and tumor treatment. Robot joint motion is commonly achieved through actuators, which encompass motor, hydraulic, or pneumatic components that often carry excessive weight. To achieve the goal of miniaturizing robotic mechanisms, innovative actuators need to be developed. This study focuses on designing a four-limbed micro-robot that utilizes piezoelectric actuators. Automatic Dynamic Analysis of the Mechanical System is employed to investigate the kinematic aspects of the micro-robot’s motion, and finite element analysis is also used to obtain the resonant characteristics of the limbs actuated by piezoelectric bimorphs. The results indicate that the gait pattern of a piezoelectric robot changes according to the walking strategy and the robot dimension. The forward travel speed varies depending on the gait pattern, and adjustments in gait design can reduce the up/down oscillation and right/left offset. The robot’s travel speed increases with both trunk and limb length, although longer thigh and leg lengths might lead to greater offset and vertical oscillation. The resonant frequency and mode shapes change with the limb structure and affect the limb motion style. By adjusting the driving frequency of the bimorph actuators, the gait pattern can be manipulated. The information presented in this study contributes to a deeper understanding of micro-robot design. [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]

Introduction: Proprioceptive neuromuscular stimulating insoles (PNIs) enhance somatosensory information from the plantar region, thus modifying standing posture, balance, and ambulatory function. The present study investigated the short-term effects of customized PNIs on lower-limb kinematics during human locomotion. Materials and Methods: Fifteen able-bodied volunteers were recruited and first examined with clinical evaluation of postural and feet behavior. Subjects performed 3-dimensional gait analysis (GA) while walking at self-selected speed in three different conditions: baseline, subjects barefoot; placebo, subjects wearing neutral insoles; and proprioceptive, subjects wearing PNIs. Spatiotemporal and kinematics data of the main lower-limb joints were acquired through a system of six photogrammetric infrared cameras acquiring at a sampling frequency of 100 Hz. Then, acquired parameters were compared in the three different conditions. Results: We found a significant difference in the percentage of double-support phase (P = 0.022) and in ankle plantarflexion values during the toe-off phase of gait cycle (P = 0.022) between the three conditions. Post hoc analysis revealed that subjects wearing PNIs presented a significant reduction in percentage of double-support phase (P = 0.009) and reduced values of ankle plantarflexion during the toe-off phase of gait cycle (P = 0.02), compared with subjects in placebo condition. Conclusions: Results suggest that proprioceptive insoles may induce modifications of gait biomechanics in able-bodied subjects, thus modulating movement strategies during human locomotion. Clinical Relevance: These findings provide a basis for future investigation of the efficacy of these foot devices in a long-term period in able-bodied individuals and potentially in subjects with neurological impairment. [ABSTRACT FROM AUTHOR]

The use of inertial measurement units (IMUs) as an alternative to optical marker-based systems has the potential to make gait analysis part of the clinical standard of care. Previously, an IMU-based system leveraging Rauch–Tung–Striebel smoothing to estimate knee angles was assessed using a six-degrees-of-freedom joint simulator. In a clinical setting, however, accurately measuring abduction/adduction and external/internal rotation of the knee joint is particularly challenging, especially in the presence of soft tissue artefacts. In this study, the in vivo IMU-based joint angles of 40 asymptomatic knees were assessed during level walking, under two distinct sensor placement configurations: (1) IMUs fixed to a rigid harness, and (2) IMUs mounted on the skin using elastic hook-and-loop bands (from here on referred to as "skin-mounted IMUs"). Estimates were compared against values obtained from a harness-mounted optical marker-based system. The comparison of these three sets of kinematic signals (IMUs on harness, IMUs on skin, and optical markers on harness) was performed before and after implementation of a REference FRame Alignment MEthod (REFRAME) to account for the effects of differences in coordinate system orientations. Prior to the implementation of REFRAME, in comparison to optical estimates, skin-mounted IMU-based angles displayed mean root-mean-square errors (RMSEs) up to 6.5°, while mean RMSEs for angles based on harness-mounted IMUs peaked at 5.1°. After REFRAME implementation, peak mean RMSEs were reduced to 4.1°, and 1.5°, respectively. The negligible differences between harness-mounted IMUs and the optical system after REFRAME revealed that the IMU-based system was capable of capturing the same underlying motion pattern as the optical reference. In contrast, obvious differences between the skin-mounted IMUs and the optical reference indicated that the use of a harness led to fundamentally different joint motion being measured, even after accounting for reference frame misalignments. Fluctuations in the kinematic signals associated with harness use suggested the rigid device oscillated upon heel strike, likely due to inertial effects from its additional mass. Our study proposes that optical systems can be successfully replaced by more cost-effective IMUs with similar accuracy, but further investigation (especially in vivo and upon heel strike) against moving videofluoroscopy is recommended. [ABSTRACT FROM AUTHOR]

Children with hemiplegic cerebral palsy (hemi-CP) frequently experience deficits in dynamic balance, a crucial factor influencing gait function. This imbalance can manifest as temporal–spatial gait asymmetry, where movement patterns differ between the affected and less affected sides. This study investigated how temporal–spatial gait asymmetries and dynamic balance are associated in children with hemi-CP. Eighty-five children with hemi-CP (age: 13.27 ± 1.72 years) were included. The temporal (AITemporal) and spatial (AISpatial) gait asymmetry indices were, respectively, computed with reference to the swing time and step length of affected and less affected sides, which were collected through a 3D gait analysis. Measures of dynamic balance included the directional dynamic limit-of-stability (D-LOSdirectional) assessed across multiple directions (forward, rearward, affected, and less affected) and the overall dynamic limit-of-stability (D-LOSoverall) during static stance, in addition to the heel-to-heel base of support (BOSH-to-H) during walking, the dynamic gait index (DynGI), and the Timed Up and Down Stair (TUDS) test.The D-LOSoverall correlated negatively with the temporal (r = −0.437, p < 0.001) and spatial (r = −0.279, p = 0.009) asymmetries. The D-LOSdirectional (forward, rearward, affected, and less affected) correlated negatively with temporal asymmetry (r ranged from −0.219 to −0.411, all p < 0.05), but only the D-LOSdirectional rearward (r = −0.325, p = 0.002) and less affected (r = −0.216, p = 0.046) correlated with spatial asymmetry. The BOSH-to-H correlated positively with both temporal (r = 0.694, p < 0.001) and spatial (r = 0.503, p < 0.001) asymmetries. The variation in D-LOSoverall and BOSH-to-H accounted for 19.1% and 48.2%, respectively, of the variations in the temporal asymmetry and 7.8% and 25.3% of the variations in the spatial asymmetry. The findings of this study suggest that dynamic balance control is related to the magnitude of temporal–spatial gait asymmetries in children with hemi-CP. This evidence lays the groundwork for further research into the mechanism linking gait asymmetry and dynamic balance, potentially leading to a deeper understanding of these impairments, while also highlighting the need for longitudinal studies with the inclusion of a broader population to enhance the generalizability of the findings. [ABSTRACT FROM AUTHOR]

Given the high morbidity related to the progression of gait deficits in spinocerebellar ataxias (SCA), there is a growing interest in identifying biomarkers that can guide early diagnosis and rehabilitation. Spatiotemporal parameter (STP) gait analysis using inertial measurement units (IMUs) has been increasingly studied in this context. This study evaluated STP profiles in SCA types 3 and 10, compared them to controls, and correlated them with clinical scales. IMU portable sensors were used to measure STPs under four gait conditions: self-selected pace (SSP), fast pace (FP), fast pace checking-boxes (FPCB), and fast pace with serial seven subtractions (FPS7). Compared to healthy subjects, both SCA groups had higher values for step time, variability, and swing time, with lower values for gait speed, cadence, and step length. We also found a reduction in speed gain capacity in both SCA groups compared to controls and an increase in speed dual-task cost in the SCA10 group. However, there were no significant differences between the SCA groups. Swing time, mean speed, and step length were correlated with disease severity, risk of falling and functionality in both clinical groups. In the SCA3 group, fear of falling was correlated with cadence. In the SCA10 group, results of the Montreal cognitive assessment test were correlated with step time, mean speed, and step length. These results show that individuals with SCA3 and SCA10 present a highly variable, short-stepped, slow gait pattern compared to healthy subjects, and their gait quality worsened with a fast pace and dual-task involvement. [ABSTRACT FROM AUTHOR]

Mobile health technologies enable continuous, quantitative assessment of mobility and gait in real-world environments, facilitating early diagnoses of gait disorders, disease progression monitoring, and prediction of adverse events like falls. Traditionally, mobile gait assessment predominantly relied on body-fixed sensors positioned at the feet or lower trunk. Here, we investigate the potential of an algorithm utilizing an ear-worn motion sensor for spatiotemporal segmentation of gait patterns. We collected 3D acceleration profiles from the ear-worn sensor during varied walking speeds in 53 healthy adults. Temporal convolutional networks were trained to detect stepping sequences and predict spatial relations between steps. The resulting algorithm, mEar, accurately detects initial and final ground contacts (F1 score of 99% and 91%, respectively). It enables the determination of temporal and spatial gait cycle characteristics (among others, stride time and stride length) with good to excellent validity at a precision sufficient to monitor clinically relevant changes in walking speed, stride-to-stride variability, and side asymmetry. This study highlights the ear as a viable site for monitoring gait and proposes its potential integration with in-ear vital-sign monitoring. Such integration offers a practical approach to comprehensive health monitoring and telemedical applications, by integrating multiple sensors in a single anatomical location. [ABSTRACT FROM AUTHOR]

Osteoarthritis (OA) is a global problem. There are few reports in the literature regarding the temporal and spatial parameters of gait in people with OA. The aim of this study was to determine spatiotemporal parameters for the pelvis and lower limbs during walking in women with OA and to compare these parameters with healthy people. For this purpose, a 6 min walking test (6MWT) was carried out. OA subjects had worse outcomes compared to the control group (p < 0.05). Data were collected using IMU sensors integrated into the MoKA system and mounted on indicator points on the body. Limited mobility of the pelvis in the frontal plane was observed in the study group, which influenced walking strategy. For the comparison with the control group at each minute, p < 0.05. IMU sensors attached to the body and integrated in one application provide extensive research and diagnostic capabilities. [ABSTRACT FROM AUTHOR]

Existing studies on gait phase estimation generally involve walking experiments using inertial measurement units under limited walking conditions (WCs). In this study, a gait phase estimation algorithm is proposed that uses data from force sensing resistors (FSRs) and a Bi-LSTM model. The proposed algorithm estimates gait phases in real time under various WCs, e.g., walking on paved/unpaved roads, ascending and descending stairs, and ascending or descending on ramps. The performance of the proposed algorithm is evaluated by performing walking experiments on ten healthy adult participants. An average gait estimation accuracy exceeding 90% is observed with a small error (root mean square error = 0.794, R2 score = 0.906) across various WCs. These results demonstrate the wide applicability of the proposed gait phase estimation algorithm using various insole devices, e.g., in walking aid control, gait disturbance diagnosis in daily life, and motor ability analysis. [ABSTRACT FROM AUTHOR]