Gait Analysis Research Articles

Uncertainty-aware ensemble model for stride length estimation in gait analysis

Deep neural network (DNN) models have become highly effective tools for function estimation in regression tasks, with applications in various domains, including human gait stride length estimation. Several studies have developed DNN models that use gait cycle data from wearable devices equipped with inertial measurement units to accurately predict stride lengths within a cycle. However, many of these deep learning approaches do not quantify predictive uncertainty and fail to consider individual gait characteristics. To address these limitations, we introduced an ensemble model based on a heteroscedastic neural network that quantifies the uncertainty in stride length predictions. Additionally, we proposed a novel stride training strategy that uses the average stride instead of individual strides to optimize the training process and improve model efficiency. Our extensive performance evaluations demonstrate the robustness and adaptability of our model, accurately predicting both the uncertainty of individual stride lengths and the specific stride lengths for each gait cycle. Our study represents a significant advancement in stride length estimation, addressing the challenges of uncertainty quantification and capturing the unique aspects of human gait. The proposed model has considerable potential for practical applications in gait analysis and related fields.

Associations amongst dynamic knee stiffness during gait, quadriceps stiffness, and the incidence of knee osteoarthritis over 24 months: a cohort study with a mediation analysis

BackgroundDecreased strength and increased stiffness of the quadriceps have been associated with a higher risk of developing knee osteoarthritis (OA) in elders. Dynamic joint stiffness (DJS) represents collective resistance from active and passive knee structures for dynamic knee motions. Elevated sagittal knee DJS has been associated with worsening of cartilage loss in knee OA patients. Altered quadriceps properties may affect DJS, which could be a mediator for associations between quadriceps properties and knee OA. Hence, this study aimed to examine whether DJS and quadriceps properties would be associated with the development of clinical knee OA over 24 months, and to explore the mediation role of DJS in associations between quadriceps properties and knee OA.MethodsThis was a prospective cohort study with 162 healthy community-dwelling elders. Gait analysis was conducted to compute DJS during the loading response phase. Quadriceps strength and stiffness were evaluated using a Cybex dynamometer and shear-wave ultrasound elastography, respectively. Knee OA was defined based on clinical criteria 24 months later. Logistic regression with generalized estimating equations was used to examine the association between quadriceps properties and DJS and incident knee OA. Mediation analysis was performed to explore the mediation role of DJS in associations between quadriceps properties and the incidence of knee OA.ResultsA total of 125 participants (65.6 ± 4.0 years, 58.4% females) completed the 24-month follow-up, with 36 out of 250 knees identified as clinical knee OA. Higher DJS (OR = 1.86, 95%CI: 1.33–2.62), lower quadriceps strength (1.85, 1.05–3.23), and greater quadriceps stiffness (1.56, 1.10–2.21) were significantly associated with a higher risk of clinical knee OA. Mediation analysis showed that the DJS was not a significant mediator for the associations between quadriceps properties and knee OA.ConclusionsHigher sagittal knee dynamic joint stiffness, lower quadriceps strength, and greater quadriceps stiffness are potential risk factors for developing clinical knee OA in asymptomatic elders. Associations between quadriceps properties and knee OA may not be mediated by dynamic joint stiffness. Interventions for reducing increased passive properties of the quadriceps and knee joint stiffness may be beneficial for maintaining healthy knees in the aging population.

Recent Innovations in Footwear and the Role of Smart Footwear in Healthcare-A Survey.

Smart shoes have ushered in a new era of personalised health monitoring and assistive technologies. Smart shoes leverage technologies such as Bluetooth for data collection and wireless transmission, and incorporate features such as GPS tracking, obstacle detection, and fitness tracking. As the 2010s unfolded, the smart shoe landscape diversified and advanced rapidly, driven by sensor technology enhancements and smartphones' ubiquity. Shoes have begun incorporating accelerometers, gyroscopes, and pressure sensors, significantly improving the accuracy of data collection and enabling functionalities such as gait analysis. The healthcare sector has recognised the potential of smart shoes, leading to innovations such as shoes designed to monitor diabetic foot ulcers, track rehabilitation progress, and detect falls among older people, thus expanding their application beyond fitness into medical monitoring. This article provides an overview of the current state of smart shoe technology, highlighting the integration of advanced sensors for health monitoring, energy harvesting, assistive features for the visually impaired, and deep learning for data analysis. This study discusses the potential of smart footwear in medical applications, particularly for patients with diabetes, and the ongoing research in this field. Current footwear challenges are also discussed, including complex construction, poor fit, comfort, and high cost.

GaitNet+ARL: A Deep Learning Algorithm for Interpretable Gait Analysis of Chronic Ankle Instability.

Chronic ankle instability (CAI) is a major public health concern and adversely affects people's mobility and quality of life. Traditional assessment methods are subjective and qualitative by means of clinician observation and patient self-reporting, which may lead to inaccurate assessment and reduce the effectiveness of treatment in clinical practice. Gait analysis becomes a commonly used approach for monitoring human motion behaviors, which can be applied to specific diagnosis and assessment of CAI. However, it is still challenging to recognize the pathological gait pattern for CAI subjects. In this paper, we propose an integrated deep learning framework to solve the CAI recognition problem using kinematic data. Specifically, inspired by the biomechanics of human body system, we create a simple graph neural network (GNN), termed GaitNet, that operates on a spatial domain and exploits interactions among 3-D joint coordinates. We also develop an attention reinforcement learning (ARL) model that determines attention weights of frames on a temporal domain, which is combined with GaitNet for prediction. The effectiveness of our method is validated on the kinematic NEU-CAI dataset which is collected in our institution using a stereophotogrammetric system. According to extensive experiments, we demonstrate that the selected key phases (i.e., sequences of frames with high attentions) significantly increase the predictability of the proposed biomechanics-based GNN model to differentiate between CAI cohort and control cohort. Moreover, we show a significant prediction accuracy improvement (20%-25%) by our approach compared to state-of-the-art machine learning and deep learning methods.

Gait analysis of patients undergoing knee endoprosthesis: functional differences between tibia and femur resections.

With the improvement in survival of patients undergoing knee reconstructive surgeries, the functional parameter became widely studied heading optimize and minimize motor sequelae. In patients undergoing knee endoprosthesis, proximal tibial or distal femoral resections affect the functioning of the knee extensor mechanism, with possible repercussions on gait. Seventeen patients were selected, divided into two groups, undergoing distal femoral or proximal tibial resection, and gait analysis examination was performed. Changes in gait velocity, cadence, step length, and alterations in the support and balance phase were observed. No major statistically significant differences were found in the kinetic and kinematic parameters between the operated groups. The study corroborates that although tibial resections have a higher theoretical risk of compromising the extensor mechanism, such data were not observed in the analyzed sample.

Electroacupuncture activates the peroxisome proliferators-activated receptor pathway to improve thephenotype of cerebral palsy.

This study explores the efficacy of electroacupuncture (EA) in treating cerebral palsy (CP) in Sprague-Dawley (SD) pups, specifically CP animal models, and its molecular mechanisms. Gait analysis and Y-maze were used to detect the improvement of motor ability and cognitive function of CP rats after EA treatment. Transcription sequencing was used to determine the key pathway for EA to improve the symptoms of CP. PPAR agonists were used to verify the causal relationship between the pathway and the improvement of CP phenotype. The motor ability and cognitive function of CP pups were improved after EA treatment. The results of transcriptome sequencing suggest that the improvement of CP phenotype may be caused by the activation of PPAR pathway. PPAR pathway is widely activated in the epithelium of CP pups treated with EA, which is verified by qPCR. Rosiglitazone (Ros), a PPAR agonist, can improve CP phenotype while activating PPAR pathway, which proves the causal relationship between PPAR pathway activation and CP phenotype improvement. Our study demonstrated behavioral improvements and enhanced cognitive functions in CP models after EA treatment by activating PPAR pathway, suggesting new perspectives for CP rehabilitation, and providing theoretical support for acupuncture treatment of CP.

Gait phase normalization resolves the problem of different phases being compared in gait cycle normalization

For time-continuous analysis of gait, the problem of variations in cycle durations is resolved by normalizing to the gait cycle, but results depend on the definition of the cycle start. Gait cycle normalization ignores variations in gait phase durations, which results in averaging and comparing data across different phases. We propose gait phase normalization as part of a comprehensive method for independently analyzing magnitude and timing differences. First, gait phases are identified and differences in absolute and/or relative timing of phase durations or any point of interest between conditions or groups are analyzed using standard statistics. Next, time-continuous gait data is normalized to gait phases, and statistical parametric mapping (SPM) is used to assess magnitude differences in gait data. This approach is demonstrated on data recorded from ten young healthy adults walking on a treadmill at five different speeds. Sagittal knee angle was normalized to gait cycle or gait phase using five different gait cycle start events. Walking at different speeds resulted in significant changes in gait phase durations, highlighting a problem ignored by gait cycle normalization. SPM results for knee angle normalized to gait cycle varied from normalization to gait phases. Gait phase normalized SPM results were robust to the definition of the cycle start, in contrast to gait cycle normalized data. The approach of analyzing phase durations and normalizing data to gait phases overcomes previous limitations and enables a comprehensive analysis of magnitude and timing differences in time-continuous gait data and could be readily adapted to other tasks.

Robotic Assisted TKA achieves adjusted mechanical alignment targets more consistently compared to manual TKA without improving outcomes.

Robotic total knee arthroplasty (rTKA), with its purported advantages of more accurate alignment, greater functional outcomes and patient satisfaction, is gaining popularity in patients undergoing TKA. The purpose of our study was to compare these parameters along with gait pattern and kneeling ability in a cohort of patients who underwent simultaneous TKA with manual instrumentation (mTKA) and rTKA in contralateral knees at a 1-year follow-up. This was a retrospective review of 135 consecutive patients who underwent simultaneous bilateral TKA using robotic assistance on one side and manual instrumentation on the contralateral side between January 2022 and June 2022. The target alignment in both cohorts was adjusted mechanical. Patients were followed up at 3, 6 and 12 months to assess and compare alignment, range of motion (ROM) and patient-reported outcome measures (PROM) data. Gait parameters and kneeling ability were assessed at 1-year follow-up. While adjusted mechanical alignment was achieved in all rTKA patients, we recorded five outliers (≥3° with relation to 180° HKA axis) in the mTKA cohort (three varus and two valgus). There were no significant differences between both cohorts with regards to ROM, PROM scores, gait analysis parameters and kneeling ability at 1-year follow-up. rTKA helps in achieving the adjusted mechanical alignment more consistently than mTKA. This, however, does not contribute to better functional outcomes and patient satisfaction at 1-year follow-up. Level III.

Trendelenburg gait after total hip arthroplasty due to reduced muscle contraction of the hip abductors and extensors

BackgroundDespite experiencing pain relief and improved activities of daily living after total hip arthroplasty (THA) for osteoarthritis of the hip, a Trendelenburg gait may be observed in some patients. The concentric and eccentric contraction patterns of hip muscles in a Trendelenburg gait are not well understood. MethodsThis study included 89 patients (28 males and 61 females, mean age 66.5 ± 8.4 years, mean postoperative period 1.3 ± 0.4 years) after unilateral THA without functional impairment on the contralateral side. Gait analysis utilized a three-dimensional motion capture system to assess pelvis and hip angles, hip moment, and hip power. A Trendelenburg gait was defined as positive when nonoperative pelvic descent occurred at 30 % of the gait cycle, equivalent to mid-stance. Patients were classified into Trendelenburg gait-positive and -negative groups for statistical analysis. Unpaired t-test and chi-square test were used to compare the two groups. Multiple regression analysis was conducted to identify factors associated with the presence of a Trendelenburg gait. ResultsA Trendelenburg gait was observed in 24 patients (27 %). Multiple regression analysis indicated that abduction (p < 0.01) and extension (p = 0.03) of hip joint power were significant determining of a Trendelenburg gait. Patients with a Trendelenburg gait exhibited reduced eccentric contraction of the hip abductor muscles and decreased concentric contraction of hip extensor muscles during early to mid-stance of their gait. ConclusionCentrifugal contraction of hip abductor muscles and diminished eccentric contractility of hip extensor muscles appear crucial for hip stabilization mechanisms during gait after THA.

Research on Monitoring Assistive Devices for Rehabilitation of Movement Disorders through Multi-Sensor Analysis Combined with Deep Learning.

This study aims to integrate a convolutional neural network (CNN) and the Random Forest Model into a rehabilitation assessment device to provide a comprehensive gait analysis in the evaluation of movement disorders to help physicians evaluate rehabilitation progress by distinguishing gait characteristics under different walking modes. Equipped with accelerometers and six-axis force sensors, the device monitors body symmetry and upper limb strength during rehabilitation. Data were collected from normal and abnormal walking groups. A knee joint limiter was applied to subjects to simulate different levels of movement disorders. Features were extracted from the collected data and analyzed using a CNN. The overall performance was scored with Random Forest Model weights. Significant differences in average acceleration values between the moderately abnormal (MA) and severely abnormal (SA) groups (without vehicle assistance) were observed (p < 0.05), whereas no significant differences were found between the MA with vehicle assistance (MA-V) and SA with vehicle assistance (SA-V) groups (p > 0.05). Force sensor data showed good concentration in the normal walking group and more scatter in the SA-V group. The CNN and Random Forest Model accurately recognized gait conditions, achieving average accuracies of 88.4% and 92.3%, respectively, proving that the method mentioned above provides more accurate gait evaluations for patients with movement disorders.

Long-Term Effect of Intra-Articular Adipose-Derived Stromal Vascular Fraction and Platelet-Rich Plasma in Dogs with Elbow Joint Disease-A Pilot Study.

(1) Background: The aim of the current pilot study was to describe the long-term effects of a single intra-articular injection of autologous stromal vascular fraction (SVF) with platelet-rich plasma (PRP) in dogs with confirmed elbow OA, using orthopedic lameness scoring and kinetic and kinematic gait analysis. For comparison of normal long-term variation of gait over time, a group of healthy control dogs (CDs) was also evaluated. (2) Methods: A prospective longitudinal clinical pilot study investigating 19 client-owned dogs with elbow OA (OADs) treated with SVF and PRP and eight CDs not receiving treatment. The OAD and CD groups were evaluated before and after 6 and at least 12 months following treatment with SVF and PRP (OAD group) and twice with a six-month interval (CD group), respectively, through orthopedic examinations, goniometry, and kinetic and kinematic analyses (seven variables). (3) Results: The OAD had an increase in fore-hind peak force symmetry ≥12 months after treatment (p < 0.05), but no other objective variables changed over time. Orthopedic consensus scores had improved at ≥six months follow-up evaluation (p < 0.05). None of the investigated gait variables had changed at ≥six months follow-up evaluation in the CD group. (4) Conclusions: The current study could not confirm a significant benefit from SVF and PRP treatment in OADs, but future studies should be conducted in order to fully evaluate the potential of the treatment. The improvement seen in fore-hindlimb symmetry may represent an improvement in gait or an incidental finding.

Skilled reaching test for shoulder function assessment in a rat model of rotator cuff tear: a pilot study

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

Neural network-based estimation of lower limb joint kinematics: A minimally intrusive approach for gait analysis

The establishment of a quantitative gait analysis system holds paramount importance, particularly in the context of functional rehabilitation of the lower limbs. Clinicians emphasize the imperative for sensors to be portable, compact, integrated, and non-intrusive, crucial characteristics in the rehabilitation field to facilitate their use and ensure optimal integration into care protocols. This study investigates an innovative approach aimed at reducing the reliance on body-fixed sensors by harnessing their data within a neural network, thus concentrating on the joint kinematics of the lower limbs. The primary objective is to estimate the flexion-extension angles of the hip, knee, and ankle during walking, utilizing data collected by two sensors positioned on the subject's legs. Initially, the neural network undergoes training with calculated data (leg tilt angles and angular velocities) sourced from the OpenSim database, followed by further refinement with experimental data obtained from a subject walking on a treadmill, wherein leg tilt angles and angular velocities are measured. The significance of this research is underscored by the demonstrated capability, through conducted tests, of the implemented networks to efficiently fuse data from a minimal set of sensors. Consequently, the proposed approach emerges as both practical and minimally intrusive, facilitating a robust evaluation of gait kinematic parameters.

Effects of overweight and obesity on lower limb walking characteristics from joint kinematics to muscle activations

BackgroundObesity is a crucial factor that increases the risk of initiating and advancing knee osteoarthritis. However, it remains unclear how obesity directly impacts the biomechanical experience of the lower limb joints, potentially triggering or exacerbating joint degeneration. This study investigated the interactive effects of BMI augmentation on lower limb kinematics, kinetics, and muscle activations during walking. MethodologyA group of 60 participants underwent a three-dimensional gait analysis. These individuals were categorized into three groups based on their body mass index (BMI): those with a BMI below 25 were classified as having a healthy weight, those with a BMI between 25 and 30 were categorized as overweight, and those with a BMI exceeding 30 were considered obese. This study analyzed the gait of 60 participants categorized by BMI. During walking trials, they recorded ground reaction forces electromyography of leg muscles like the gastrocnemii, hamstrings, and quadriceps. Lower limb joint angles and net moments were also calculated. Statistical mapping identified variations in kinematic, kinetic, and muscle activation patterns across the stance phase between BMI groups. ResultsThe results displayed distinct biomechanical patterns in obese individuals. Notably, there was a significant increase in flexion observed in the hip and knee joints (P < 0.001) during the initial stance phase and an increase in hip and knee adduction angles and moments throughout the entire stance phase (P < 0.001). Additionally, muscle activations underwent significant changes (P < 0.01), with a positive correlation noted with the BMI factor. This correlation was most pronounced during the early stance phase for the quadriceps and hamstring muscles and the late stance phase for the gastrocnemius. ConclusionThese findings represent a comprehensive picture that contributes to understanding how excess weight and obesity influence joint biomechanics, highlighting the associated risk of joint osteoarthritis.

Tendon extracellular-matrix-derived tissue engineering micro-tissue for Achilles tendon injury regeneration in rats

BackgroundAchilles tendon is vital in maintaining the stability and function of ankle joint. It is quite difficult to achieve the structural and functional repair of Achilles tendon in tissue engineering.MethodsA tissue-engineered tendon micro-tissue was prepared using rat tail tendon extracellular matrix (TECM) combined with rat adipose stem cells (ADSCs) to repair Achilles tendon injuries. The TECM was prepared by repeated freezing and thawing. The in vitro characteristics of TECM and its effect on ADSCs proliferation were detected. This tissue-engineered tendon micro-tissue for Achilles tendon repair in vivo was evaluated based on general characteristics, gait analysis, ultrasound findings, histological analysis, and biomechanical testing.ResultsThe results showed that the TECM scaffold had good biocompatibility for ADSCs. At 2 weeks post-surgery, collagen types I and III and tenomodulin expression were higher, and vascular endothelial growth factor expression was lower in the micro-tissue group than other groups. At 4 and 8 weeks post-surgery, the results of histological analysis and ultrasound findings showed that the repaired tendon tissue was smooth and lustrous, and was arranged regularly and evenly in the micro-tissue group. Gait analysis confirmed that better motor function recovery was noted in micro-tissue group than other groups. In addition, the mechanical properties of the repaired tendon tissue in micro-tissue group were better than other groups.ConclusionTissue-engineered tendon micro-tissue fabricated by TECM and ADSCs has good biocompatibility and can promote structural and functional repair of tendon in vivo. This composite biomaterial has broad application prospects in tissue engineering.

Extraction and Validation of Biomechanical Gait Parameters with Contactless FMCW Radar.

A 77 GHz frequency-modulated continuous wave (FMCW) radar was utilized to extract biomechanical parameters for gait analysis in indoor scenarios. By preprocessing the collected raw radar data and eliminating environmental noise, a range-velocity-time (RVT) data cube encompassing the subjects' information was derived. The strongest signals from the torso in the velocity and range dimensions and the enveloped signal from the toe in the velocity dimension were individually separated for the gait parameters extraction. Then, six gait parameters, including step time, stride time, step length, stride length, torso velocity, and toe velocity, were measured. In addition, the Qualisys system was concurrently utilized to measure the gait parameters of the subjects as the ground truth. The reliability of the parameters extracted by the radar was validated through the application of the Wilcoxon test, the intraclass correlation coefficient (ICC) value, and Bland-Altman plots. The average errors of the gait parameters in the time, range, and velocity dimensions were less than 0.004 s, 0.002 m, and 0.045 m/s, respectively. This non-contact radar modality promises to be employable for gait monitoring and analysis of the elderly at home.

The efficacy of 3D gait analysis to evaluate surgical (and rehabilitation) outcome after degenerative lumbar surgery

BackgroundLumbar degenerative conditions are a major cause of back pain and disability in individuals aged 45 and above. Gait analysis utilizes sensor technology to collect movement data, aiding in the evaluation of various gait aspects like spatiotemporal parameters, joint angles, neuromuscular activity, and joint forces. It is widely used in conditions such as cerebral palsy and knee osteoarthritis. This research aims to assess the effectiveness of 3D gait analysis in evaluating surgical outcomes and postoperative rehabilitation for lumbar degenerative disorders.MethodsA prospective self-controlled before-after study (n = 85) carried out at our Hospital (Sep 2018 - Dec 2021) utilized a 3D motion analysis system to analyze gait in patients with lumbar degenerative diseases. The study focused on the multifidus muscle, a crucial spinal muscle, during a minimally invasive lumbar interbody fusion surgery conducted by Shandong Weigao Pharmaceutical Co., Ltd. Pre- and postoperative assessments included time-distance parameters (gait speed, stride frequency, stride length, stance phase), hip flexion angle, and stride angle. Changes in 3D gait parameters post-surgery and during rehabilitation were examined. Pearson correlation coefficient was employed to assess relationships with the visual analog pain scale (VAS), Oswestry Disability Index (ODI), and Japanese Orthopedic Association (JOA) scores. Patient sagittal alignment was evaluated using “Surgimap” software from two types of lateral radiographs to obtain parameters like pelvic incidence (PI), pelvic tilt (PT), sacral slope (SS), lumbar lordosis (LL), intervertebral space height (DH), posterior height of the intervertebral space (PDH) at the operative segment, and anterior height of the intervertebral space (ADH).ResultsBy the 6th week post-operation, significant improvements were observed in the VAS score, JOA score, and ODI score of the patients compared to preoperative values (P < 0.05), along with notable enhancements in 3D gait quantification parameters (P < 0.05). Pearson correlation analysis revealed a significant positive correlation between improvements in 3D gait quantification parameters and VAS score, JOA score, and ODI value (all P < 0.001).Conclusion3D gait analysis is a valuable tool for evaluating the efficacy of surgery and rehabilitation training in patients.

Immediate Effects of Wearing an Ankle Bandage on Fine Coordination, Proprioception, Balance and Gait in the Subacute Phase of Ankle Sprains.

Ankle sprains are the most frequently occurring musculoskeletal injuries among recreational athletes. Ankle support through bandages following the initial orthotic treatment might be beneficial for rehabilitation purposes. However, the literature is sparse regarding the use of an ankle support directly after the acute phase of an ankle sprain. Therefore, this study investigates the hypothesis that wearing an ankle bandage immediately after an acute ankle sprain improves motor performance, stability and reduces pain. In total, 70 subjects with acute unilateral supination trauma were tested. Subjects were tested five weeks post-injury to assess immediate effects of the ankle bandage. On the testing day, subjects completed rating questionnaires and underwent comprehensive biomechanical assessments. Biomechanical investigations included fine coordination and proprioception tests, single leg stances, the Y-Balance test, and gait analysis. All biomechanical investigations were conducted for the subject's injured leg with and without a bandage (MalleoTrain® Bauerfeind AG, Zeulenroda-Triebes, Germany) and the healthy leg. Results indicated moderate to strong improvements in ankle stability and pain relief while wearing the bandage. Wearing the bandage significantly normalized single leg stance performance (p < 0.001), stance phase duration (p < 0.001), and vertical ground reaction forces during walking (p < 0.05). However, the bandage did not have a clear effect on fine coordination and proprioception. The findings of our study suggest that ankle bandages may play a crucial role in early-stage rehabilitation by enhancing motor performance and reducing pain.

Wearable sensor-based quantitative gait analysis in Parkinson’s disease patients with different motor subtypes

Gait impairments are among the most common and disabling symptoms of Parkinson’s disease and worsen as the disease progresses. Early detection and diagnosis of subtype-specific gait deficits, as well as progression monitoring, can help to implement effective and preventive personalized treatment for PD patients. Yet, the gait features have not been fully studied in PD and its motor subtypes. To characterize comprehensive and objective gait alterations and to identify the potential gait biomarkers for early diagnosis, subtype differentiation, and disease severity monitoring. We analyzed gait parameters related to upper/lower limbs, trunk and lumbar, and postural transitions from 24 tremor-dominant (TD) and 20 postural instability gait difficulty (PIGD) dominant PD patients who were in early stage and 39 matched healthy controls (HC) during the Timed Up and Go test using wearable sensors. Results show: (1) Both TD and PIGD groups showed restricted backswing range in bilateral lower extremities and more affected side (MAS) arm, reduced trunk and lumbar rotation range in the coronal plane, and low turning efficiency. The receiver operating characteristic (ROC) analysis revealed these objective gait features had high discriminative value in distinguishing both PD subtypes from the HC with the area under the curve (AUC) values of 0.7~0.9 (p < 0.01). (2) Subtle but measurable gait differences existed between TD and PIGD patients before the onset of clinically apparent gait impairment. (3) Specific gait parameters were significantly associated with disease severity in TD and PIGD subtypes. Objective gait biomarkers based on wearable sensors may facilitate timely and personalized gait treatments in PD subtypes through early diagnosis, subtype differentiation, and disease severity monitoring.

The effects of laser cane cues on the freezing of gait of Parkinson's disease patients: can increasing the laser light beam width play a role?

Freezing of gait can be seen in a significant number of people with Parkinson's disease. Disappointingly, the classic standard treatment of Parkinson's disease with dopamine replacement has not shown promising results in improving the freezing of gait. Hence the approach have shifted towards using non-invasive methods to address this problem. To assess the effect of laser cane as a visual cue on the freezing of gait of people with Parkinson's disease and further determine the effect of laser light beam width and color on the freezing of gait. 7 known Parkinson's Disease patients were enrolled in this study, all of whom had at least one episode of freezing at at least one clinical visit. These patients underwent gait analysis in 4 stages: walking without a cane, walking with a thin red light laser cane, a thick red light laser cane, and a green light laser cane. Using laser canes effectively improved nearly all parameters of walking, including right and left stride length, step length, the velocity of movement, and rotation time, compared to walking without a stick. Using different colors of laser cane didn't make any significant difference in improving the freezing of gait of our patients. Nevertheless, increasing the laser light beam width significantly improved almost all walking parameters. This is the first study assessing the effect of laser light beam width on freezing of gait in Parkinson's disease patients and shows promising results in regards to increasing the thickness of laser lights in order to improve walking parameters in Parkinson's disease patients more effectively. Furthermore, this is the second study to evaluate the effect of laser light color, contradicting the previous results by showing no significant correlation between the color of laser light and improvements in walking parameters.