Exploration and demonstration of explainable machine learning models in prosthetic rehabilitation-based gait analysis.

Quantitative gait analysis is important for understanding the non-typical walking patterns associated with mobility impairments. Conventional linear statistical methods and machine learning (ML) models are commonly used to assess gait performance and related changes in the gait parameters. Nonetheless, explainable machine learning provides an alternative technique for distinguishing the significant and influential gait changes stemming from a given intervention. The goal of this work was to demonstrate the use of explainable ML models in gait analysis for prosthetic rehabilitation in both population- and sample-based interpretability analyses. Models were developed to classify amputee gait with two types of prosthetic knee joints. Sagittal plane gait patterns of 21 individuals with unilateral transfemoral amputations were video-recorded and 19 spatiotemporal and kinematic gait parameters were extracted and included in the models. Four ML models-logistic regression, support vector machine, random forest, and LightGBM-were assessed and tested for accuracy and precision. The Shapley Additive exPlanations (SHAP) framework was applied to examine global and local interpretability. Random Forest yielded the highest classification accuracy (98.3%). The SHAP framework quantified the level of influence of each gait parameter in the models where knee flexion-related parameters were found the most influential factors in yielding the outcomes of the models. The sample-based explainable ML provided additional insights over the population-based analyses, including an understanding of the effect of the knee type on the walking style of a specific sample, and whether or not it agreed with global interpretations. It was concluded that explainable ML models can be powerful tools for the assessment of gait-related clinical interventions, revealing important parameters that may be overlooked using conventional statistical methods.

[Factors associated with oral frailty among community-dwelling older people -A comparison between those <75 and ≥75 years old].

PURPOSE: This study investigated the factors associated with oral frailty among community-dwelling older adults. In particular, we compared the factors between individuals in the young-old and old-old groups and clarified the differences between the two groups. METHODS: We measured the basic attributes, body composition, grip strength, gait function, oral function, cognitive function, and daily living function using the Kihon checklist in older people living independently in T City, Aichi Prefecture. The risk of oral frailty was assessed using the Oral Frailty Screening and Evaluation Form (OFI-8), and the measurement results were compared between two groups: those with and those without risk. To identify the factors associated with oral frailty, we performed a multivariate analysis with the risk of oral frailty as the dependent variable and a univariate analysis separately for the young-old and old-old groups. RESULTS: The mean age of the 100 subjects was 76.6±4.6 years old. Forty-four subjects were at risk of oral frailty, and 55 subjects were not at risk. The high-risk group had significantly higher rates of polypharmacy, depression, and a slow walking speed than the no-risk group. The risk factors associated with oral frailty were living alone, polypharmacy, and depression. The risk factors for oral frailty were a poor ambulatory function in the young-old and a poor ambulatory function, decline in the cognitive function, and depression in the old-old. CONCLUSIONS: The results of this study suggest that the risk factors for oral frailty differ between older individuals in the young-old and old-old groups and that age-appropriate support is necessary to prevent oral frailty in older people.

Estimating the prevalence and predictors of musculoskeletal disorders in Tanzania: a cross-sectional pilot study.

Introduction: musculoskeletal (MSK) disorders account for approximately 20% of all years lived with disability worldwide however studies of MSK disorders in Africa are scarce. This pilot study aimed to estimate the community-based prevalence of MSK disorders, identify predictors, and assess the associated disability in a Tanzanian population. Methods: a cross-sectional study was conducted in one village in the Kilimanjaro region from March to June 2019. The Gait, Arms, Legs, Spine (GALS) or paediatric GALS (pGALS) examinations were used during household and school visits. Individuals positive in GALS/pGALS screening were assessed by the regional examination of the musculoskeletal system (REMS) and Modified Health Assessment Questionnaire (MHAQ). Results: among the 1,172 individuals enrolled in households, 95 (8.1%, 95% CI: 6.6 - 9.8) showed signs of MSK disorders using the GALS/pGALS examination and 37 (3.2%, 95% CI: 2.2 - 4.3) using the REMS. Among 682 schools enrolled children, seven showed signs of MSK disorders using the GALS/pGALS examination (1.0%, 95% CI: 0.4 - 2.1) and three using the REMS (0.4%, 95% CI: 0.0 - 1.3). In the household-enrolled adult population, female gender and increasing age were associated with GALS and REMS-positive findings. Among GALS-positive adults, increasing age was associated with REMS-positive status and increasing MHAQ score. Conclusion: this Tanzanian study demonstrates a prevalence of MSK disorders and identifies predictors of MSK disorders comparable to those seen globally. These findings can inform the development of rheumatology services and interventions in Tanzania and the design of future investigations of the determinants of MSK disorders, and their impacts on health, livelihoods, and well-being.

Physical exercise for people with Parkinson's disease: a systematic review and network meta-analysis.

BACKGROUND: Physical exercise is effective in managing Parkinson's disease (PD), but the relative benefit of different exercise types remains unclear. OBJECTIVES: To compare the effects of different types of physical exercise in adults with PD on the severity of motor signs, quality of life (QoL), and the occurrence of adverse events, and to generate a clinically meaningful treatment ranking using network meta-analyses (NMAs). SEARCH METHODS: An experienced information specialist performed a systematic search for relevant articles in CENTRAL, MEDLINE, Embase, and five other databases to 17 May 2021. We also searched trial registries, conference proceedings, and reference lists of identified studies up to this date. SELECTION CRITERIA: We included randomized controlled trials (RCTs) comparing one type of physical exercise for adults with PD to another type of exercise, a control group, or both. DATA COLLECTION AND ANALYSIS: Two review authors independently extracted data. A third author was involved in case of disagreements. We categorized the interventions and analyzed their effects on the severity of motor signs, QoL, freezing of gait, and functional mobility and balance up to six weeks after the intervention using NMAs. Two review authors independently assessed the risk of bias using the risk of bias 2 (RoB 2) tool and rated the confidence in the evidence using the CINeMA approach for results on the severity of motor signs and QoL. We consulted a third review author to resolve any disagreements. Due to heterogeneous reporting of adverse events, we summarized safety data narratively and rated our confidence in the evidence using the GRADE approach. MAIN RESULTS: We included 154 RCTs with a total of 7837 participants with mostly mild to moderate disease and no major cognitive impairment. The number of participants per study was small (mean 51, range from 10 to 474). The NMAs on the severity of motor signs and QoL included data from 60 (2721 participants), and 48 (3029 participants) trials, respectively. Eighty-five studies (5192 participants) provided safety data. Here, we present the main results. We observed evidence of beneficial effects for most types of physical exercise included in our review compared to a passive control group. The effects on the severity of motor signs and QoL are expressed as scores on the motor scale of the Unified Parkinson's Disease Rating Scale (UPDRS-M) and the Parkinson's Disease Questionnaire 39 (PDQ-39), respectively. For both scales, higher scores denote higher symptom burden. Therefore, negative estimates reflect improvement (minimum clinically important difference: -2.5 for UPDRS-M and -4.72 for PDQ-39). Severity of motor signs The evidence from the NMA (60 studies; 2721 participants) suggests that dance and gait/balance/functional training probably have a moderate beneficial effect on the severity of motor signs (dance: mean difference (MD) -10.18, 95% confidence interval (CI) -14.87 to -5.36; gait/balance/functional training: MD -7.50, 95% CI -11.39 to -3.48; moderate confidence), and multi-domain training probably has a small beneficial effect on the severity of motor signs (MD -5.90, 95% CI -9.11 to -2.68; moderate confidence). The evidence also suggests that endurance, aqua-based, strength/resistance, and mind-body training might have a small beneficial effect on the severity of motor signs (endurance training: MD -5.76, 95% CI -9.78 to -1.74; aqua-based training: MD -5.09, 95% CI -10.45 to 0.40; strength/resistance training: MD -4.96, 95% CI -9.51 to -0.40; mind-body training: MD -3.62, 95% CI -7.24 to 0.00; low confidence). The evidence is very uncertain about the effects of "Lee Silverman Voice training BIG" (LSVT BIG) and flexibility training on the severity of motor signs (LSVT BIG: MD -6.70, 95% CI -16.48 to 3.08; flexibility training: MD 4.20, 95% CI -1.61 to 9.92; very low confidence). Quality of life The evidence from the NMA (48 studies; 3029 participants) suggests that aqua-based training probably has a large beneficial effect on QoL (MD -15.15, 95% CI -23.43 to -6.87; moderate confidence). The evidence also suggests that mind-body, gait/balance/functional, and multi-domain training and dance might have a small beneficial effect on QoL (mind-body training: MD -7.22, 95% CI -13.57 to -0.70; gait/balance/functional training: MD -6.17, 95% CI -10.75 to -1.59; multi-domain training: MD -5.29, 95% CI -9.51 to -1.06; dance: MD -3.88, 95% CI -10.92 to 3.00; low confidence). The evidence is very uncertain about the effects of gaming, strength/resistance, endurance, and flexibility training on QoL (gaming: MD -8.99, 95% CI -23.43 to 5.46; strength/resistance training: MD -6.70, 95% CI -12.86 to -0.35; endurance training: MD -6.52, 95% CI -13.74 to 0.88; flexibility training: MD 1.94, 95% CI -10.40 to 14.27; very low confidence). Adverse events Only 85 studies (5192 participants) provided some kind of safety data, mostly only for the intervention groups. No adverse events (AEs) occurred in 40 studies and no serious AEs occurred in four studies. AEs occurred in 28 studies. The most frequently reported events were falls (18 studies) and pain (10 studies). The evidence is very uncertain about the effect of physical exercise on the risk of adverse events (very low confidence). Across outcomes, we observed little evidence of differences between exercise types. AUTHORS' CONCLUSIONS: We found evidence of beneficial effects on the severity of motor signs and QoL for most types of physical exercise for people with PD included in this review, but little evidence of differences between these interventions. Thus, our review highlights the importance of physical exercise regarding our primary outcomes severity of motor signs and QoL, while the exact exercise type might be secondary. Notably, this conclusion is consistent with the possibility that specific motor symptoms may be treated most effectively by PD-specific programs. Although the evidence is very uncertain about the effect of exercise on the risk of adverse events, the interventions included in our review were described as relatively safe. Larger, well-conducted studies are needed to increase confidence in the evidence. Additional studies recruiting people with advanced disease severity and cognitive impairment might help extend the generalizability of our findings to a broader range of people with PD.

Three-Dimensional Instrumented Gait Analysis for Children With Cerebral Palsy: An Evidence-Based Clinical Practice Guideline.

BACKGROUND: Children with cerebral palsy (CP) who walk have complex gait patterns and deviations often requiring physical therapy (PT)/medical/surgical interventions. Walking in children with CP can be assessed with 3-dimensional instrumented gait analysis (3D-IGA) providing kinematics (joint angles), kinetics (joint moments/powers), and muscle activity. PURPOSE: This clinical practice guideline provides PTs, physicians, and associated clinicians involved in the care of children with CP, with 7 action statements on when and how 3D-IGA can inform clinical assessments and potential interventions. It links the action statement grades with specific levels of evidence based on a critical appraisal of the literature. CONCLUSIONS: This clinical practice guideline addresses 3D-IGA's utility to inform surgical and non-surgical interventions, to identify gait deviations among segments/joints and planes and to evaluate the effectiveness of interventions. Best practice statements provide guidance for clinicians about the preferred characteristics of 3D-IGA laboratories including instrumentation, staffing, and reporting practices.Video Abstract: Supplemental digital content available at http://links.lww.com/PPT/A524.

The impact of pediatric obesity on biomechanical differences across the gait cycle at three walking speeds.

BACKGROUND: Obesity impacts a child's ability to walk with resulting biomechanical adaptations; however, existing research has not comprehensively compared differences across the gait cycle. We examined differences in lower extremity biomechanics across the gait cycle between children with and without obesity at three walking speeds. METHODS: Full gait cycles of age-matched children with obesity (N = 10; BMI: 25.7 ± 4.2 kg/m2) and without obesity (N = 10; BMI: 17.0 ± 1.9 kg/m2) were analyzed at slow, normal, and fast walking speeds. Main and interaction effects of group and speed across hip, knee, and ankle joint angles and moments in sagittal, frontal, and transverse planes were analyzed using one-dimensional statistical parametric mapping. FINDINGS: Compared to children without obesity, children with obesity had greater hip adduction during mid-stance, while also producing greater hip extensor moments during early stance phase, abductor moments throughout most of stance, and hip external rotator moments during late stance. Children with obesity recorded greater knee flexor, knee extensor and knee internal rotator moments during early stance, and knee external rotator moments in late stance than children without obesity; children with obesity also demonstrated greater ankle plantarflexor moments throughout mid and late stance. Interaction effects existed within joint kinetics data; children with obesity produced greater hip extensor moments at initial contact and toe-off when walking at fast compared to normal walking speed. INTERPRETATION: While few kinematic differences existed between the two groups, children with obesity exhibited greater moments at the hip, knee, and ankle during critical periods of controlling and stabilizing mass.

Trial- vs. cycle-level detrending in the analysis of cyclical biomechanical data.

Biomechanical time series may contain low-frequency trends due to factors like electromechanical drift, attentional drift and fatigue. Existing detrending procedures are predominantly conducted at the trial level, removing trends that exist over finite, adjacent time windows, but this fails to consider what we term 'cycle-level trends': trends that occur in cyclical movements like gait and that vary across the movement cycle, for example: positive and negative drifts in early and late gait phases, respectively. The purposes of this study were to describe cycle-level detrending and to investigate the frequencies with which cycle-level trends (i) exist, and (ii) statistically affect results. Anterioposterior ground reaction forces (GRF) from the 41-subject, 8-speed, open treadmill walking dataset of Fukuchi (2018) were analyzed. Of a total of 552 analyzed trials, significant cycle-level trends were found approximately three times more frequently (21.1%) than significant trial-level trends (7.4%). In statistical comparisons of adjacent walking speeds (i.e., speed 1 vs. 2, 2 vs. 3, etc.) just 3.3% of trials exhibited cycle-level trends that changed the null hypothesis rejection decision. However 17.6% of trials exhibited cycle-level trends that qualitatively changed the stance phase regions identified as significant. Although these results are preliminary and derived from just one dataset, results suggest that cycle-level trends can contribute to analysis bias, and therefore that cycle-level trends should be considered and/or removed where possible. Software implementing the proposed cycle-level detrending is available at https://github.com/0todd0000/detrend1d.

Turns while walking among individuals with Parkinson's disease following overground locomotor training: A pilot study.

BACKGROUND: Individuals with Parkinson's disease are challenged in making turns while walking, evidenced by reduced intersegmental coordination and reduced dynamic postural stability. Although overground locomotor training previously improved ambulation among people with Parkinson's disease, its effect on walking turns remained unknown. We sought to understand the effects of overground locomotor training on walking turns among individuals with mild-Parkinson's disease. METHODS: Twelve participants with Parkinson's (7 Males/5 Females; Age: 68.5 ± 6.4 years) completed twenty-four sessions lasting approximately 60 min and over 12-15 weeks. Baseline and follow-up assessments included the ten-minute walk test using wearable sensors. Primary outcomes included changes to intersegmental coordination, measured by peak rotation and normalized peak rotation, and dynamic postural stability, measured by peak turn velocities in the frontal and transverse planes. Statistical analysis included one-tailed paired t-tests and Cohen's d effect sizes with α = 0.05. FINDINGS: No effects of overground locomotor training on mean peak thoracic rotation (+0.23 ± 4.24°; Cohen's d = 0.05; P = 0.45) or mean normalized peak thoracic rotation (-0.59 ± 5.52 (unitless); Cohen's d = 0.10; P = 0.45) were observed. Moderate and small effects of overground locomotor training were observed on mean peak turn velocities in the frontal (+1.59 ± 2.18°/s; Cohen's d = 0.43; P = 0.01) and transverse planes (+0.88 ± 3.18°/s; Cohen's d = 0.25; P = 0.18). INTERPRETATION: This pilot study provides preliminary evidence suggesting that individuals with mild-Parkinson's moderately improved frontal plane dynamic postural stability after overground locomotor training, likely attenuating the perturbations experienced while turning. CLINICAL TRIAL REGISTRATION: NCT03864393.

Limb and joint kinetics during walking in individuals with Mild-Moderate Parkinson's disease.

Given the known deficits in spatiotemporal aspects of gait for people with Parkinson's disease (PD), we sought to determine the underlying gait abnormalities in limb and joint kinetics, and examine how deficits in push-off and leg swing might contribute to the shortened step lengths for people with PD. Ten participants with PD and 11 age-matched control participants walked overground and on an instrumented treadmill. Participants with PD then walked on the treadmill with a posteriorly directed restraining force applied to 1) the pelvis to challenge push-off and 2) the ankles to challenge leg swing. Spatiotemporal, kinematic, and force data were collected and compared between groups and conditions. Despite group differences in spatiotemporal measures during overground walking, we did not observe these differences when the groups walked on a treadmill at comparable speeds. Nevertheless, the hip extension impulse appeared smaller in the PD group during their typical walking. When challenging limb propulsion, participants in the PD group maintained step lengths by increasing the propulsive impulse. Participants with PD were also able to maintain their typical step length against resistance intended to impede swing limb advancement, and even increased step lengths with cuing. The presence of reduced hip extension torque might be an early indicator of gait deterioration in this neurodegenerative disease. Our participants with PD were able to increase hip extension torque in response to needed demands. Additionally, participants with PD were able to increase limb propulsion and leg swing against resistance, suggesting a reserve in limb mechanics.

Visual feedback improves propulsive force generation during treadmill walking in people with Parkinson disease.

Persons with Parkinson's disease experience gait alterations, such as reduced step length. Gait dysfunction is a significant research priority as the current treatments targeting gait impairment are limited. This study aimed to investigate the effects of visual biofeedback on propulsive force during treadmill walking in persons with Parkinson's. Sixteen ambulatory persons with Parkinson's participated in the study. They received real-time biofeedback of anterior ground reaction force during treadmill walking at a constant speed. Peak propulsive force values were measured and normalized to body weight. Spatiotemporal parameters were also assessed, including stride length and double support percent. Persons with Parkinson's significantly increased peak propulsive force during biofeedback compared to baseline (p <.0001, Cohen's dz = 1.69). Variability in peak anterior ground reaction force decreased across repeated trials (p <.0001, dz = 1.51). While spatiotemporal parameters did not show significant changes individually, stride length and double support percent improved marginally during biofeedback trials. Persons with Parkinson's can increase propulsive force with visual biofeedback, suggesting the presence of a propulsive reserve. Though stride length did not significantly change, clinically meaningful improvements were observed. Targeting push-off force through visual biofeedback may offer a potential rehabilitation technique to enhance gait performance in Persons with Parkinson's. Future studies could explore the long-term efficacy of this intervention and investigate additional strategies to improve gait in Parkinson's disease.

Accuracy of conventional motion capture in measuring hip joint center location and hip rotations during gait, squat, and step-up activities.

Accurate measurements of hip joint kinematics are essential for improving our understanding of the effects of injury, disease, and surgical intervention on long-term hip joint health. This study assessed the accuracy of conventional motion capture (MoCap) for measuring hip joint center (HJC) location and hip joint angles during gait, squat, and step-up activities while using dynamic biplane radiography (DBR) as the reference standard. Twenty-four young adults performed six trials of treadmill walking, six body-weight squats, and six step-ups within a biplane radiography system. Synchronized biplane radiographs were collected at 50 images per second and MoCap was collected simultaneously at 100 images per second. Bone motion during each activity was determined by matching digitally reconstructed radiographs, created from subject-specific CT-based bone models, to the biplane radiographs using a validated registration process. Errors in estimating HJC location and hip angles using MoCap were quantified by the root mean squared error (RMSE) across all frames of available data. The MoCap error in estimating HJC location was larger during step-up (up to 89.3 mm) than during gait (up to 16.6 mm) or squat (up to 31.4 mm) in all three anatomic directions (all p < 0.001). RMSE in hip joint flexion (7.2°) and abduction (4.3°) during gait was less than during squat (23.8° and 8.9°) and step-up (20.1° and 10.6°) (all p < 0.01). Clinical analysis and computational models that rely on skin-mounted markers to estimate hip kinematics should be interpreted with caution, especially during activities that involve deeper hip flexion.

Comparative analysis of gait: Similar coronal but different sagittal effects between closing-wedge and opening-wedge high tibial osteotomy.

BACKGROUND: High tibial osteotomy is an established surgical option for medial compartment osteoarthritis of the knee with varus alignment. It can be divided into open wedge and closing wedge by operative technique. Although they have fundamental differences, little is known about the biomechanical consequences of the two surgical methods. METHODS: Thirty-eight patients with medial compartment osteoarthritis who underwent high tibial osteotomy (19 open-wedge and 19 closing-wedge) were retrospectively reviewed. Clinical scores and radiological measurements were assessed until postoperative two years. Gait analysis was performed preoperatively and again at postoperative one year. FINDINGS: Varus alignment was corrected in both groups without a significant difference between them (p = 0.543). However, posterior tibial slope was higher, and the Blackburne-Peel ratio was lower in the open wedge osteotomy group after surgery (both p < 0.001). Reduction of dynamic knee varus and knee adduction moment were observed in both groups without significant differences. However, after surgery, average knee range of motion (63.3° vs 57.3°, p < 0.001) and the magnitude of knee flexion moment was significantly lower (p = 0.005) in the closing wedge group. There were no significant differences in the Kujala Anterior Knee Pain Scale and the occurrence of patellofemoral arthritis between the groups postoperatively. INTERPRETATION: After osteotomy, a smaller average knee range of motion in the sagittal plane and a higher knee flexion moment were observed in the open wedge osteotomy group, suggesting quadriceps muscle avoidance. However, no differences in clinical scores or the short-term occurrence of patellofemoral arthritis were noted between the two surgical techniques.

Estimation of electrical muscle activity during gait using inertial measurement units with convolution attention neural network and small-scale dataset.

In general, muscle activity can be directly measured using Electromyography (EMG) or calculated with musculoskeletal models. However, both methods are not suitable for non-technical users and unstructured environments. It is desired to establish more portable and easy-to-use muscle activity estimation methods. Deep learning (DL) models combined with inertial measurement units (IMUs) have shown great potential to estimate muscle activity. However, it frequently occurs in clinical scenarios that a very small amount of data is available and leads to limited performance of the DL models, while the augmentation techniques to efficiently expand a small sample size for DL model training are rarely used. The primary aim of the present study was to develop a novel DL model to estimate the EMG envelope during gait using IMUs with high accuracy. A secondary aim was to develop a novel model-based data augmentation method to improve the performance of the estimation model with small-scale dataset. Therefore, in the present study, a time convolutional network-based generative adversarial network, namely MuscleGAN, was proposed for data augmentation. Moreover, a subject-independent regression DL model was developed to estimate EMG envelope. Results suggested that the proposed two-stage method has better generalization and estimation performance than the commonly used existing methods. Pearson correlation coefficient and normalized root-mean-square errors derived from the proposed method reached up to 0.72 and 0.13, respectively. It was indicated that the MuscleGAN indeed improved the estimation accuracy of lower limb EMG envelope from 70% to 72%. Thus, even using only two IMUs and a very small-scale dataset, the proposed model is still capable of accurately estimating lower limb EMG envelope, demonstrating considerable potential for its application in clinical and daily life scenarios.

Mobility-related brain regions linking carotid intima-media thickness to specific gait performances in old age.

BACKGROUND: Gait disturbance is common in older adults with vascular diseases. However, how carotid atherosclerosis affects gait remains poorly understood. The objectives were to investigate the associations between carotid intima-media thickness and specific gait performances and explore the potential role of brain structure in mediating these associations. METHODS: A cross-sectional analysis of data from the Taizhou Imaging Study was conducted, including 707 individuals who underwent both gait and carotid ultrasound examinations. Gait assessments include the Timed-Up-and-Go test, the Tinetti test, and quantitative gait assessment using a wearable device. Quantitative parameters were summarized into independent gait domains with factor analysis. Magnetic resonance images were obtained on a 3.0-Tesla scanner, and the volumes of fifteen brain regions related to motor function (primary motor, sensorimotor), visuospatial attention (inferior posterior parietal lobules, superior posterior parietal lobules), executive control function (dorsolateral prefrontal cortex, anterior cingulate), memory (hippocampus, entorhinal cortex), motor imagery (precuneus, parahippocampus, posterior cingulated cortex), and balance (basal ganglia: pallidum, putamen, caudate, thalamus) were computed using FreeSurfer and the Desikan-Killiany atlas. Mediation analysis was conducted with carotid intima-media thickness as the predictor and mobility-related brain regions as mediators. RESULTS: Carotid intima-media thickness was found to be associated with the Timed-Up-and-Go performance (ß = 0.129, p = 0.010) as well as gait performances related to pace (ß=-0.213, p < 0.001) and symmetry (ß = 0.096, p = 0.045). Besides, gait performances were correlated with mobility-related brain regions responsible for motor, visuospatial attention, executive control, memory, and balance (all FDR < 0.05). Notably, significant regions differed depending on the gait outcomes measured. The primary motor (41.9%), sensorimotor (29.3%), visuospatial attention (inferior posterior parietal lobules, superior posterior parietal lobules) (13.8%), entorhinal cortex (36.4%), and motor imagery (precuneus, parahippocampus, posterior cingulated cortex) (27.3%) mediated the association between increased carotid intima-media thickness and poorer Timed-Up-and-Go performance. For the pace domain, the primary motor (37.5%), sensorimotor (25.8%), visuospatial attention (12.3%), entorhinal cortex (20.7%), motor imagery (24.9%), and balance (basal ganglia: pallidum, putamen, caudate, thalamus) (11.6%) acted as mediators. CONCLUSIONS: Carotid intima-media thickness is associated with gait performances, and mobility-related brain volume mediates these associations. Moreover, the distribution of brain regions regulating mobility varies in the different gait domains. Our study adds value in exploring the underlying mechanisms of gait disturbance in the aging population.

Noninvasive spinal stimulation improves walking in chronic stroke survivors: a proof-of-concept case series.

BACKGROUND: After stroke, restoring safe, independent, and efficient walking is a top rehabilitation priority. However, in nearly 70% of stroke survivors asymmetrical walking patterns and reduced walking speed persist. This case series study aims to investigate the effectiveness of transcutaneous spinal cord stimulation (tSCS) in enhancing walking ability of persons with chronic stroke. METHODS: Eight participants with hemiparesis after a single, chronic stroke were enrolled. Each participant was assigned to either the Stim group (N = 4, gait training + tSCS) or Control group (N = 4, gait training alone). Each participant in the Stim group was matched to a participant in the Control group based on age, time since stroke, and self-selected gait speed. For the Stim group, tSCS was delivered during gait training via electrodes placed on the skin between the spinous processes of C5-C6, T11-T12, and L1-L2. Both groups received 24 sessions of gait training over 8 weeks with a physical therapist providing verbal cueing for improved gait symmetry. Gait speed (measured from 10 m walk test), endurance (measured from 6 min walk test), spatiotemporal gait symmetries (step length and swing time), as well as the neurophysiological outcomes (muscle synergy, resting motor thresholds via spinal motor evoked responses) were collected without tSCS at baseline, completion, and 3 month follow-up. RESULTS: All four Stim participants sustained spatiotemporal symmetry improvements at the 3 month follow-up (step length: 17.7%, swing time: 10.1%) compared to the Control group (step length: 1.1%, swing time 3.6%). Additionally, 3 of 4 Stim participants showed increased number of muscle synergies and/or lowered resting motor thresholds compared to the Control group. CONCLUSIONS: This study provides promising preliminary evidence that using tSCS as a therapeutic catalyst to gait training may increase the efficacy of gait rehabilitation in individuals with chronic stroke. Trial registration NCT03714282 (clinicaltrials.gov), registration date: 2018-10-18.

The effect of upper limb loading with external weights on gait and trunk control in ambulatory children with spastic hemiplegic cerebral palsy: a randomized controlled trial.

OBJECTIVE: Children with hemiplegic cerebral palsy (CP) are typically ambulant with high motor functioning levels but with gait asymmetry and a greater risk of instability and falling. Physiotherapy is considered the core part of CP rehabilitation due to the risk of neurosurgery and the side effects of drug interventions. Although growing evidence has looked at the effect of upper limb loading during walking in many populations, such interventions in children with CP remain unexplored yet. The purpose of this study was to investigate if loading the upper limbs with external weights could improve walking speed, trunk control, and balance in ambulatory children with hemiplegic CP. PATIENTS AND METHODS: The following outcome measures were recorded at baseline and six weeks after the intervention: gait speed [10-Meter Walk Test (10 MWT)], trunk control [Trunk Control Measurement Scale (TCMS)], and balance [Pediatric Balance Scale (PBS)]. Multiple 2 (groups) x 2 (time-points) mixed analysis of variance models (ANOVAs) were used for analysis. RESULTS: Both groups showed a significant improvement (p < 0.001) in 10 MWT, TCMS, and PBS scores post-intervention. However, the magnitude of change in the outcome measures was higher in the intervention group (10 MWT = 0.59 m/s, TCMS = 10.41, PBS = 9.35) compared to the control group (10 MWT = 0.37 m/s, TCMS = 6.43, PBS = 4.68). CONCLUSIONS: This study demonstrated that although both control and intervention groups showed improvements in terms of gait speed, trunk control, and balance, the intervention group that had upper limb loading showed higher significant improvements.  Clinicaltrial.gov ID: NCT05444387.

Minimal detectable change of gait and balance measures in older neurological patients: estimating the standard error of the measurement from before-after rehabilitation data thanks to the linear mixed-effects models.

BACKGROUND: Tracking gait and balance impairment in time is paramount in the care of older neurological patients. The Minimal Detectable Change (MDC), built upon the Standard Error of the Measurement (SEM), is the smallest modification of a measure exceeding the measurement error. Here, a novel method based on linear mixed-effects models (LMMs) is applied to estimate the standard error of the measurement from data collected before and after rehabilitation and calculate the MDC of gait and balance measures. METHODS: One hundred nine older adults with a gait impairment due to neurological disease (66 stroke patients) completed two assessment sessions before and after inpatient rehabilitation. In each session, two trials of the 10-meter walking test and the Timed Up and Go (TUG) test, instrumented with inertial sensors, have been collected. The 95% MDC was calculated for the gait speed, TUG test duration (TTD) and other measures from the TUG test, including the angular velocity peak (ωpeak) in the TUG test's turning phase. Random intercepts and slopes LMMs with sessions as fixed effects were used to estimate SEM. LMMs assumptions (residuals normality and homoscedasticity) were checked, and the predictor variable ln-transformed if needed. RESULTS: The MDC of gait speed was 0.13 m/s. The TTD MDC, ln-transformed and then expressed as a percentage of the baseline value to meet LMMs' assumptions, was 15%, i.e. TTD should be < 85% of the baseline value to conclude the patient's improvement. ωpeak MDC, also ln-transformed and expressed as the baseline percentage change, was 25%. CONCLUSIONS: LMMs allowed calculating the MDC of gait and balance measures even if the test-retest steady-state assumption did not hold. The MDC of gait speed, TTD and ωpeak from the TUG test with an inertial sensor have been provided. These indices allow monitoring of the gait and balance impairment, which is central for patients with an increased falling risk, such as neurological old persons. TRIAL REGISTRATION: NA.

Identifying changes in dynamic plantar pressure associated with radiological knee osteoarthritis based on machine learning and wearable devices.

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

The Difference in the Assessment of Knee Extension/Flexion Angles during Gait between Two Calibration Methods for Wearable Goniometer Sensors.

Frontal and axial knee motion can affect the accuracy of the knee extension/flexion motion measurement using a wearable goniometer. The purpose of this study was to test the hypothesis that calibrating the goniometer on an individual's body would reduce errors in knee flexion angle during gait, compared to bench calibration. Ten young adults (23.2 ± 1.3 years) were enrolled. Knee flexion angles during gait were simultaneously assessed using a wearable goniometer sensor and an optical three-dimensional motion analysis system, and the absolute error (AE) between the two methods was calculated. The mean AE across a gait cycle was 2.4° (0.5°) for the on-body calibration, and the AE was acceptable (<5°) throughout a gait cycle (range: 1.5-3.8°). The mean AE for the on-bench calibration was 4.9° (3.4°) (range: 1.9-13.6°). Statistical parametric mapping (SPM) analysis revealed that the AE of the on-body calibration was significantly smaller than that of the on-bench calibration during 67-82% of the gait cycle. The results indicated that the on-body calibration of a goniometer sensor had acceptable and better validity compared to the on-bench calibration, especially for the swing phase of gait.

Introducing the Pi-CON Methodology to Overcome Usability Deficits during Remote Patient Monitoring.

The adoption of telehealth has soared, and with that the acceptance of Remote Patient Monitoring (RPM) and virtual care. A review of the literature illustrates, however, that poor device usability can impact the generated data when using Patient-Generated Health Data (PGHD) devices, such as wearables or home use medical devices, when used outside a health facility. The Pi-CON methodology is introduced to overcome these challenges and guide the definition of user-friendly and intuitive devices in the future. Pi-CON stands for passive, continuous, and non-contact, and describes the ability to acquire health data, such as vital signs, continuously and passively with limited user interaction and without attaching any sensors to the patient. The paper highlights the advantages of Pi-CON by leveraging various sensors and techniques, such as radar, remote photoplethysmography, and infrared. It illustrates potential concerns and discusses future applications Pi-CON could be used for, including gait and fall monitoring by installing an omnipresent sensor based on the Pi-CON methodology. This would allow automatic data collection once a person is recognized, and could be extended with an integrated gateway so multiple cameras could be installed to enable data feeds to a cloud-based interface, allowing clinicians and family members to monitor patient health status remotely at any time.