Gait Measures Research Articles

Vascular risk, gait, behavioral, and plasma indicators of VCID.

Cost-effective screening tools for vascular contributions to cognitive impairment and dementia (VCID) has significant implications. We evaluated non-imaging indicators of VCID using magnetic resonance imaging (MRI)-measured white matter (WM) damage and hypothesized that these indicators differ based on age. In 745 participants from the Mayo Clinic Study of Aging (≥50 years of age) with serial WM assessments from diffusion MRI and fluid-attenuated inversion recovery (FLAIR)-MRI, we examined associations between baseline non-imaging indicators (demographics, vascular risk factors [VRFs], gait, behavioral, plasma glial fibrillary acidic protein [GFAP], and plasma neurofilament light chain [NfL]) and WM damage across three age tertiles. VRFs and gait were associated with diffusion changes even in low age strata. All measures (VRFs, gait, behavioral, plasma GFAP, plasma NfL) were associated with white matter hyperintensities (WMHs) but mainly in intermediate and high age strata. Non-imaging indicators of VCID were related to WM damage and may aid in screening participants and assessing outcomes for VCID. Non-imaging indicators of VCID can aid in prediction of MRI-measured WM damage but their importance differed by age. Vascular risk and gait measures were associated with early VCID changes measured using diffusion MRI. Plasma markers explained variability in WMH across age strata. Most non-imaging measures explained variability in WMH and vascular WM scores in intermediate and older age groups. The framework developed here can be used to evaluate new non-imaging VCID indicators proposed in the future.

Effect of orthopedic insoles on spinal deformity and walking in adolescents with idiopathic scoliosis summary.

To observe the effects of scoliosis-specific exercise therapy combined with braces and orthopedic insoles on improved spinal deformity and walking ability in adolescents with idiopathic scoliosis (AIS). From September 2019 to September 2020, 60 outpatient AIS patients were distributed into brace group (n = 30) at random and brace combined orthopedic insole group (n = 30). Both groups underwent brace dryness, and the observation group used scoliosis-specific exercise therapy combined with brace therapy, and on this basis, orthopedic insole intervention was added for 8 h per day for 2 months. At the same time, 20 adolescents of the same age with normal spinal development were recruited as a healthy group. GaitScan instruments were used to collect gait and plantar pressure measurements from study subjects. First, the gait and plantar pressure data of AIS patients and healthy groups were compared horizontally to ascertain the abnormal indicators, and then the spinal deformity and the above abnormal indicators were compared between the brace group and the brace combined orthopedic insole group. The plantar pressure center drift index (CPEI) in the AIS group was higher than that in the healthy group (F = 3.120, P < 0.05), and there were significant differences in the ratio of medial and lateral heel pressure (M/l) and total foot pressure (P < 0.05) between the AIS group and the healthy group, and no noticeable variations were found in the support phase period, walking speed, and proportion of each phase (P > 0.05). After treatment, the Cobb angle was significantly reduced in both the brace group and the brace combined with orthopedic insole group (P < 0.05), and there was no significant difference between the groups (P > 0.05). There were no significant changes in the pressure ratio of CPEI, M/l and bilateral full foot in the brace group (P > 0.05). The CPEI decreased in the brace combined with orthopedic insole group (P < 0.05), and the pressure ratio of M/l and bilateral full foot tended to 1 (P < 0.05), and was better than that in the brace group (P < 0.05). Patients with AIS may have local and worldwide asymmetric changes in plantar pressure distribution. The addition of orthopedic insoles has limited effect on improving scoliosis deformity in patients with AIS, but it can effectively improve the abnormal biomechanics of patients with AIS, so that the patient's force tends to be balanced.

A machine learning approach to identify important variables for distinguishing between fallers and non-fallers in older women.

Falls are a significant ongoing public health concern for older adults. At present, few studies have concurrently explored the influence of multiple measures when seeking to determine which variables are most predictive of fall risks. As such, this cross-sectional study aimed to identify those functional variables (i.e. balance, gait and clinical measures) and physical characteristics (i.e. strength and body composition) that could best distinguish between older female fallers and non-fallers, using a machine learning approach. Overall, 60 community-dwelling older women (≥65 years), retrospectively classified as fallers (n = 21) or non-fallers (n = 39), attended three data collection sessions. Data (281 variables) collected from tests in five separate domains (balance, gait, clinical measures, strength and body composition) were analysed using random forest (RF) and leave-one-variable-out partial least squares correlation analysis (LOVO PLSCA) to assess variable importance. The strongest discriminators from each domain were then aggregated into a multi-domain dataset, and RF, LOVO PLSCA, and logistic regression models were constructed to identify the important variables in distinguishing between fallers and non-fallers. These models were used to classify participants as either fallers or non-fallers, with their performance evaluated using receiver operating characteristic (ROC) analysis. The study found that it is possible to classify fallers and non-fallers with a high degree of accuracy (e.g. logistic regression: sensitivity = 90%; specificity = 87%; AUC = 0.92; leave-one-out cross-validation accuracy = 63%) using a combination of 18 variables from four domains, with the gait and strength domains being particularly informative for screening programmes aimed at assessing falls risk.

Unravelling the gait and balance: A novel approach for detecting depression in young healthy individuals

Depression is a prevalent mental health disorder that affects people of all ages and origins; therefore, early detection is essential for timely intervention and support. This investigation proposes a novel method for detecting melancholy in young, healthy individuals by analysing their gait and balance patterns. In order to accomplish this, a comprehensive system is designed that incorporates cutting-edge technologies such as a Barometric Pressure Sensor, Beck Depression Inventory (BDI), and t-Distributed Stochastic Neighbour Embedding (t-SNE) algorithm. The system intends to capitalize on the subtle motor and physiological changes associated with melancholy, which may manifest in a person’s gait and balance. The Barometric Pressure Sensor is used to estimate variations in altitude and vertical velocity, thereby adding context to the evaluation. The mood states of participants are evaluated using the BDI, a well-established psychological assessment instrument that provides insight into their emotional health. Integrated and pre-processed data from the Barometric Pressure Sensor, BDI responses, and gait and balance measurements. The t-SNE algorithm is then used to map the high-dimensional data into a lower-dimensional space while maintaining the local structure and identifying underlying patterns within the dataset. The t-SNE algorithm improves visualization and pattern recognition by reducing the dimensionality of the data, allowing for a more nuanced analysis of depression-related markers. As the proposed system combines objective physiological measurements

Balance telerehabilitation and wearable technology for people with Parkinson’s disease (TelePD trial)

BackgroundBalance impairments, that lead to falls, are one of the main symptoms of Parkinson’s disease (PD). Telerehabilitation is becoming more common for people with PD; however, balance is particularly challenging to assess and treat virtually. The feasibility and efficacy of virtual assessment and virtual treatment of balance in people with PD are unknown. The present study protocol has three aims: I) to determine if a virtual balance and gait assessment (instrumented L-shape mobility test) with wearable sensors can predict a gold-standard, in-person clinical assessment of balance, the Mini Balance Evaluation Systems Test (Mini-BESTest); II) to explore the effects of 12 sessions of balance telerehabilitation and unsupervised home exercises on balance, gait, executive function, and clinical scales; and III) to explore if improvements after balance telerehabilitation transfer to daily-life mobility, as measured by instrumented socks with inertial sensors worn for 7 days.MethodsThe TelePD Trial is a prospective, single-center, parallel-group, single-blind, pilot, randomized, controlled trial. This trial will enroll 80 eligible people with PD. Participants will be randomized at a 1:1 ratio into receiving home-based balance exercises in either: 1) balance telerehabilitation (experimental group, n = 40) or 2) unsupervised exercises (control group, n = 40). Both groups will perform 12 sessions of exercise at home that are 60 min long. The primary outcome will be Mini-BESTest. The secondary outcomes will be upper and lower body gait metrics from a prescribed task (instrumented L-shape mobility test); daily-life mobility measures over 7 days with wearable sensors in socks, instrumented executive function tests, and clinical scales. Baseline testing and 7 days of daily-life mobility measurement will occur before and after the intervention period.ConclusionThe TelePD Trial will be the first to explore the usefulness of using wearable sensor-based measures of balance and gait remotely to assess balance, the feasibility and efficacy of balance telerehabilitation in people with PD, and the translation of balance improvements after telerehabilitation to daily-life mobility. These results will help to develop a more effective home-based balance telerehabilitation and virtual assessment that can be used remotely in people with balance impairments.Trial registrationThis trial was prospectively registered on ClinicalTrials.gov (NCT05680597).

Wearable Devices for Gait Measurement - A Case for Textile-Based Devices

Wearable devices for gait measurement are devices worn on the body to measure the gait of the wearers. During gait measurement, several parameters are measured and the choice of parameters is influenced by the application and by extension the gait index. Two approaches have been adopted in this research. One is the provision of an overview of wearable devices for gait measurement with a bias towards textile-based “soft” smart wearable systems using information from varied academic sources and databases. The second approach is to map out key scientific research trends within the wearable device classes using the Web of Science database. The focus is to make a case for textile-based gait measurement devices and systems while exploring the key determinants of wearable gait sensor placements and application efficiency. These soft smart wearable systems describe flexible material sensor-based systems which have their sensing mechanisms based on material deformation after being subjected to stress or pressure. This study could therefore serve as an apt reference for the development of soft smart wearable gait measurement systems as it throws light on the various soft wearable gait measurement applications, the bottlenecks in soft wearable device design, opportunities for developing new devices and the merit that soft gait analysis systems possess over their hard gait measurement counterparts.

Gait Analysis in Idiopathic Normal Pressure Hydrocephalus: A Meta-Analysis.

Gait analysis objectively quantifies gait impairment in idiopathic normal pressure hydrocephalus (iNPH), may improve diagnosis and evaluation for surgical candidacy. This meta-analysis aims to understand which objective gait parameters improve after tap-test (TT) and CSF shunt surgery (CSS), also comparing responders (R) with non-responders (NR) and to assess if gait restores within the range of healthy controls after procedures. Studies enrolling iNPH with at least one instrumented gait measure were selected. Three time points of gait assessment were defined: PRE, POST-TT, and POST-CSS. Gait velocity, cadence, step length, stride length, and double limb support time were evaluated. Patients were categorized based on responsiveness to CSF diversion procedures. Seventeen studies including 527 patients were selected. iNPH improved significantly in almost all gait parameters POST-TT, and to a greater extent POST-CSS. Gait parameters consistently discriminated iNPH from healthy controls. Despite the aforementioned improvements, iNPH's gait did not completely normalize after CSF diversion procedures. Meta-regression analysis also revealed that TT's effect on gait velocity plateaus after 24-48 hr and returns to baseline in 90-100 hr. Gait analysis is a reliable quantitative instrument to assess gait impairment in iNPH, demarking a net differentiation from healthy controls, according to the notion that the iNPH CSF dynamic alteration also leads to an irreversible damage. Specific gait parameters improve among TT-R, providing an opportunity to select patients that will respond to CSS. Future studies validating a standardized reporting method including criteria of responsiveness, specific gait parameters, and timeframe of assessment are needed.

Effect of total knee arthroplasty on contralateral knee: A prospective comparative gait analysis of non-operated legs in the Indian population

IntroductionBiomechanics plays a crucial function in osteoarthritis. Changes in the biomechanical parameters of the contralateral knee following total knee arthroplasty (TKA) may result in pain in the contralateral knee. The objective of this study was to examine preoperative and postoperative gait measurements on the contralateral leg following a TKA for a variety of gait measures at a self-selected normal gait pace in a similar speed population. MethodThere were 11 patients included in the study, and their average age was 68 (7 females and 4 males). Gait analysis was performed at a sampling frequency of 120 Hz using nine cameras Qualisys motion capture systems (Qualisys AB, Sweden). To process the kinematic data, Visual 3D C-Motion Software was used. ResultsAnkle plantar flexion (0.01), knee abduction during the terminal stance (0.002), and knee adduction during the initial swing (0.01) all showed a significant difference. In spatiotemporal data, walking speed (0.01), stance time (0.01), step length (0.005), and stride length (0.001) all showed significant differences. There were significant differences in knee flexion-extension (0.04) values. ConclusionA change in the contralateral knee's biomechanics as a result of TKA is strongly suggested by significant alterations in the knee's stance phase, joint angle, and MAP. The research may help to modify the stride of the contralateral leg to decrease the advancement of osteoarthritis.

The variability of dual-task walking parameters using in-shoe inertial sensors in nonconcussed individuals: A randomized within-subject repeated measures design.

There is a need for high utility and portability, and cost-effective technologies that are suitable for assessing dual-task gait after experiencing a concussion. Current technologies utilized such as 3D motion capture and force plates are too complex and expensive for most practitioners. The aim of this study was to quantify the variability of dual-task walking gait parameters using in-shoe inertial sensors in nonconcussed individuals. This was a randomized within-subject repeated measures design conducted within a sports laboratory. Twenty healthy, uninjured, nonconcussed participants were recruited for this study. Gait variables of interest were measured across three 2-min continuous walking protocols (12 m, 30 m, 1 min out and back) while performing a cognitive task of counting backward in sevens from a randomly generated number between 300 and 500. Testing was completed over three occasions separated by 7 days, for a total of nine walking trials. Participants completed the testing protocols in a randomized, individual order. The primary outcome was to determine the variability of dual-task walking gait parameters using in-shoe inertial sensors in nonconcussed individuals across three protocols. Three to four participants were allocated to each randomized protocol order. Regarding the absolute consistency (coefficient of variation [CV]) between testing occasions, no gait measure was found to have variability above 6.5%. Relative consistency (intraclass correlation coefficient [ICC]) was acceptable (>0.70) in 95% of the variables of interest, with only three variables < 0.70. Similar variability was found across the three testing protocols. In-shoe inertial sensors provide a viable option for monitoring gait parameters. This technology is also reliable across different testing distances, thus offering various testing options for practitioners. Further research needs to be conducted to examine the variability with concussed subjects.

Combined Reactive and Volitional Step Training Improves Balance Recovery and Stepping Reaction Time in People With Parkinson’s Disease: A Randomised Controlled Trial

Background Falls are frequent and devastating events for people with Parkinson’s disease (PD). Here, we investigated whether laboratory-based reactive step training combined with home-based volitional step training was effective in improving balance recovery and stepping ability in people with PD. Methods Forty-four people with idiopathic PD were randomized into intervention or control groups. Intervention participants performed unsupervised volitional step training using home-based exergames (80+ minutes/week) for 12 weeks and attended reactive step training sessions in which they were exposed to slip and trip perturbations at 4 and 8 weeks. Control participants continued their usual activities. Primary outcomes were balance recovery following an induced-trip/slip and choice stepping reaction time (CSRT) at the 12-week reassessment. Secondary outcomes comprised sensorimotor, balance, cognitive, psychological, complex stepping (inhibitory CSRT and Stroop Stepping Test [SST]), gait measures, and falls experienced in everyday life. Results At reassessment, the intervention group had significantly fewer total laboratory-induced falls and faster CSRT compared to the control group (P < .05). The intervention group also had significantly faster inhibitory CSRT and SST movement times and made fewer mistakes in the SST (P < .05). There were no significant differences in the rate of every day falls or other secondary outcome measures between the groups. Conclusion Combined volitional and reactive step training improved balance recovery from an induced-perturbation, voluntary stepping time, and stepping accuracy in cognitively challenging tests in people with PD. Further research is required to determine whether such combined step training can prevent daily-life falls in this population.

Gait Measurement System Utilizing Missing Point Clouds Caused by Feet With Apple LiDAR Camera

Gait Measurement System Utilizing Missing Point Clouds Caused by Feet With Apple LiDAR Camera

Capturing Measures That Matter: The Potential Value of Digital Measures of Physical Behavior for Alzheimer's Disease Drug Development.

Alzheimer's disease (AD) is a devastating neurodegenerative disease and the primary cause of dementia worldwide. Despite the magnitude of AD's impact on patients, caregivers, and society, nearly all AD clinical trials fail. A potential contributor to this high rate of failure is that established clinical outcome assessments fail to capture subtle clinical changes, entail high burden for patients and their caregivers, and ineffectively address the aspects of health deemed important by patients and their caregivers. AD progression is associated with widespread changes in physical behavior that have impacts on the ability to function independently, which is a meaningful aspect of health for patients with AD and important for diagnosis. However, established assessments of functional independence remain underutilized in AD clinical trials and are limited by subjective biases and ceiling effects. Digital measures of real-world physical behavior assessed passively, continuously, and remotely using digital health technologies have the potential to address some of these limitations and to capture aspects of functional independence in patients with AD. In particular, measures of real-world gait, physical activity, and life-space mobility captured with wearable sensors may offer value. Additional research is needed to understand the validity, feasibility, and acceptability of these measures in AD clinical research.

Floor-to-Stand Performance Among People Following Stroke.

Studies have examined floor-to-stand performance in varied adult populations both quantitatively and qualitatively. Despite an elevated risk of falls and inability to independently return to stand after a fall, few have examined the ability to stand from the floor in patients recovering from stroke. There were 2 objectives of the study: to identify the relationships between floor-to-stand performance using a timed supine-to-stand test (TSS) and physical performance measures of gait, balance, and balance confidence among persons in the subacute phase after stroke; and to analyze descriptive strategies used in the completion of the TSS. A cross-sectional design was implemented. Fifty-eight adults (mean age = 59.2 [standard deviation (SD) = 13.9] years; 34 [58.6%] men) who were in the subacute phase after ischemic or hemorrhagic stroke and who could stand from the floor with no more than supervision completed the TSS and physical performance assessments. The median time to complete the TSS in our sample was 13.0 (interquartile range = 15.5) seconds. TSS time was significantly correlated with physical performance tests, including the Timed "Up & Go" Test (ρ = 0.70), gait speed (ρ = -0.67), Dynamic Gait Index (ρ = -0.52), and Activities-Specific Balance Confidence Scale (ρ = -0.43). Thirty-two percent of the variance in TSS time was attributed to Timed "Up & Go" Test time and the use of the quadruped position to transition to standing. Participants who used a gait device were more likely to use a chair during rise to stand. The TSS demonstrates concurrent validity with physical performance measures. Findings serve to improve functional mobility examination after stroke and to formulate effective treatment interventions to improve floor-to-stand performance.

P09.06.B GAIT CHARACTERISTICS OF PROGRESSIVE DISEASE IN HIGH GRADE GLIOMA: THE BRAINWEAR STUDY

Abstract BACKGROUND Walking is a useful measure of overall health and walking speed has well-documented predictive value for health-related outcomes such as mortality, quality of life, physical and cognitive functional decline in older people. Wearable technology-based gait analysis is emerging as a powerful tool to detect early disease and monitor progression in areas such as Parkinson’s disease. We present an exploratory analysis of gait characteristics at the time of progressive disease from patients with high grade glioma (HGG) participating in the BrainWear Study which evaluates the use of free-living accelerometers in patients with brain tumours. MATERIAL AND METHODS All agreed to wear a wrist-worn Axivity AX3 triaxial accelerometer changed at 14-day intervals. Raw accelerometer data was processed using the UKBiobank OxWearables stepcount model v2.1.2 for Python and inclusion of high-quality wear time selected as ≥72 hours of data in a 7-day data collection and data in each 1-hour period of a 24-hour cycle over multiple days. 12 gait measures were characterised including total daily steps, cadence, cadence peak and minutes walking per day. We analysed variation in gait measures by patient demographics and MRI result. Wilcoxin-signed rank test was used to compare participant gait measures at timepoints of stable disease (SD) or progressive disease (PD). Mixed-effects models were used to evaluate longitudinal changes in gait measures. RESULTS 17 HGG patients (6 female; 11 male) provided 4654 days of accelerometer data across 49 MRI Head scan RESULTS , 32 labelled as PD and 17 as SD. Median age was 62 years (32-79) and mean study participation 273 days (41-550). 8 patients provided accelerometer data at timepoints of both PD and SD allowing for paired analysis. There were no differences in 12 gait measures between age (&amp;lt;60 and &amp;gt;60 years) and gender. In the 6 weeks surrounding an MRI scan, patients with PD walked on average 1856 steps less per day than those with SD, and spent 22 minutes less walking (p=0.0403). Peak 1-minute cadence was 77 steps/min in patients with SD versus 67 steps/min with PD. CONCLUSION The complexity of HGG treatment, recovery and survivorship creates a need for novel monitoring approaches. Wearable accelerometry is feasible and acceptable and evaluating gait measures captures objective evidence of significant differences in patients with PD versus SD. Physical activity measures can guide clinicians in optimising quality of life and may act as an alert system prior to events such as disease progression.

Pay attention: you can fall! The Mini-BESTest scale and the turning duration of the TUG test provide valid balance measures in neurological patients: a prospective study with falls as the balance criterion.

Balance, i.e., the ability not to fall, is often poor in neurological patients and this impairment increases their risk of falling. The Mini-Balance Evaluation System Test (Mini-BESTest), a rating scale, the Timed Up and Go (TUG) test, and gait measures are commonly used to quantify balance. This study assesses the criterion validity of these measures as balance measures. The probability of being a faller within nine months was used as the balance criterion. The Mini-BESTest, TUG (instrumented with inertial sensors), and walking test were administered before and after inpatient rehabilitation. Multiple and LASSO logistic regressions were used for the analysis. The diagnostic accuracy of the model was assessed with the area under the curve (AUC) of the receiver operating characteristic curve. Mobility measure validity was compared with the Akaike Information Criterion (AIC). Two hundred and fourteen neurological patients (stroke, peripheral neuropathy, or parkinsonism) were recruited. In total, 82 patients fell at least once in the nine-month follow-up. The Mini-BESTest (AUC = 0.69; 95%CI: 0.62-0.76), the duration of the TUG turning phase (AUC = 0.69; 0.62-0.76), and other TUG measures were significant faller predictors in regression models. However, only the turning duration (AIC = 274.0) and Mini-BESTest (AIC = 276.1) substantially improved the prediction of a baseline model, which only included fall risk factors from the medical history (AIC = 281.7). The LASSO procedure selected gender, disease chronicity, urinary incontinence, the Mini-BESTest, and turning duration as optimal faller predictors. The TUG turning duration and the Mini-BESTest predict the chance of being a faller. Their criterion validity as balance measures in neurological patients is substantial.

Assessing spring-mass similarity in elite and recreational runners.

The dynamic complexity and individualization of running biomechanics has challenged the development of objective and comparative gait measures. Here, we present and explore several novel biomechanical metrics for running that are informed by a canonical inter-species gait template-the spring-mass model. The measures assess running mechanics systemically against the template via quantifying characteristics of a runner's kinetics relative to the energy-conserving elastic system-i.e., their "spring-mass similarity". Applying these metrics in a retrospective cohort investigation, we studied the overground kinetics of two heterogenous populations of runners in two footwear conditions: elite and recreational athletes in shod and barefoot conditions. Across all measures and within foot strike types, the elite runners exhibited mechanics that were more similar to those of the ideally elastic spring-mass template. The elite runners had more symmetric bounces, less discrepancy (i.e., greater coordination) between horizontal and vertical kinetic changes, and better fit to a spring-mass vertical ground reaction force time series. Barefoot running elicited greater kinetic coordination in the recreational runners. At a faster speed, the elites further improved their similarity to the template. Overall, the more economical elite group exhibited greater likeness to the linearly elastic, energy-conserving spring-mass system than their recreational counterparts. This study introduces novel biomechanical measures related to performance in distance running. More broadly, it provides new, approachable metrics for systemic quantification of gait biomechanics in runners across all demographics. These metrics may be applied to assess a runner's global biomechanical response to a variety of interventions, including training adaptations, rehabilitation programs, and footwear conditions.

Exploring mobility dysfunction in people with and without impaired cognition in Parkinson disease

IntroductionThe relationship between mobility and cognition has been studied in the aging population and associations have been also reported in people with Parkinson's disease (PD). ObjectiveTo compare different aspects of gait and balance between individuals with PD who have normal cognition and those with impaired cognition, using both clinical and instrumented measures. MethodsOne-hundred forty-three participants with PD were divided into two groups: 1) normal cognition (n = 71) and 2) impaired cognition (n = 72) based on the Montreal Cognitive Assessment (MoCA) cut-off. Groups were compared using instrumented and clinical measures of gait and balance in the following domains: Sensory Orientation, Anticipatory Postural Adjustments, Automatic Postural Responses and Dynamic Balance for Gait. Instrumented measures were obtained via wearable sensors while performing eight different motor tasks and clinical measures were obtained with the Mini-BESTest. ResultsThe total Mini-BESTest score was not different between groups. However, the Dynamic Gait domain was worse in individuals with impaired cognition. Among the instrumented measures across domains, all significant group differences were in the Dynamic Gait domain, specifically, dual-task gait speed, dual-task stride length, stance time, and turn velocity. ConclusionsDynamic balance during gait was more impaired in people with PD who had abnormal cognition than those with normal cognition, for both clinical and instrumented measures. All other balance domains did not differ between groups, for both instrumented and clinical measures.

A Comparison of Walking Behavior during the Instrumented TUG and Habitual Gait.

The timed up and go test (TUG) is a common clinical functional balance test often used to complement findings on sensorimotor changes due to aging or sensory/motor dysfunction. The instrumented TUG can be used to obtain objective postural and gait measures that are more sensitive to mobility changes. We investigated whether gait and body coordination during TUG is representative of walking. We examined the walking phase of the TUG and compared gait metrics (stride duration and length, walking speed, and step frequency) and head/trunk accelerations to normal walking. The latter is a key aspect of postural control and can also reveal changes in sensory and motor function. Forty participants were recruited into three groups: young adults, older adults, and older adults with visual impairment. All performed the TUG and a short walking task wearing ultra-lightweight wireless IMUs on the head, chest, and right ankle. Gait and head/trunk acceleration metrics were comparable across tasks. Further, stride length and walking speed were correlated with the participants' age. Those with visual impairment walked significantly slower than sighted older adults. We suggest that the TUG can be a valuable tool for examining gait and stability during walking without the added time or space constraints.

Gait analysis algorithm for lower limb rehabilitation robot applications

Abstract. When patients with lower limb dyskinesia use robots for rehabilitation training, gait parameters are of great significance for disease diagnosis and rehabilitation evaluation. Gait measurement is usually carried out by using optical motion capture systems, pressure plates and so on. However, it is difficult to apply these systems to lower limb rehabilitation robots due to their high price, limited scope and wearing requirements. At the same time, most of the current applications in robots focus on the basic gait parameters (such as step length and step speed) for robot control or user intention recognition. Therefore, this paper proposes an online gait analysis algorithm for lower limb rehabilitation robots, which uses a lidar sensor as the gait data acquisition sensor. The device is installed on the lower limb rehabilitation robot, which not only avoids the problems of decline in the detection accuracy and failure of leg tracking caused by lidar placement on the ground, but it also calculates seven gait parameters, such as step length, stride length, gait cycle and stance time, with high precision in real time. At the same time, the walking track of the patient may not be straight, and the lidar coordinate system is also changed due to the movement of the lower limb rehabilitation robot when the patient moves forward. In order to overcome this situation, a spatial parameter-splicing algorithm based on a time series is proposed to effectively reduce the error impact on gait spatiotemporal parameters. The experimental results show that the gait analysis algorithm proposed in this paper can measure the gait parameters effectively and accurately. Except for the swing time and double support time, which are calculated with large relative errors due to their small values, the relative errors of the remaining gait parameters are kept below 8 %, meeting the requirements of clinical applications.

The effect of high-frequency repetitive transcranial magnetic stimulation on motor recovery and gait parameters in chronic incomplete spinal cord injury: A randomized-controlled study.

This study aims to examine the effect of high-frequency repetitive transcranial magnetic stimulation (rTMS) on gait parameters and lower extremity motor recovery in a more specific sample of individuals with chronic and traumatic incomplete spinal cord injury (iSCI). This double-blind, sham-controlled, randomized study included a total of 28 individuals (20 males, 8 females; mean age: 35.7±12.1 years; range, 18 to 45 years) with chronic (>1 year) traumatic iSCI. The participants were randomly allocated to either sham rTMS group (n=14) or real rTMS group (n=14). We compared the groups based on the lower extremity motor scores (LEMS), the temporal-spatial gait measurements using three-dimensional gait analysis, the Walking Index for SCI-II (WISCI-II), and 10-m walking test at baseline, three weeks (post-treatment) and five weeks (follow-up) after the treatment. The real rTMS group revealed a significant improvement in walking speed, LEMS score, and 10-m walking test after the treatment compared to baseline (p=0.001, p=0.002, and p=0.023, respectively). Changes in the LEMS score were significantly increased in the real rTMS group compared to the sham group at both three and five weeks (p=0.001 and p=0.001, respectively). No significant difference was observed in the other variables between the groups (p>0.05). Our study findings support the therapeutic effectiveness of rTMS on motor recovery in chronic iSCI. The rTMS can be used as an adjuvant therapy to conventional physiotherapy in the rehabilitation of patients with iSCI.