Validity and Reproducibility of Inertial Physilog Sensors for Spatiotemporal Gait Analysis in Patients With Stroke

Psychometric properties of wearable technologies to assess post-stroke gait parameters: A systematic review

BACKGROUND

Wearable technologies using inertial sensors are an alternative for gait assessment. However, their psychometric properties in evaluating post-stroke patients are still being determined. This systematic review aimed to evaluate the psychometric properties of wearable technologies used to assess post-stroke gait and analyze their reliability and measurement error. The review also investigated which wearable technologies have been used to assess angular changes in post-stroke gait.

METHODS

The present review included studies in English with no publication date restrictions that evaluated the psychometric properties (e.g., validity, reliability, responsiveness, and measurement error) of wearable technologies used to assess post-stroke gait. Searches were conducted from February to March 2023 in the following databases: Cochrane Central Registry of Controlled Trials (CENTRAL), Medline/PubMed, EMBASE Ovid, CINAHL EBSCO, PsycINFO Ovid, IEEE Xplore Digital Library (IEEE), and Physiotherapy Evidence Database (PEDro); the gray literature was also verified. The Consensus-based Standards for the Selection of Health Measurement Instruments (COSMIN) risk-of-bias tool was used to assess the quality of the studies that analyzed reliability and measurement error.

RESULTS

Forty-two studies investigating validity (37 studies), reliability (16 studies), and measurement error (6 studies) of wearable technologies were included. Devices presented good reliability in measuring gait speed and step count; however, the quality of the evidence supporting this was low. The evidence of measurement error in step counts was indeterminate. Moreover, only two studies obtained angular results using wearable technology.

SIGNIFICANCE

Wearable technologies have demonstrated reliability in analyzing gait parameters (gait speed and step count) among post-stroke patients. However, higher-quality studies should be conducted to improve the quality of evidence and to address the measurement error assessment. Also, few studies used wearable technology to analyze angular changes during post-stroke gait.

Comparability between wearable inertial sensors and an electronic walkway for spatiotemporal and relative phase data in young children aged 6-11 years

BACKGROUND

Approaches to gait analysis are evolving rapidly and now include a wide range of options: from e-patches to video platforms to wearable inertial measurement unit systems. Newer options for gait analysis are generally more inclusive for the assessment of children, more cost effective and easier to administer. However, there is limited data on the comparability of newer systems with more established traditional approaches in young children.

RESEARCH QUESTION

To determine comparability between the Physilog®5 wearable inertial sensor and GAITRite® electronic walkway for spatiotemporal (stride length, time and velocity, cadence) and relative phase (double support time, stance, swing, loading, foot flat and push off) data in young children.

METHODS

A total 34 typically developing participants (41% female) aged 6-11 years old median age 8.99 years old (interquartile range 2.83) were assessed walking at self-selected speed over the GAITRite® electronic walkway while concurrently wearing shoe-attached Physilog®5 IMU sensors. Level of agreement was analysed by Lin's concordance correlation coefficient (CCC), Bland-Altman plots and 95% limit of agreement. Systematic bias was assessed using 95% confidence interval of the mean difference.

RESULTS

Excellent to almost perfect agreement was observed between systems for spatiotemporal metrics: cadence (CCC=0.996), stride length (CCC=0.993), stride time (CCC=0.996), stride velocity (CCC=0.988). The relative phase metrics adjusted for stride velocity showed improved comparability when compared to the unadjusted metrics: swing adjusted (adj) (CCC=0.635); stance adj (CCC: 0.879); loading adj: (CCC=0.626).

SIGNIFICANCE

Spatiotemporal metrics are highly compatible across GAITRite® electronic walkway and Physilog®5 IMU systems in young children. Relative phase metrics were somewhat compatible between systems when adjusted for stride velocity.

Reliability of Obstacle-Crossing Parameters during Overground Walking in Young Adults

We aimed to evaluate the intra-session relative and absolute reliability of obstacle-crossing parameters during overground walking in young adults, and to determine the number of trials required to ensure reliable assessment. We analysed data from 43 young male adults who were instructed to walk at a self-selected velocity on a pathway and to step over an obstacle (height = 15 cm; width = 80 cm, thickness = 2 cm) three times. Spatial-temporal gait parameters of the approaching and crossing phases (i.e., before and after the obstacle) and obstacle clearance parameters (i.e., vertical and horizontal distance between the foot and the obstacle during crossing) were computed using a three-dimensional motion analysis system. Intraclass correlation coefficients were used to compute the relative reliability, while standard error of measurement and minimal detectable change were used to assess the absolute reliability for all possible combinations between trials. Results showed that most spatial-temporal gait parameters and obstacle clearance parameters are reliable using the average of three trials. However, the mean of the second and third trials ensures the best relative and absolute reliabilities of most obstacle-crossing parameters. Further works are needed to generalize these results in more realistic conditions and in other populations.

Interactive boxing-cycling on frailty and activity limitations in frail and prefrail older adults: A randomized controlled trial

BACKGROUND

Frailty is common among older adults, often associated with activity limitations during physical and walking tasks. The interactive boxing-cycling combination has the potential to be an innovative and efficient training method, and our hypothesis was that interactive boxing-cycling would be superior to stationary cycling in improving frailty and activity limitations in frail and prefrail older adults.

OBJECTIVE

To examine the impact of interactive boxing-cycling on frailty and activity limitations in frail and prefrail older adults compared to stationary cycling.

MATERIALS AND METHODS

A single-blinded randomized controlled trial. Forty-five participants who met at least one frailty phenotype criteria were randomly assigned to receive either interactive boxing-cycling (n = 23) or stationary-cycling (n = 22) for 36 sessions over 12 weeks. The interactive boxing-cycling was performed on a cycle boxer bike with an interactive boxing panel fixed in front of the bike. The primary outcomes were frailty status, including score and phenotypes. Secondary outcomes included activity limitations during physical and walking tasks. The pre- and post-intervention data of both groups were analyzed using a repeated measures two-way ANOVA.

RESULTS

Both types of cycling significantly improved frailty scores (p<0.001). Interactive boxing-cycling was more effective than stationary cycling in reversing the frailty phenotype of muscle weakness (p = 0.03, odds ratio 9.19) and demonstrated greater improvements than stationary cycling in arm curl (p = 0.002, η2=0.20), functional reach (p = 0.001, η2=0.22), and grip strength (p = 0.02, η2=0.12) tests. Additionally, interactive boxing-cycling exhibited a greater effect on gait speed (p = 0.02, η2=0.13) and gait variability (p = 0.01, η2=0.14) during dual-task walking.

CONCLUSION

In frail and prefrail older adults, interactive boxing-cycling effectively improves frailty but is not superior to stationary cycling. However, it is more effective at improving certain activity limitations.

REGISTRATION NUMBER

TCTR20220328001.

Risk of using smartphones while walking for digital natives in realistic environments: Effects of cognitive-motor interference

The effect of using smartphones while walking on the cognitive and physical abilities of the "digital native" generation, i.e., individuals who have grown up in a digital media-centric environment, remains poorly understood. This study evaluated the effects of cognitive-motor interference on the use of smartphones while walking in children and young adults. The study involved 50 individuals from the digital age generation, including 24 children and 26 young adults. The study encompassed three experimental conditions, in which participants were instructed to traverse a distance of 60 m. The initial condition functioned as a control, wherein the participants walked without supplementary stimuli. In the second condition, the participants were provided with explicit instructions to grasp the smartphone device and position it in front of their chest by using both hands. This manipulation introduced a postural component into the experimental setup. The third condition required participants to be ambulatory while concurrently engaging in a cognitive task, namely, participating in a game that necessitated focused attention. Gait parameters were obtained by using inertial measurement unit sensors. Subsequently, the acquired gait characteristics were converted into dual-task costs (DTC). In the cognitive condition, children exhibited significantly greater DTC values for gait speed (76%), stride length (79%), stride time (102%), and stride length coefficient of variation (CV) than the young adults (p < 0.025). Moreover, as shown by the increased CV, a significant association exists between poor performance in smartphone games among children and increased variability in stride length. In children, the DTC of stride time CV decreased as smartphone game scores increased (R2 = 16.5%), and the DTC of stride length CV decreased more markedly as smartphone game scores increased (R2 = 28.2%). In conclusion, children are at a higher risk of pedestrian accidents when using smartphones while walking compared to young adults.

Accuracy, concurrent validity, and test-retest reliability of pressure-based insoles for gait measurement in chronic stroke patients

Introduction

Wearables are potentially valuable tools for understanding mobility behavior in individuals with neurological disorders and how it changes depending on health status, such as after rehabilitation. However, the accurate detection of gait events, which are crucial for the evaluation of gait performance and quality, is challenging due to highly individual-specific patterns that also vary greatly in movement and speed, especially after stroke. Therefore, the purpose of this study was to assess the accuracy, concurrent validity, and test-retest reliability of a commercially available insole system in the detection of gait events and the calculation of stance duration in individuals with chronic stroke.

Methods

Pressure insole data were collected from 17 individuals with chronic stroke during two measurement blocks, each comprising three 10-min walking tests conducted in a clinical setting. The gait assessments were recorded with a video camera that served as a ground truth, and pressure insoles as an experimental system. We compared the number of gait events and stance durations between systems.

Results and discussion

Over all 3,820 gait events, 90.86% were correctly identified by the insole system. Recall values ranged from 0.994 to 1, with a precision of 1 for all measurements. The F1 score ranged from 0.997 to 1. Excellent absolute agreement (Intraclass correlation coefficient, ICC = 0.874) was observed for the calculation of the stance duration, with a slightly longer stance duration recorded by the insole system (difference of -0.01 s). Bland-Altmann analysis indicated limits of agreement of 0.33 s that were robust to changes in walking speed. This consistency makes the system well-suited for individuals post-stroke. The test-retest reliability between measurement timepoints T1 and T2 was excellent (ICC = 0.928). The mean difference in stance duration between T1 and T2 was 0.03 s. We conclude that the insole system is valid for use in a clinical setting to quantitatively assess continuous walking in individuals with stroke.

Reliability of patient-specific gait profiles with inertial measurement units during the 2-min walk test in incomplete spinal cord injury

Most established clinical walking tests assess specific aspects of movement function (velocity, endurance, etc.) but are generally unable to determine specific biomechanical or neurological deficits that limit an individual's ability to walk. Recently, inertial measurement units (IMU) have been used to collect objective kinematic data for gait analysis and could be a valuable extension for clinical assessments (e.g., functional walking measures). This study assesses the reliability of an IMU-based overground gait analysis during the 2-min walk test (2mWT) in individuals with spinal cord injury (SCI). Furthermore, the study elaborates on the capability of IMUs to distinguish between different gait characteristics in individuals with SCI. Twenty-six individuals (aged 22-79) with acute or chronic SCI (AIS: C and D) completed the 2mWT with IMUs attached above each ankle on 2 test days, separated by 1 to 7 days. The IMU-based gait analysis showed good to excellent test-retest reliability (ICC: 0.77-0.99) for all gait parameters. Gait profiles remained stable between two measurements. Sensor-based gait profiling was able to reveal patient-specific gait impairments even in individuals with the same walking performance in the 2mWT. IMUs are a valuable add-on to clinical gait assessments and deliver reliable information on detailed gait pathologies in individuals with SCI.Trial registration: NCT04555759.

Can inertial measurement unit sensors evaluate foot kinematics in drop foot patients using functional electrical stimulation?

The accuracy of inertial measurement units (IMUs) in measuring foot motion in the sagittal plane has been previously compared to motion capture systems for healthy and impaired participants. Studies analyzing the accuracy of IMUs in measuring foot motion in the frontal plane are lacking. Drop foot patients use functional electrical stimulation (FES) to improve walking and reduce the risk of tripping and falling by improving foot dorsiflexion and inversion-eversion. Therefore, this study aims to evaluate if IMUs can estimate foot angles in the frontal and sagittal planes to help understand the effects of FES on drop foot patients in clinical settings. Two Gait Up sensors were used to estimate foot dorsi-plantar flexion and inversion-eversion angles in 13 unimpaired participants and 9 participants affected by drop foot while walking 6 m in a straight line. Unimpaired participants were asked to walk normally at three self-selected speeds and to simulate drop foot. Impaired participants walked with and without FES assistance. Foot angles estimated by the IMUs were compared with those measured from a motion capture system using curve RMSE and Bland Altman limits of agreement. Between participant groups, overall errors of 7.95° ± 3.98°, -1.12° ± 4.20°, and 1.38° ± 5.05° were obtained for the dorsi-plantar flexion range of motion, dorsi-plantar flexion at heel strike, and inversion-eversion at heel strike, respectively. The between-system comparison of their ability to detect dorsi-plantar flexion and inversion-eversion differences associated with FES use on drop foot patients provided limits of agreement too large for IMUs to be able to accurately detect the changes in foot kinematics following FES intervention. To the best of the authors' knowledge, this is the first study to evaluate IMU accuracy in the estimation of foot inversion-eversion and analyze the potential of using IMUs in clinical settings to assess gait for drop foot patients and evaluate the effects of FES. From the results, it can be concluded that IMUs do not currently represent an alternative to motion capture to evaluate foot kinematics in drop foot patients using FES.

Measurement Accuracy of the HTC VIVE Tracker 3.0 Compared to Vicon System for Generating Valid Positional Feedback in Virtual Reality

For realistic and reliable full-body visualization in virtual reality, the HTC VIVE Tracker could be an alternative to highly complex and cost- and effort-intensive motion capture systems such as Vicon. Due to its lighter weight and smaller dimensions, the latest generation of trackers is proving to be very promising for capturing human movements. The aim of this study was to investigate the accuracy of the HTC VIVE Tracker 3.0 compared to the gold-standard Vicon for different arrangements of the base stations and various velocities during an athletic movement. Therefore, the position data from three trackers attached to the hip, knee and ankle of one sporty participant were recorded while riding a bicycle ergometer at different pedaling frequencies and different base station arrangements. As parameters for the measurement accuracy, the trajectories of the linear motion of the knee and the circular motion of the ankle were compared between VIVE and Vicon by calculating the spatial distance from the raw data at each point in time. Both the pedaling frequency and the arrangement of the base stations significantly affected the measurement accuracy, with the lowest pedaling frequency of 80 rpm and the rectangular arrangement recommended by the manufacturer showing the smallest spatial differences of 10.4 mm ± 4.5 mm at the knee and 11.3 mm ± 5.1 mm at the ankle. As the pedaling frequency increased gradually (120 rpm and 160 rpm), the measurement accuracy of the trackers per step decreased less at the knee (approximately 5 mm) than at the ankle (approximately 10 mm). In conclusion, the measurement accuracy for various athletic skills was high enough to enable the visualization of body limbs or the entire body using inverse kinematics in VR on the one hand and, on the other hand, to provide initial insights into the quality of certain techniques at lower speeds in sports science research. However, the VIVE trackers are not suitable for exact biomechanical analyses.

The instrumented single leg stance test detects early balance impairment in people with multiple sclerosis

Balance impairment is frequent in people with multiple sclerosis (pwMS) and affects risk of falls and quality of life. By using inertial measurement units (IMUs) on the Single Leg Stance Test (SLS) we aimed to discriminate healthy controls (HC) from pwMS and detect differences in balance endurance and quality. Thirdly, we wanted to test the correlation between instrumented SLS parameters and self-reported measures of gait and balance. Fifty-five pwMS with mild (EDSS<4) and moderate disability (EDSS≥4) and 20 HC performed the SLS with 3 IMUs placed on the feet and sacrum and filled the Twelve Item Multiple Sclerosis Walking Scale (MSWS-12) questionnaire. A linear mixed model was used to compare differences in the automated balance measures. Balance duration was significantly longer in HC compared to pwMS (p < 0.001) and between the two disability groups (p < 0.001). Instrumented measures identified that trunk stability (normalized mediolateral and antero-posterior center of mass stability) had the strongest association with disability (R2 marginal 0.30, p < 0.001) and correlated well with MSWS-12 (R = 0.650, p < 0.001). PwMS tended to overestimate own balance compared to measured balance duration. The use of both self-reported and objective assessments from IMUs can secure the follow-up of balance in pwMS.

Examining gender differences in gait parameters between non-smoker and smoker participants

Smoking is one of the predictors of decreased cardiopulmonary endurance. Gait disturbance may be due to many reasons, including cardiovascular endurance. This study aimed to determine differences in gait parameters between non-smoker and smoker participants. A cross-sectional design was employed, involving thirty non-smokers and thirty-seven smokers as participants. Detailed interviews were conducted to gather information on smoking habits, status, and history. Gait parameters were measured using a high-quality 3D accelerometer, 3D gyroscope, and barometric pressure sensors (Physilog4 from GaitUp). Anthropometric characteristics were described, and mean values with standard deviations (SD) were calculated. An independent two-tailed t-test was conducted to compare gait parameters between non-smokers and smokers, with statistical significance set at p<0.05. The analysis revealed significant differences in various gait parameters between non-smokers and smokers. Specifically, significant differences were found in cadence (t=9.95, p=0.001), stride length (t=6.85, p=0.001), stride velocity (t=-6.58, p=0.001), stance (t=2.02, p=0.001), swing (t=3.46, p=0.001), foot flat (t=-8.94, p=0.001), pushing (t=3.53, p=0.001), and double support (t=-13.35, p=0.001). However, no significant difference was found between non-smokers and smokers in the loading phase (t=-1.57, p= 0.121). There were significant differences in general and temporal gait parameters between smokers and non-smokers. Gait parameters provide valuable insights for evaluating functional performance and providing objective and quantitative data to assess gait disorders. Future studies should include longitudinal studies with large sample sizes to explore the effects of potential confounders on gait parameters.

Is foot clearance influenced by different types of dual task in once-only faller community-dwelling older adults?

BACKGROUND

Tripping is one of the main causes of falls in older adults and has an important association with minimum toe clearance (MTC). MTC variability while performing alternating (ADT) or concurrent (CDT) dual-task activities may be a useful gait parameter to differentiate once-only fallers from non-faller older adults.

RESEARCH QUESTION

Is the MTC variability influenced by ADT and CDT in once-only faller community-dwelling older adults?

METHODS

Twenty-two community-dwelling older adults with a self-report of up to one fall in the last 12 months were allocated to the fallers group and 38 to the non-fallers group. Gait data were collected by two foot-worn inertial sensors (Physilog® 5, GaitUp, Lausanne, Switzerland). MTC mean magnitude and variability, as well as the stride-to-stride variability, stride time and length, lower limb peak angular velocity, and foot forward linear speed at the MTC instant, were calculated across approximately 50 gait cycles for each participant and condition using the GaitUp Analyzer software (GaitUp, Lausanne, Switzerland). The statistical analyzes were performed in the Statistical Package for the Social Sciences (SPSS), v.22.0, using generalized mixed linear models, adopting an alpha of 5%.

RESULTS AND SIGNIFICANCE

No interaction effect was observed; however, faller participants reduced the MTC variability (standard deviation) [(mean difference, MD = -0.099 cm; confidence interval, 95%CI = -0.183 to -0.015)], regardless of the condition. CDT compared to a single task (only gait) reduced the mean magnitude of the foot forward linear speed (MD=-0.264 m/s; 95%CI=-0.462 to -0.067), peak angular velocity (MD = -25.205 degrees/s; 95%CI = -45.507 to -4.904), and gait speed (MD = -0.104 m/s; 95%CI = -0.179 to -0.029), regardless of the group. These results suggest that MTC variability, regardless of condition, may be a promising gait parameter to differentiate once-only faller community-dwelling older adults from non-fallers.

Reliability and Validity of a Wearable Sensing System and Online Gait Analysis Report in Persons after Stroke

The restoration of gait and mobility after stroke is an important and challenging therapy goal due to the complexity of the potentially impaired functions. As a result, precise and clinically feasible assessment methods are required for personalized gait rehabilitation after stroke. The aim of this study is to investigate the reliability and validity of a sensor-based gait analysis system in stroke survivors with different severities of gait deficits. For this purpose, 28 chronic stroke survivors (9 women, ages: 62.04 ± 11.68 years) with mild to moderate walking impairments performed a set of ambulatory assessments (3× 10MWT, 1× 6MWT per session) twice while being equipped with a sensor suit. The derived gait reports provided information about speed, step length, step width, swing and stance phases, as well as joint angles of the hip, knee, and ankle, which we analyzed for test-retest reliability and hypothesis testing. Further, test-retest reliability resulted in a mean ICC of 0.78 (range: 0.46-0.88) for walking 10 m and a mean ICC of 0.90 (range: 0.63-0.99) for walking 6 min. Additionally, all gait parameters showed moderate-to-strong correlations with clinical scales reflecting lower limb function. These results support the applicability of this sensor-based gait analysis system for individuals with stroke-related walking impairments.

An observational study to assess validity and reliability of smartphone sensor-based gait and balance assessments in multiple sclerosis: Floodlight GaitLab protocol

Background

Gait and balance impairments are often present in people with multiple sclerosis (PwMS) and have a significant impact on quality of life and independence. Gold-standard quantitative tools for assessing gait and balance such as motion capture systems and force plates usually require complex technical setups. Wearable sensors, including those integrated into smartphones, offer a more frequent, convenient, and minimally burdensome assessment of functional disability in a home environment. We developed a novel smartphone sensor-based application (Floodlight) that is being used in multiple research and clinical contexts, but a complete validation of this technology is still lacking.

Methods

This protocol describes an observational study designed to evaluate the analytical and clinical validity of Floodlight gait and balance tests. Approximately 100 PwMS and 35 healthy controls will perform multiple gait and balance tasks in both laboratory-based and real-world environments in order to explore the following properties: (a) concurrent validity of the Floodlight gait and balance tests against gold-standard assessments; (b) reliability of Floodlight digital measures derived under different controlled gait and balance conditions, and different on-body sensor locations; (c) ecological validity of the tests; and (d) construct validity compared with clinician- and patient-reported assessments.

Conclusions

The Floodlight GaitLab study (ISRCTN15993728) represents a critical step in the technical validation of Floodlight technology to measure gait and balance in PwMS, and will also allow the development of new test designs and algorithms.

Comparison of gender, age, and body mass index for spatiotemporal parameters of bilateral gait pattern

Background: Studies on the gaits parameters have been identified on the patient population. Most researchers confirm that the patients walk differently than normal people and they may have a greater risk of falls. Consistent finding and description of gender, age, and body mass index differences in gait studies is rare in healthy subjects.  This research was performed to compare spatiotemporal parameters of gait between gender, as per their age and body mass index level.   Methods: A cross-sectional study was conducted with forty-five young adults (F=20, M=25). Stadiometer and Physilog 4 inertial sensors were used for data collection. A gait analyzer 5.2 software (GaitUp, S.A. Lausanne, Switzerland) was used to determine spatiotemporal parameters.   Results:  Females were found with higher mean score of total double support and cadence than males. Cadence also increases with age. Obese people showed lower gait speed, cadence, and total double support. No statistically significant differences were found in any bilateral foot gait parameters with respect to gender, age, and body mass index. Conclusion: The findings of the study may be beneficial to those who have abnormal gait pattern due to age, body mass index differences, decreased muscle strength, spasticity, and joint mobility. This important information should be considered to rehabilitate patients with abnormal gait patterns to controlling dynamic balance and risk of falling.

Biomechanics beyond the lab: Remote technology for osteoarthritis patient data-A scoping review

The objective of this project is to produce a review of available and validated technologies suitable for gathering biomechanical and functional research data in patients with osteoarthritis (OA), outside of a traditionally fixed laboratory setting. A scoping review was conducted using defined search terms across three databases (Scopus, Ovid MEDLINE, and PEDro), and additional sources of information from grey literature were added. One author carried out an initial title and abstract review, and two authors independently completed full-text screenings. Out of the total 5,164 articles screened, 75 were included based on inclusion criteria covering a range of technologies in articles published from 2015. These were subsequently categorised by technology type, parameters measured, level of remoteness, and a separate table of commercially available systems. The results concluded that from the growing number of available and emerging technologies, there is a well-established range in use and further in development. Of particular note are the wide-ranging available inertial measurement unit systems and the breadth of technology available to record basic gait spatiotemporal measures with highly beneficial and informative functional outputs. With the majority of technologies categorised as suitable for part-remote use, the number of technologies that are usable and fully remote is rare and they usually employ smartphone software to enable this. With many systems being developed for camera-based technology, such technology is likely to increase in usability and availability as computational models are being developed with increased sensitivities to recognise patterns of movement, enabling data collection in the wider environment and reducing costs and creating a better understanding of OA patient biomechanical and functional movement data.

Comprehensive validation of a wearable foot sensor system for estimating spatiotemporal gait parameters by simultaneous three-dimensional optical motion analysis

BACKGROUND

Use of a wearable gait analysis system (WGAS) is becoming common when conducting gait analysis studies due to its versatility. At the same time, its versatility raises a concern about its accuracy, because its calculations rely on assumptions embedded in its algorithms. The purpose of the present study was to validate twenty spatiotemporal gait parameters calculated by the WGAS by comparison with simultaneous measurements taken with an optical motion capture system (OMCS).

METHODS

Ten young healthy volunteers wore two inertial sensors of the commercially available WGAS, Physilog®, on their feet and 23 markers for the OMCS on the lower part of the body. The participants performed at least three sets of 10-m walk tests at their self-paced speed in the laboratory equipped with 12 high-speed digital cameras with embedded force plates. To measure repeatability, all participants returned for a second day of testing within two weeks.

RESULTS

Twenty gait parameters calculated by the WGAS had a significant correlation with the ones determined by the OMCS. Bland and Altman analysis showed that the between-device agreement for twenty gait parameters was within clinically acceptable limits. The validity of the gait parameters generated by the WGAS was found to be excellent except for two parameters, swing width and maximal heel clearance. The repeatability of the WGAS was excellent when measured between sessions.

CONCLUSION

The present study showed that spatiotemporal gait parameters estimated by the WGAS were reasonably accurate and repeatable in healthy young adults, providing a scientific basis for applying this system to clinical studies.

Differences in walking-to-turning characteristics between older adult fallers and nonfallers: a prospective and observational study using wearable inertial sensors

Wearable inertial sensors have gradually been used as an objective technology for biomechanical assessments of both healthy and pathological movement patterns. This paper used foot-worn sensors for characterizing the spatiotemporal characteristics of walking and turning between older fallers and nonfallers. Thirty community-dwelling older fallers and 30 older nonfallers performed 10-m straight walking, turned 180° around a cone, and then walked 10-m back to the starting point. Specific algorithms were used to measure spatiotemporal gait (double support phase of the gait cycle, swing width, and minimal toe clearance) and turning parameters (turn duration and turn steps) using two foot-worn Physiolog inertial sensor system. The researchers directly exported data as reported by the system. Our findings indicated that older fallers showed 26.58% longer time (P = 0.036) and 13.21% more steps (P = 0.038) compared to nonfallers during turning. However, both groups decreased their walking velocity (both P < 0.001), increased double support (both P = 0.001), and increased the swing width (both P = 0.001) during the transition from walking to turning. The older nonfallers additionally increased toe clearance (P = 0.001). Compared with the fallers, the older nonfallers showed a larger change in the swing width (P = 0.025) and toe clearance (P = 0.025) in walking to turning. Older fallers may adopt a cautionary strategy while turning to reduce the risk of falls. Wearable sensors can provide the temporospatial characteristics of turning and reveal significant differences by fall status, indicating the potential of turning measures as possible markers for identifying those at fall risk.

Automatic detection of passing and shooting in water polo using machine learning: a feasibility study

There is currently no efficient way to quantify overhead throwing volume in water polo. Therefore, this study aimed to test the feasibility of a method to detect passes and shots in water polo automatically using inertial measurement units (IMU) and machine-learning algorithms. Eight water polo players wore one IMU sensor on the wrist (dominant hand) and one on the sacrum during six practices each. Sessions were filmed with a video camera and manually tagged for individual shots or passes. Data were synchronised between video tagging and IMU sensors using a cross-correlation approach. Support vector machine (SVM) and artificial neural networks (ANN) were compared based on sensitivity and specificity for identifying shots and passes. A total of 7294 actions were identified during the training sessions, including 945 shots and 5361 passes. Using SVM, passes and shots together were identified with 94.4% (95%CI = 91.8-96.4) sensitivity and 93.6% (95%CI = 91.4-95.4) specificity. Using ANN yielded similar sensitivity (93.0% [95%CI = 90.1-95.1]) and specificity (93.4% [95%CI = 91.1 = 95.2]). The results suggest that this method of identifying overhead throwing motions with IMU has potential for future field applications. A set-up with one single sensor at the wrist can suffice to measure these activities in water polo.

Validation of shoe-worn Gait Up Physilog®5 wearable inertial sensors in adolescents

BACKGROUND

Gait Up Physilog® wearable inertial sensors are a powerful alternative to traditional laboratory-based gait assessment for children with gait impairment. To build clinician trust in these devices and ultimately facilitate their use outside confined spaces, studies have examined performance of previous versions of Physilog® wearable inertial sensors but predominant focus has been on older adults. Despite their different gait patterns and behavioural/cognitive profiles, there are limited studies in children.

RESEARCH QUESTION

To determine whether key spatiotemporal gait parameters (stride length, time and velocity) collected by shoe-worn Physilog®5 sensors in a hallway assessment protocol are a valid method of gait assessment in typically developing adolescents aged 12-15 years.

METHODS

A total 30 typically developing participants (50 % female) median age 13.7 (interquartile range 2.34) were assessed in an exploratory study whilst walking at self-selected speed over the GAITRite® electronic walkway, concurrently wearing Physilog®5 sensors. Concurrent validity was analysed by Lin's concordance correlation coefficient (CCC), Bland-Altman plots and 95 % limit of agreement. Systematic bias was assessed using 95 % confidence interval of the mean difference.

RESULTS

Mean stride data demonstrated substantial agreement for stride length (CCC = 0.975) and stride velocity (CCC = 0.979) to almost perfect agreement for stride time (CCC > 0.996). Agreement between the technologies for individual stride-to-stride data remained high for stride time (CCC = 0.952); yet reduced for stride length (CCC = 0.868) and stride velocity (CCC = 0.877). Male/female differences in performance of the technology were observed for stride velocity, favouring females.

SIGNIFICANCE

Physilog®5 inertial sensors accurately measure walking in adolescents, with stride time the most accurately detected parameter. This demonstrates that wearables can be used by researchers and clinicians working with adolescent groups as an alternative to fixed systems. These findings will ultimately pave the way to using wearables for assessments with children outside of the laboratory environment.

Personalized Motor-Cognitive Exergame Training in Chronic Stroke Patients-A Feasibility Study

Purpose: Exergame training may be beneficial for improving long-term outcome in stroke patients. Personalized training prescription applying progression rules, is missing. We adapted a theory-based taxonomy for a rehabilitation approach using user-centered exergames. The aims were primarily to investigate the feasibility of this rehabilitation approach, and secondarily to evaluate its performance of personalizing training progression, as well as explore the effects on secondary outcomes.

Methods: Chronic stroke patients (≥ 18 years) were included, who were able to walk 10 meters and stand for 3 min. The rehabilitation approach was administered twice per week for 8 weeks. As primary outcome, feasibility was evaluated by comparing achieved rates of inclusion, adherence, compliance, attrition, motivation, and satisfaction to pre-defined thresholds for acceptance. Secondary outcomes were (1) perceived motor and cognitive task difficulty throughout the intervention; (2) measures collected during baseline and post-measurements—a gait analysis, the Timed-up-and-go test (TUG), several cognitive tests assessing attentional, executive, and visuospatial functions.

Results: Thirteen patients [median: 68.0 (IQR: 49.5–73.5) years, median: 34.5 (IQR: 12.25–90.75) months post-stroke] were included, of whom ten completed the study. Rates for inclusion (57%), adherence (95%), compliance (99%), motivation (77%), and satisfaction (74%) were acceptable, however, the attrition rate was high (23%). The perceived motor and cognitive task difficulty predominantly moved below the targeted range. We found a significant change in the TUG (p = 0.05, r = 0.46) and medium-to-large effect sizes (p > 0.05) for swing time of the affected leg, the asymmetry index, time needed for the Trail-making test (TMT) A and accuracy for the TMT B and the Mental Rotation Test (MRT; 0.26 ≤ r ≤ 0.46).

Discussion: The intervention was feasible with minor modifications necessary, which warrants a larger trial investigating the effects of the rehabilitation approach following the adapted taxonomy on mobility, gait and cognitive functions. Two main limitations of the rehabilitation approach were; (1) the taxonomy decoupled motor and cognitive progression, which may be improper as motor and cognitive learning is coupled; (2) separate subjective ratings were used to guide the progression. Future studies should develop an instrument to objectively assess motor-cognitive task difficulty for monitoring the progression of an exergame-based training.

Calibration-Free Gait Assessment by Foot-Worn Inertial Sensors

Walking is a central activity of daily life, and there is an increasing demand for objective measurement-based gait assessment. In contrast to stationary systems, wearable inertial measurement units (IMUs) have the potential to enable non-restrictive and accurate gait assessment in daily life. We propose a set of algorithms that uses the measurements of two foot-worn IMUs to determine major spatiotemporal gait parameters that are essential for clinical gait assessment: durations of five gait phases for each side as well as stride length, walking speed, and cadence. Compared to many existing methods, the proposed algorithms neither require magnetometers nor a precise mounting of the sensor or dedicated calibration movements. They are therefore suitable for unsupervised use by non-experts in indoor as well as outdoor environments. While previously proposed methods are rarely validated in pathological gait, we evaluate the accuracy of the proposed algorithms on a very broad dataset consisting of 215 trials and three different subject groups walking on a treadmill: healthy subjects (n = 39), walking at three different speeds, as well as orthopedic (n = 62) and neurological (n = 36) patients, walking at a self-selected speed. The results show a very strong correlation of all gait parameters (Pearson's r between 0.83 and 0.99, p < 0.01) between the IMU system and the reference system. The mean absolute difference (MAD) is 1.4 % for the gait phase durations, 1.7 cm for the stride length, 0.04 km/h for the walking speed, and 0.7 steps/min for the cadence. We show that the proposed methods achieve high accuracy not only for a large range of walking speeds but also in pathological gait as it occurs in orthopedic and neurological diseases. In contrast to all previous research, we present calibration-free methods for the estimation of gait phases and spatiotemporal parameters and validate them in a large number of patients with different pathologies. The proposed methods lay the foundation for ubiquitous unsupervised gait assessment in daily-life environments.

The effects of a secondary task on gait in axial spondyloarthritis

Studies on the effects of dual tasking in patients with chronic inflammatory rheumatic diseases are limited. The aim of this study was to assess dual tasking while walking in patients with axial spondyloarthritis (axSpA) in comparison to healthy controls. Thirty patients with axSpA and thirty healthy controls underwent a 10-m walk test at a self-selected comfortable walking speed in single- and dual-task conditions. Foot-worn inertial sensors were used to compute spatiotemporal gait parameters. Analysis of spatiotemporal gait parameters showed that the secondary manual task negatively affected walking performance in terms of significantly decreased mean speed (p < 0.001), stride length (p < 0.001) and swing time (p = 0.008) and increased double support (p = 0.002) and stance time (p = 0.008). No significant interaction of group and condition was observed. Both groups showed lower gait performance in dual task condition by reducing speed, swing time and stride length, and increasing double support and stance time. Patients with axSpA were not more affected by the dual task than matched healthy controls, suggesting that the secondary manual task did not require greater attention in patients with axSpA. Increasing the complexity of the walking and/or secondary task may increase the sensitivity of the dual-task design to axial spondyloarthritis.

Reliability of using foot-worn devices to measure gait parameters in people with Parkinson's disease

BACKGROUND

Recent advances in technology have warranted the use of wearable sensors to monitor gait and posture. However, the psychometric properties of using wearable devices to measure gait-related outcomes have not been fully established in patients with Parkinson's disease (PD).

OBJECTIVE

This study aimed to investigate the test-retest reliability of body-worn sensors for gait evaluation in people with PD. Additionally, the influence of disease severity on the reliability was determined.

METHODS

Twenty individuals with PD were recruited. During the first evaluation, the participants wore inertial sensors on their shoes and walked along a walkway thrice at their comfortable walking speed. The participants were then required to return to the lab after 3-5 days to complete the second evaluation with the same study procedure. Test-retest reliability of gait-related outcomes were calculated. To determine whether the results would be affected by disease severity, reliability was re-calculated by subdividing the participants into early and mid-advanced stages of the disease.

RESULTS

The results showed moderate to good reliability (ICC = 0.64-0.87) of the wearable sensors for gait assessment in the general population with PD. Subgroup analysis showed that the reliability was higher among patients at early stages (ICC = 0.71-0.97) compared to those at mid-advanced stages (ICC = 0.65-0.81) of PD.

CONCLUSIONS

Wearable sensors could reliably measure gait parameters in people with PD, and the reliability was higher among individuals at early stages of the disease compared to those at mid-advanced stages. Absolute reliability values were calculated to act as references for future studies.

Assessment Methods of Post-stroke Gait: A Scoping Review of Technology-Driven Approaches to Gait Characterization and Analysis

Background: Gait dysfunction or impairment is considered one of the most common and devastating physiological consequences of stroke, and achieving optimal gait is a key goal for stroke victims with gait disability along with their clinical teams. Many researchers have explored post stroke gait, including assessment tools and techniques, key gait parameters and significance on functional recovery, as well as data mining, modeling and analyses methods.

Research Question: This study aimed to review and summarize research efforts applicable to quantification and analyses of post-stroke gait with focus on recent technology-driven gait characterization and analysis approaches, including the integration of smart low cost wearables and Artificial Intelligence (AI), as well as feasibility and potential value in clinical settings.

Methods: A comprehensive literature search was conducted within Google Scholar, PubMed, and ScienceDirect using a set of keywords, including lower extremity, walking, post-stroke, and kinematics. Original articles that met the selection criteria were included.

Results and Significance: This scoping review aimed to shed light on tools and technologies employed in post stroke gait assessment toward bridging the existing gap between the research and clinical communities. Conventional qualitative gait analysis, typically used in clinics is mainly based on observational gait and is hence subjective and largely impacted by the observer's experience. Quantitative gait analysis, however, provides measured parameters, with good accuracy and repeatability for the diagnosis and comparative assessment throughout rehabilitation. Rapidly emerging smart wearable technology and AI, including Machine Learning, Support Vector Machine, and Neural Network approaches, are increasingly commanding greater attention in gait research. Although their use in clinical settings are not yet well leveraged, these tools promise a paradigm shift in stroke gait quantification, as they provide means for acquiring, storing and analyzing multifactorial complex gait data, while capturing its non-linear dynamic variability and offering the invaluable benefits of predictive analytics.

Spatio-temporal gait parameters obtained from foot-worn inertial sensors are reliable in healthy adults in single- and dual-task conditions

Inertial measurement units (IMUs) are increasingly popular and may be usable in clinical routine to assess gait. However, assessing their intra-session reliability is crucial and has not been tested with foot-worn sensors in healthy participants. The aim of this study was to assess the intra-session reliability of foot-worn IMUs for measuring gait parameters in healthy adults. Twenty healthy participants were enrolled in the study and performed the 10-m walk test in single- and dual-task ('carrying a full cup of water') conditions, three trials per condition. IMUs were used to assess spatiotemporal gait parameters, gait symmetry parameters (symmetry index (SI) and symmetry ratio (SR)), and dual task effects parameters. The relative and the absolute reliability were calculated for each gait parameter. Results showed that spatiotemporal gait parameters measured with foot-worn inertial sensors were reliable; symmetry gait parameters relative reliability was low, and SR showed better absolute reliability than SI; dual task effects were poorly reliable, and taking the mean of the second and the third trials was the most reliable. Foot-worn IMUs are reliable to assess spatiotemporal and symmetry ratio gait parameters but symmetry index and DTE gait parameters reliabilities were low and need to be interpreted with cautious by clinicians and researchers.

Towards Human Motion Tracking Enhanced by Semi-Continuous Ultrasonic Time-of-Flight Measurements

Human motion analysis is a valuable tool for assessing disease progression in persons with conditions such as multiple sclerosis or Parkinson’s disease. Human motion tracking is also used extensively for sporting technique and performance analysis as well as for work life ergonomics evaluations. Wearable inertial sensors (e.g., accelerometers, gyroscopes and/or magnetometers) are frequently employed because they are easy to mount and can be used in real life, out-of-the-lab-settings, as opposed to video-based lab setups. These distributed sensors cannot, however, measure relative distances between sensors, and are also cumbersome when it comes to calibration and drift compensation. In this study, we tested an ultrasonic time-of-flight sensor for measuring relative limb-to-limb distance, and we developed a combined inertial sensor and ultrasonic time-of-flight wearable measurement system. The aim was to investigate if ultrasonic time-of-flight sensors can supplement inertial sensor-based motion tracking by providing relative distances between inertial sensor modules. We found that the ultrasonic time-of-flight measurements reflected expected walking motion patterns. The stride length estimates derived from ultrasonic time-of-flight measurements corresponded well with estimates from validated inertial sensors, indicating that the inclusion of ultrasonic time-of-flight measurements could be a feasible approach for improving inertial sensor-only systems. Our prototype was able to measure both inertial and time-of-flight measurements simultaneously and continuously, but more work is necessary to merge the complementary approaches to provide more accurate and more detailed human motion tracking.

Gait analysis in neurological populations: Progression in the use of wearables

Gait assessment is an essential tool for clinical applications not only to diagnose different neurological conditions but also to monitor disease progression as it contributes to the understanding of underlying deficits. There are established methods and models for data collection and interpretation of gait assessment within different pathologies. This narrative review aims to depict the evolution of gait assessment from observation and rating scales to wearable sensors and laboratory technologies and provide limitations and possible future directions in the field of gait assessment. In this context, we first present an extensive review of current clinical outcomes and gait models. Then, we demonstrate commercially available wearable technologies with their technical capabilities along with their use in gait assessment studies for various neurological conditions. In the next sections, a descriptive knowledge for existing inertial and EMG based algorithms and a sign based guide that shows the outcomes of previous neurological gait assessment studies are presented. Finally, we state a discussion for the use of wearables in gait assessment and speculate the possible research directions by revealing the limitations and knowledge gaps in the literature.

Foot-Worn Inertial Sensors Are Reliable to Assess Spatiotemporal Gait Parameters in Axial Spondyloarthritis under Single and Dual Task Walking in Axial Spondyloarthritis

The aim of this study was (1) to evaluate the relative and absolute reliability of gait parameters during walking in single- and dual-task conditions in patients with axial spondyloarthritis (axSpA), (2) to evaluate the absolute and relative reliability of dual task effects (DTE) parameters, and (3) to determine the number of trials required to ensure reliable gait assessment, in patients with axSpA. Twenty patients with axSpa performed a 10-m walk test in single- and dual-task conditions, three times for each condition. Spatiotemporal, symmetry, and DTE gait parameters were calculated from foot-worn inertial sensors. The relative reliability (intraclass correlation coefficients-ICC) and absolute reliability (standard error of measurement-SEM and minimum detectable change-MDC) were calculated for these parameters in each condition. Spatiotemporal gait parameters showed good to excellent reliability in both conditions (0.59 < ICC < 0.90). The reliability of symmetry and DTE parameters was low. ICC, SEM, and MDC were better when using the mean of the second and the third trials. Spatiotemporal gait parameters obtained from foot-worn inertial sensors assessed in patients with axSpA in single- and dual-task conditions are reliable. However, symmetry and DTE parameters seem less reliable and need to be interpreted with caution. Finally, better reliability of gait parameters was found when using the mean of the 2nd and the 3rd trials.

A Determination Method for Gait Event Based on Acceleration Sensors

A gait event is a crucial step towards the effective assessment and rehabilitation of motor dysfunctions. However, for the data acquisition of a three-dimensional motion capture (3D Mo-Cap) system, the high cost of setups, such as the high standard laboratory environment, limits widespread clinical application. Inertial sensors are increasingly being used to recognize and classify physical activities in a variety of applications. Inertial sensors are now sufficiently small in size and light in weight to be part of a body sensor network for the collection of human gait data. The acceleration signal has found important applications in human gait recognition. In this paper, using the experimental data from the heel and toe, first the wavelet method was used to remove noise from the acceleration signal, then, based on the threshold of comprehensive change rate of the acceleration signal, the signal was primarily segmented. Subsequently, the vertical acceleration signals, from heel and toe, were integrated twice, to compute their respective vertical displacement. Four gait events were determined in the segmented signal, based on the characteristics of the vertical displacement of heel and toe. The results indicated that the gait events were consistent with the synchronous record of the motion capture system. The method has achieved gait event subdivision, while it has also ensured the accuracy of the defined gait events. The work acts as a valuable reference, to further study gait recognition.