Smartphone applications to assess gait and postural control in people with multiple sclerosis: A systematic review

Gait Assessment Using Smartphone Applications in Older Adults: A Scoping Review

Spatiotemporal parameters such as gait velocity and stride length are simple indicators of functional status and can be used to predict major adverse outcomes in older adults. A smartphone can be used for gait analysis by providing spatiotemporal parameters useful for improving the diagnosis and rehabilitation processes in frail people. The aim of this study was to review articles published in the last 20 years (from 2004 to 2024) concerning the application of smartphones to assess the spatiotemporal parameters of gait in older adults. This systematic review was performed in line with Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA), and original articles were identified by searching seven electronic databases: SciVerse (ScienceDirect), Excerpta Medica Database (EMBASE), Medline, Scopus, PubMed, Web of Science and the Cochrane Library. Studies were rigorously screened using the inclusion criteria of smartphones and mobile apps, older adults and spatiotemporal gait parameters, and results were narratively synthesized. Seventy-three articles were initially identified while searching the scientific literature regarding this topic. Eleven articles were selected and included in this review. Analysis of these studies covered information about gait assessment using mobile apps recorded in 723 older adults and 164 control cases. Analysis of data related to the application of smartphones to assess spatiotemporal parameters of gait in older adults showed moderate-to-excellent test-retest reliability and validity (ICCs around 0.9) of gait speed, the most common parameter reported. Additionally, gait speeds recorded with mobile apps showed excellent agreement when compared to gold standard systems. Smartphones and mobile apps are useful, non-invasive, low-cost and objective tools that are being extensively used to perform gait analysis in older adults. Smartphones and mobile apps can reliably identify spatiotemporal parameters related to adverse outcomes, such as a slow gait speed, as predictors and outcomes in clinical practice and research involving older adults.

Tablet app-based dexterity training in multiple sclerosis (TAD-MS): a randomized controlled trial

PURPOSE

Mobile health applications (mHealth apps) may lead to health benefits. In recent years, the use of apps in multiple sclerosis (MS) has increased. Apps to train and improve dexterity in MS are scarce. This study investigated the effectiveness of a tablet app-based home-based training to improve dexterity in individuals with MS.

MATERIALS AND METHODS

In a randomized controlled trial, two standardized 4-week home-based interventions focussing on different aspects of dexterity and upper limb function were compared. Assessments were done at baseline, post-intervention and 12-week follow-up. The primary endpoint was the Arm Function in Multiple Sclerosis Questionnaire, a dexterity-related measure of patient-reported activities of daily living. Secondary endpoints were dexterous function, grip strength and health-related quality of life.

RESULTS

Forty-eight individuals were randomly assigned to a tablet app-based program (n = 26) or a control strengthening exercise program (n = 22). No significant differences were found for the primary endpoint (p = 0.35). Some significant differences in favour of the app-group were found in fine coordinated finger movements and strength. No significant differences were found at the 12-week follow-up for all endpoints. Adherence in both groups was above 90%.

CONCLUSIONS

App-based training was not superior compared to a control strengthening exercise program concerning the arm- and hand function from the participant's perspective. However, app-based training was found to be effective in improving specific dimensions (finger movements and strength), and can easily be applied at home. Therefore, individuals living with MS with impaired dexterity should consider app-based training.

CLINICAL TRIAL REGISTRATION

Clinicaltrials.gov NCT03369470.

Effects of Different Wearable Resistance Placements on Running Stability

Stability during running has been recognized as a crucial factor contributing to running performance. This study aimed to investigate the effects of wearable equipment containing external loads on different body parts on running stability. Fifteen recreational male runners (20.27 ± 1.23 years, age range 19-22 years) participated in five treadmill running conditions, including running without loads and running with loads equivalent to 10% of individual body weight placed on four different body positions: forearms, lower legs, trunk, and a combination of all three (forearms, lower legs, and trunk). A tri-axial accelerometer-based smartphone sensor was attached to the participants' lumbar spine (L5) to record body accelerations. The largest Lyapunov exponent (LyE) was applied to individual acceleration data as a measure of local dynamic stability, where higher LyE values suggest lower stability. The effects of load distribution appear in the mediolateral (ML) direction. Specifically, running with loads on the lower legs resulted in a lower LyE_ML value compared to running without loads (p = 0.001) and running with loads on the forearms (p < 0.001), trunk (p = 0.001), and combined segments (p = 0.005). These findings suggest that running with loads on the lower legs enhances side-to-side local dynamic stability, providing valuable insights for training.

Smartphone-based gait and balance assessment in survivors of stroke: a systematic review

PURPOSE

Gait and balance impairments are associated with falls and reduced quality of life among survivors of stroke (SS). Effective methods to assess these impairments at-home and in-clinic can help reduce fall risks and improve functional outcomes. Smartphone technology may be able to evaluate these impairments. This review aims to summarize the validity, reliability, sensitivity, and specificity of smartphone applications for determining gait and balance disorders in SS.

METHOD

Database search through PubMed, Web of Science, Scopus, CINAHL, and SportDiscuss was conducted to retrieve studies that explored the use of smartphone-based applications for assessing gait and balance disorders in SS. Two independent reviewers screened potential articles to determine eligibility for inclusion. Eligible studies were summarized for participant and study characteristics, validity, reliability, sensitivity, and specificity of smartphone assessments. Methodological quality assessment of studies was performed using the NIH Quality Assessment Tool.

RESULTS

Seven cross-sectional studies were included in the review. Quality assessment revealed all studies had low risk of bias. Three of the included studies examined the validity, four examined the reliability, and two examined the specificity and sensitivity of smartphone-based application assessments of gait and balance in SS. Studies revealed that smartphones were valid, reliable, specific, and sensitive. Six of the seven included studies intended their use for SS and one study for clinicians.

CONCLUSION

Preliminary evidence supports that smartphone-based gait and balance assessments are valid, reliable, sensitive, and specific in SS in laboratory settings. Future research is needed to test smartphone-based gait and balance assessments in home settings and determine optimal wear sites for assessments.IMPLICATIONS FOR REHABILITATIONSmartphone-based gait and balance assessments are feasible, valid and reliable for survivors of strokeThe findings may guide future research to standardize the use of smartphone to assess gait and balance in this population.The remote use of smartphone-based assessments to predict fall risk in survivors of stroke needs to be explored.

A Scoping Review of the Validity and Reliability of Smartphone Accelerometers When Collecting Kinematic Gait Data

The aim of this scoping review is to evaluate and summarize the existing literature that considers the validity and/or reliability of smartphone accelerometer applications when compared to 'gold standard' kinematic data collection (for example, motion capture). An electronic keyword search was performed on three databases to identify appropriate research. This research was then examined for details of measures and methodology and general study characteristics to identify related themes. No restrictions were placed on the date of publication, type of smartphone, or participant demographics. In total, 21 papers were reviewed to synthesize themes and approaches used and to identify future research priorities. The validity and reliability of smartphone-based accelerometry data have been assessed against motion capture, pressure walkways, and IMUs as 'gold standard' technology and they have been found to be accurate and reliable. This suggests that smartphone accelerometers can provide a cheap and accurate alternative to gather kinematic data, which can be used in ecologically valid environments to potentially increase diversity in research participation. However, some studies suggest that body placement may affect the accuracy of the result, and that position data correlate better than actual acceleration values, which should be considered in any future implementation of smartphone technology. Future research comparing different capture frequencies and resulting noise, and different walking surfaces, would be useful.

Wearable Sensor Technologies to Assess Motor Functions in People With Multiple Sclerosis: Systematic Scoping Review and Perspective

BACKGROUND

Wearable sensor technologies have the potential to improve monitoring in people with multiple sclerosis (MS) and inform timely disease management decisions. Evidence of the utility of wearable sensor technologies in people with MS is accumulating but is generally limited to specific subgroups of patients, clinical or laboratory settings, and functional domains.

OBJECTIVE

This review aims to provide a comprehensive overview of all studies that have used wearable sensors to assess, monitor, and quantify motor function in people with MS during daily activities or in a controlled laboratory setting and to shed light on the technological advances over the past decades.

METHODS

We systematically reviewed studies on wearable sensors to assess the motor performance of people with MS. We scanned PubMed, Scopus, Embase, and Web of Science databases until December 31, 2022, considering search terms "multiple sclerosis" and those associated with wearable technologies and included all studies assessing motor functions. The types of results from relevant studies were systematically mapped into 9 predefined categories (association with clinical scores or other measures; test-retest reliability; group differences, 3 types; responsiveness to change or intervention; and acceptability to study participants), and the reporting quality was determined through 9 questions. We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) reporting guidelines.

RESULTS

Of the 1251 identified publications, 308 were included: 176 (57.1%) in a real-world context, 107 (34.7%) in a laboratory context, and 25 (8.1%) in a mixed context. Most publications studied physical activity (196/308, 63.6%), followed by gait (81/308, 26.3%), dexterity or tremor (38/308, 12.3%), and balance (34/308, 11%). In the laboratory setting, outcome measures included (in addition to clinical severity scores) 2- and 6-minute walking tests, timed 25-foot walking test, timed up and go, stair climbing, balance tests, and finger-to-nose test, among others. The most popular anatomical landmarks for wearable placement were the waist, wrist, and lower back. Triaxial accelerometers were most commonly used (229/308, 74.4%). A surge in the number of sensors embedded in smartphones and smartwatches has been observed. Overall, the reporting quality was good.

CONCLUSIONS

Continuous monitoring with wearable sensors could optimize the management of people with MS, but some hurdles still exist to full clinical adoption of digital monitoring. Despite a possible publication bias and vast heterogeneity in the outcomes reported, our review provides an overview of the current literature on wearable sensor technologies used for people with MS and highlights shortcomings, such as the lack of harmonization, transparency in reporting methods and results, and limited data availability for the research community. These limitations need to be addressed for the growing implementation of wearable sensor technologies in clinical routine and clinical trials, which is of utmost importance for further progress in clinical research and daily management of people with MS.

TRIAL REGISTRATION

PROSPERO CRD42021243249; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=243249.

Spatiotemporal parameters from remote smartphone-based gait analysis are associated with lower extremity functional scale categories

Objective

Self-report tools are recommended in research and clinical practice to capture individual perceptions regarding health status; however, only modest correlations are found with performance-based results. The Lower Extremity Functional Scale (LEFS) is one well-validated measure of impairment affecting physical activities that has been compared with objective tests. More recently, mobile gait assessment software can provide comprehensive motion tracking output from ecologically valid environments, but how this data relates to subjective scales is unknown. Therefore, the association between the LEFS and walking variables remotely collected by a smartphone was explored.

Methods

Proprietary algorithms extracted spatiotemporal parameters detected by a standard integrated inertial measurement unit from 132 subjects enrolled in physical therapy for orthopedic or neurological rehabilitation. Users initiated ambulation recordings and completed questionnaires through the OneStep digital platform. Discrete categories were created based on LEFS score cut-offs and Analysis of Variance was applied to estimate the difference in gait metrics across functional groups (Low-Medium-High).

Results

The main finding of this cross-sectional retrospective study is that remotely-collected biomechanical walking data are significantly associated with individuals' self-evaluated function as defined by LEFS categorization (n = 132) and many variables differ between groups. Velocity was found to have the strongest effect size.

Discussion

When patients are classified according to subjective mobility level, there are significant differences in quantitative measures of ambulation analyzed with smartphone-based technology. Capturing real-time information about movement is important to obtain accurate impressions of how individuals perform in daily life while understanding the relationship between enacted activity and relevant clinical outcomes.

Determinants of gait dystonia severity in cerebral palsy

AIM

To determine the movement features governing expert assessment of gait dystonia severity in individuals with cerebral palsy (CP).

METHOD

In this prospective cohort study, three movement disorder neurologists graded lower extremity dystonia severity in gait videos of individuals with CP using a 10-point Likert-like scale. Using conventional content analysis, we determined the features experts cited when grading dystonia severity. Then, using open-source pose estimation techniques, we determined gait variable analogs of these expert-cited features correlating with their assessments of dystonia severity.

RESULTS

Experts assessed videos from 116 participants (46 with dystonia aged 15 years [SD 3] and 70 without dystonia aged 15 years [SD 2], both groups ranging 10-20 years old and 50% male). Variable limb adduction was most commonly cited by experts when identifying dystonia, comprising 60% of expert statements. Effect on gait (regularity, stability, trajectory, speed) and dystonia amplitude were common features experts used to determine dystonia severity, comprising 19% and 13% of statements respectively. Gait variables assessing adduction variability and amplitude (inter-ankle distance variance and foot adduction amplitude) were significantly correlated with expert assessment of dystonia severity (multiple linear regression, p < 0.001).

INTERPRETATION

Adduction variability and amplitude are quantifiable gait features that correlate with expert-determined gait dystonia severity in individuals with CP. Consideration of these features could help optimize and standardize the clinical assessment of gait dystonia severity in individuals with CP.

Leg Dominance—Surface Stability Interaction: Effects on Postural Control Assessed by Smartphone-Based Accelerometry

The preferential use of one leg over another in performing lower-limb motor tasks (i.e., leg dominance) is considered to be one of the internal risk factors for sports-related lower-limb injuries. The current study aimed to investigate the effects of leg dominance on postural control during unipedal balancing on three different support surfaces with increasing levels of instability: a firm surface, a foam pad, and a multiaxial balance board. In addition, the interaction effect between leg dominance and surface stability was also tested. To this end, a tri-axial accelerometer-based smartphone sensor was placed over the lumbar spine (L5) of 22 young adults (21.5 ± 0.6 years) to record postural accelerations. Sample entropy (SampEn) was applied to acceleration data as a measure of postural sway regularity (i.e., postural control complexity). The results show that leg dominance (p < 0.001) and interaction (p < 0.001) effects emerge in all acceleration directions. Specifically, balancing on the dominant (kicking) leg shows more irregular postural acceleration fluctuations (high SampEn), reflecting a higher postural control efficiency or automaticity than balancing on the non-dominant leg. However, the interaction effects suggest that unipedal balancing training on unstable surfaces is recommended to reduce interlimb differences in neuromuscular control for injury prevention and rehabilitation.

Reliability and acceptance of dreaMS, a software application for people with multiple sclerosis: a feasibility study

BACKGROUND

There is an unmet need for reliable and sensitive measures for better monitoring people with multiple sclerosis (PwMS) to detect disease progression early and adapt therapeutic measures accordingly.

OBJECTIVE

To assess reliability of extracted features and meaningfulness of 11 tests applied through a smartphone application ("dreaMS").

METHODS

PwMS (age 18-70 and EDSS ≤ 6.5) and matched healthy volunteers (HV) were asked to perform tests installed on their smartphone once or twice weekly for 5 weeks. Primary outcomes were test-retest reliability of test features (target: intraclass correlation [ICC] ≥ 0.6 or median coefficient of variation [mCV] < 0.2) and reported meaningfulness of the tests by PwMS. Meaningfulness was self-assessed for each test on a 5-point Likert scale (target: mean score of > 3) and by a structured interview.

CLINICALTRIALS

gov Identifier: NCT04413032.

RESULTS

We included 31 PwMS (21 [68%] female, mean age 43.4 ± 12.0 years, median EDSS 3.0 [range 1.0-6.0]) and 31 age- and sex-matched healthy volunteers. Out of 133 features extracted from 11 tests, 89 met the preset reliability criteria. All 11 tests were perceived as highly meaningful to PwMS.

CONCLUSION

The dreaMS app reliably assessed features reflecting key functional domains meaningful to PwMS. More studies with longer follow-up are needed to prove validity of these measures as digital biomarkers in PwMS.

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.

Recording context matters: Differences in gait parameters collected by the OneStep smartphone application

BACKGROUND

Detailed understanding of impairments that underlie walking dysfunction through objective measures is essential to diagnosis, evaluation and care planning. Despite significant developments in motion tracking technologies, there is a dearth of research about the influence of remote monitoring context on performance. The objective of this study was to determine whether gait parameters collected by the OneStep smartphone application differ based on the recording condition.

METHODS

Retrospective repeated measures univariate analysis was performed on data extracted based on detected activity, either spontaneous (background recording) or consciously initiated (in app) walks, of 25 patients enrolled in a physical therapy program.

FINDINGS

Across 7227 walking bouts, significant differences between the two paradigms in velocity (g = 0.48), double support (g = 0.37), stride length (g = 0.37) and step length of the affected side (g = 0.32) were revealed. Overall, the passively recorded walks presented a less clinically favorable spatiotemporal pattern for each of these variables.

INTERPRETATION

The recording context of walks that were used for analysis appears to significantly affect the biomechanical output of the OneStep application. It is unclear whether the disparity found would impact functional recovery of individuals undergoing rehabilitation due to neurological or musculoskeletal disorder. Clinicians may consider this information when incorporating remotely-acquired quantitative gait analysis and interpreting care outcomes as part of therapeutic practice. Future work can further investigate the behavioral and environmental factors contributing to how movement occurs in specific clinical populations when monitored via mobile health systems.

A Two-Minute Walking Test With a Smartphone App for Persons With Multiple Sclerosis: Validation Study

Background

Walking disturbances are a common dysfunction in persons with multiple sclerosis (MS). The 2-Minute Walking Test (2MWT) is widely used to quantify walking speed. We implemented a smartphone-based 2MWT (s2MWT) in MS sherpa, an app for persons with MS. When performing the s2MWT, users of the app are instructed to walk as fast as safely possible for 2 minutes in the open air, while the app records their movement and calculates the distance walked.

Objective

The aim of this study is to investigate the concurrent validity and test-retest reliability of the MS sherpa s2MWT.

Methods

We performed a validation study on 25 persons with relapsing-remitting MS and 79 healthy control (HC) participants. In the HC group, 21 participants were matched to the persons with MS based on age, gender, and education and these followed the same assessment schedule as the persons with MS (the HC-matched group), whereas 58 participants had a less intense assessment schedule to determine reference values (the HC-normative group). Intraclass correlation coefficients (ICCs) were determined between the distance measured by the s2MWT and the distance measured using distance markers on the pavement during these s2MWT assessments. ICCs were also determined for test-retest reliability and derived from 10 smartphone tests per study participant, with 3 days in between each test. We interviewed 7 study participants with MS regarding their experiences with the s2MWT.

Results

In total, 755 s2MWTs were completed. The adherence rate for the persons with MS and the participants in the HC-matched group was 92.4% (425/460). The calculated distance walked on the s2MWT was, on average, 8.43 m or 5% (SD 18.9 m or 11%) higher than the distance measured using distance markers (n=43). An ICC of 0.817 was found for the concurrent validity of the s2MWT in the combined analysis of persons with MS and HC participants. Average ICCs of 9 test-retest reliability analyses of the s2MWT for persons with MS and the participants in the HC-matched group were 0.648 (SD 0.150) and 0.600 (SD 0.090), respectively, whereas the average ICC of 2 test-retest reliability analyses of the s2MWT for the participants in the HC-normative group was 0.700 (SD 0.029). The interviewed study participants found the s2MWT easy to perform, but they also expressed that the test results can be confronting and that a pressure to reach a certain distance can be experienced.

Conclusions

The high correlation between s2MWT distance and the conventional 2MWT distance indicates a good concurrent validity. Similarly, high correlations underpin a good test-retest reliability of the s2MWT. We conclude that the s2MWT can be used to measure the distance that the persons with MS walk in 2 minutes outdoors near their home, from which both clinical studies and clinical practice can benefit.

Gait and Balance Assessments using Smartphone Applications in Parkinson's Disease: A Systematic Review

Gait dysfunctions and balance impairments are key fall risk factors and associated with reduced quality of life in individuals with Parkinson's Disease (PD). Smartphone-based assessments show potential to increase remote monitoring of the disease. This review aimed to summarize the validity, reliability, and discriminative abilities of smartphone applications to assess gait, balance, and falls in PD. Two independent reviewers screened articles systematically identified through PubMed, Web of Science, Scopus, CINAHL, and SportDiscuss. Studies that used smartphone-based gait, balance, or fall applications in PD were retrieved. The validity, reliability, and discriminative abilities of the smartphone applications were summarized and qualitatively discussed. Methodological quality appraisal of the studies was performed using the quality assessment tool for observational cohort and cross-sectional studies. Thirty-one articles were included in this review. The studies present mostly with low risk of bias. In total, 52% of the studies reported validity, 22% reported reliability, and 55% reported discriminative abilities of smartphone applications to evaluate gait, balance, and falls in PD. Those studies reported strong validity, good to excellent reliability, and good discriminative properties of smartphone applications. Only 19% of the studies formally evaluated the usability of their smartphone applications. The current evidence supports the use of smartphone to assess gait and balance, and detect freezing of gait in PD. More studies are needed to explore the use of smartphone to predict falls in this population. Further studies are also warranted to evaluate the usability of smartphone applications to improve remote monitoring in this population.Registration: PROSPERO CRD 42020198510.