Activity Monitor Placed at the Nonparetic Ankle Is Accurate in Measuring Step Counts During Community Walking in Poststroke Individuals: A Validation Study

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.

A Novel, Wearable Inertial Measurement Unit for Stroke Survivors: Validity, Acceptability, and Usability

OBJECTIVE

To establish the concurrent validity, acceptability, and sensor optimization of a consumer-grade, wearable, multi-sensor system to capture quantity and quality metrics of mobility and upper limb movements in stroke survivors.

DESIGN

Single-session, cross-sectional.

SETTING

Clinical research laboratory.

PARTICIPANTS

Thirty chronic stroke survivors (age 57 (10) years; 33% female) with mild to severe motor impairments participated.

INTERVENTIONS

Not Applicable.

MAIN OUTCOME MEASURES

Participants donned 5 sensors and performed standardized assessments of mobility and upper limb (UL) movement. True/false, positive/negative time in active movement for the UL were calculated and compared to criterion-standards using an accuracy rate. Bland-Altman plots and linear regression models were used to establish concurrent validity of UL movement counts, step counts, and stance time symmetry of MiGo against established criterion-standard measures. Acceptability and sensor optimization were assessed through an end-user survey and decision matrix.

RESULTS

Mobility metrics showed excellent association with criterion-standards for step counts (video: r=0.988, P<.001, IMU: r=0.921, P<.001) and stance-time symmetry (r=0.722, P<.001). In the UL, movement counts showed excellent to good agreement (paretic: r=0.849, P<.001, nonparetic: r=0.672, P<.001). Accuracy of active movement time was 85.2% (paretic) and 88.0% (nonparetic) UL. Most participants (63.3%) had difficulty donning/doffing the sensors. Acceptability was high (4.2/5).

CONCLUSIONS

The sensors demonstrated excellent concurrent validity for mobility metrics and UL movements of stroke survivors. Acceptability of the system was high, but alternative wristbands should be considered.

Increasing Activity After Stroke: A Randomized Controlled Trial of High-Intensity Walking and Step Activity Intervention

BACKGROUND

Physical inactivity in people with chronic stroke profoundly affects daily function and increases recurrent stroke risk and mortality, making physical activity improvements an important target of intervention. We compared the effects of a high-intensity walking intervention (FAST), a step activity monitoring behavioral intervention (SAM), or a combined intervention (FAST+SAM) on physical activity (ie, steps/day). We hypothesized the combined intervention would yield the greatest increase in steps/day.

METHODS

This assessor-blinded multisite randomized controlled trial was conducted at 4 university/hospital-based laboratories. Participants were 21 to 85 years old, walking without physical assistance following a single, unilateral noncerebellar stroke of ≥6 months duration, and randomly assigned to FAST, SAM, or FAST+SAM for 12 weeks (2-3 sessions/week). FAST training consisted of walking-related activities at 70% to 80% heart rate reserve, while SAM received daily feedback and goal setting of walking activity (steps/day). Assessors and study statistician were masked to group assignment. The a priori-determined primary outcome and end point was a comparison of the change in steps/day between the 3 intervention groups from pre- to post-intervention. Adverse events were tracked after randomization. All randomized participants were included in the intent-to-treat analysis.

RESULTS

Participants were enrolled from July 18, 2016, to November 16, 2021. Of 2385 participants initially screened, 250 participants were randomized (mean [SE] age, 63 [0.80] years; 116 females/134 males), with 89 assigned to FAST, 81 to SAM, and 80 to FAST+SAM. Steps/day significantly increased in both the SAM (mean [SE], 1542 [267; 95% CI, 1014-2069] P<0.001) and FAST+SAM group (1307 [280; 95% CI, 752-1861] P<0.001) but not in the FAST group (406 [238; 95% CI, -63 to 876] P=0.09). There were no deaths or serious study-related adverse events.

CONCLUSIONS

Only individuals with chronic stroke who completed a step activity monitoring behavioral intervention with skilled coaching and goal progression demonstrated improvements in physical activity (steps/day).

REGISTRATION

URL: https://www.clinicaltrials.gov; Unique identifier: NCT02835313.

ICF classification of therapeutic goals for outpatient episodes of neurorehabilitation in post-stroke and Parkinson disease

PURPOSE

To understand therapeutic priorities, a secondary data analysis on a retrospective cohort was conducted to classify rehabilitation goals according to the International Classification of Functioning, Disability, and Health (ICF).

MATERIALS AND METHODS

Therapeutic goals from an initial outpatient physical or occupational therapy evaluation for patients post-stroke or with Parkinson disease, were classified into Level 1 of the ICF. Goals in the Activity and Participation component were further sub-classified as activity capacity or activity performance (self-report or direct) in daily life.

RESULTS

776 goals across 104 participants were classified into Level 1 of the ICF. The majority, 73% (563/776) were classified as Activity and Participation, 20% (155/776) as Body Function and 2% (17/776) as Environmental Factors. Fifty-two percent (400/776) of all goals were classified as activity capacity and 21% (163/776) as activity performance in daily life, with 21% (160/776) of goals measuring self-report activity performance in daily life and less than 1% (3/776) of goals measuring direct activity performance in daily life.

CONCLUSIONS

While the majority of therapeutic goals were classified into the Activity and Participation component, less than 1% of goals measured direct activity performance in daily life. If people seek outpatient rehabilitation to improve functioning in their real-world environment, therapeutic goal setting should reflect this.

Measurement properties of device-based physical activity instruments in ambulatory adults with physical disabilities and/or chronic diseases: a scoping review

BACKGROUND

People with physical disabilities and/or chronic diseases tend to have an inactive lifestyle. Monitoring physical activity levels is important to provide insight on how much and what types of activities people with physical disabilities and/or chronic diseases engage in. This information can be used as input for interventions to promote a physically active lifestyle. Therefore, valid and reliable physical activity measurement instruments are needed. This scoping review aims 1) to provide a critical mapping of the existing literature and 2) directions for future research on measurement properties of device-based instruments assessing physical activity behavior in ambulant adults with physical disabilities and/or chronic diseases.

METHODS

Four databases (MEDLINE, CINAHL, Web of Science, Embase) were systematically searched from 2015 to April 16th 2023 for articles investigating measurement properties of device-based instruments assessing physical activity in ambulatory adults with physical disabilities and/or chronic diseases. For the majority, screening and selection of eligible studies were done in duplicate. Extracted data were publication data, study data, study population, device, studied measurement properties and study outcome. Data were synthesized per device.

RESULTS

One hundred three of 21566 Studies were included. 55 Consumer-grade and 23 research-grade devices were studied on measurement properties, using 14 different physical activity outcomes, in 23 different physical disabilities and/or chronic diseases. ActiGraph (n = 28) and Fitbit (n = 39) devices were most frequently studied. Steps (n = 68) was the most common used physical activity outcome. 97 studies determined validity, 11 studies reliability and 6 studies responsiveness.

CONCLUSION

This scoping review shows a large variability in research on measurement properties of device-based instruments in ambulatory adults with physical disabilities and/or chronic diseases. The variability highlights a need for standardization of and consensus on research in this field. The review provides directions for future research.

Comprehensive Assessment of the Activity Level of the ICF Using Both Capacity and Performance Measures: A Case Report

Individuals with neurologic conditions seek physical therapy services to improve mobility in their daily lives. While clinicians commonly track activity capacity, measurement of activity performance in daily life is an emerging yet unstandardized practice within routine clinical physical therapy. The purpose of this case report is to (1) provide an example of the structure, clinical reasoning, and implementation of both activity capacity and activity performance level assessments across an episode of outpatient physical therapy and (2) to describe how objective activity performance in daily life tracking supported the physical therapy intervention and education plan. A 42-year-old woman presented to outpatient neurologic physical therapy with a rare autoimmune-mediated disorder with primary goals of independently caring for her youngest child and grandchild, walking without limitations in the home and community, participating in exercise, and returning to work due to deconditioning and dizziness. The patient participated in 12 visits across a span of 4.5 months targeting performance in daily life (steps per day), aerobic conditioning, and vestibular habituation. Activity capacity measurement served as a standardized assessment of what the patient was able to do in the clinic, and activity performance in daily life tracking via a Samsung wrist worn consumer-grade device provided a quantitative assessment of real-world daily stepping activity. Tracking of activity performance in daily life was an essential component of physical therapy management that provided an objective quantification of daily stepping activity to identify barriers and facilitators to increasing daily performance in an individual with a medical diagnosis of Susac syndrome.

Predictors of non-stepping time in people with chronic stroke

BACKGROUND

Sedentary time is an independent construct from active time. Previous studies have examined variables associated with sedentary time to inform behavior change programs; however, these studies have lacked data sets that encompass potentially important domains.

OBJECTIVES

The purpose of this study was to build a more comprehensive model containing previously theorized important predictors of sedentary time and new predictors that have not been explored. We hypothesized that variables representing the domains of physical capacity, psychosocial, physical health, cognition, and environmental would be significantly related to sedentary time in individuals post-stroke.

METHODS

This was a cross-sectional analysis of 280 individuals with chronic stroke. An activity monitor was used to measure sedentary (i.e. non-stepping) time. Five domains (8 predictors) were entered into a sequential linear regression model: physical capacity (6-Minute Walk Test, assistive device use), psychosocial (Activities Specific Balance Confidence Scale and Patient Health Questionnaire-9), physical health (Charlson Comorbidity Index and body mass index), cognition (Montreal Cognitive Assessment), and environmental (Area Deprivation Index).

RESULTS

The 6-Minute Walk Test (β = -0.39, p < .001), assistive device use (β = 0.15, p = .03), Patient Health Questionnaire-9 (β = 0.16, p = .01), and body mass index (β = 0.11, p = .04) were significantly related to non-stepping time in individuals with chronic stroke. The model explained 28.5% of the variability in non-stepping time.

CONCLUSIONS

This work provides new perspective on which variables may need to be addressed in programs targeting sedentary time in stroke. Such programs should consider physical capacity, depressive symptoms, and physical health.

Beyond steps per day: other measures of real-world walking after stroke related to cardiovascular risk

Background

Significant variability exists in how real-world walking has been measured in prior studies in individuals with stroke and it is unknown which measures are most important for cardiovascular risk. It is also unknown whether real-world monitoring is more informative than laboratory-based measures of walking capacity in the context of cardiovascular risk. The purpose of this study was to determine a subset of real-world walking activity measures most strongly associated with systolic blood pressure (SBP), a measure of cardiovascular risk, in people with stroke and if these measures are associated with SBP after accounting for laboratory-based measures of walking capacity.

Methods

This was a cross-sectional analysis of 276 individuals with chronic (≥ 6 months) stroke. Participants wore an activity monitor for ≥ 3 days. Measures of activity volume, activity frequency, activity intensity, and sedentary behavior were calculated. Best subset selection and lasso regression were used to determine which activity measures were most strongly associated with systolic blood pressure. Sequential linear regression was used to determine if these activity measures were associated with systolic blood pressure after accounting for walking capacity (6-Minute Walk Test).

Results

Average bout cadence (i.e., the average steps/minute across all bouts of walking) and the number of long (≥ 30 min) sedentary bouts were most strongly associated with systolic blood pressure. After accounting for covariates (ΔR² = 0.089, p < 0.001) and walking capacity (ΔR² = 0.002, p = 0.48), these activity measures were significantly associated with systolic blood pressure (ΔR² = 0.027, p = 0.02). Higher systolic blood pressure was associated with older age (β = 0.219, p < 0.001), male gender (β = − 0.121, p = 0.046), black race (β = 0.165, p = 0.008), and a slower average bout cadence (β = − 0.159, p = 0.022).

Conclusions

Measures of activity intensity and sedentary behavior may be superior to commonly used measures, such as steps/day, when the outcome of interest is cardiovascular risk. The relationship between walking activity and cardiovascular risk cannot be inferred through laboratory-based assessments of walking capacity.

Relationships Among Environmental Variables, Physical Capacity, Balance Self-Efficacy, and Real-World Walking Activity Post-Stroke

BACKGROUND

Social and physical environmental factors affect real-world walking activity in individuals with stroke. However, environmental factors are often non-modifiable, presenting a challenge for clinicians working with individuals with stroke whose real-world walking is limited due to environmental barriers.

OBJECTIVE

The purpose of this work was to test a model hypothesizing the relationships among environmental factors (specifically, living situation and area deprivation), modifiable factors, and real-world walking activity to understand opportunities for intervention. We hypothesized that balance self-efficacy would mediate the relationship between the environment and real-world walking and that physical capacity would moderate this mediation.

METHODS

This was a cross-sectional study of 282 individuals with chronic (≥6 months) stroke. We tested the indirect effect to determine if mediation was present. Multiple group structural equation modeling was used to test if physical capacity moderated this mediation. A χ² difference test was used to compare the moderation model against the null (no moderation) model.

RESULTS

Balance self-efficacy mediated the relationship between area deprivation and real-world walking (indirect effect: β = -0.04, P = .04). Both the moderation and null models fit the data equally well statistically (χ²(5) = 6.9, P = .23). We therefore accepted the simpler (null) model and concluded that the mediation was not moderated.

CONCLUSIONS

Targeting balance self-efficacy may be an effective approach to improving real-world walking in persons with stroke who experience barriers within the physical environment. A stroke survivor's physical capacity may not impact this approach. Future work should consider utilizing more specific measures of the social and physical environment to better understand their influences on real-world walking activity in individuals with stroke. However, the results of this work provide excellent targets for future longitudinal studies targeting real-world walking activity in stroke.

mHealth technologies used to capture walking and arm use behavior in adult stroke survivors: a scoping review beyond measurement properties

PURPOSE

We aimed to provide a critical review of measurement properties of mHealth technologies used for stroke survivors to measure the amount and intensity of functional skills, and to identify facilitators and barriers toward adoption in research and clinical practice.

MATERIALS AND METHODS

Using Arksey and O'Malley's framework, two independent reviewers determined eligibility and performed data extraction. We conducted an online consultation survey exercise with 37 experts.

RESULTS

Sixty-four out of 1380 studies were included. A majority reported on lower limb behavior (n = 32), primarily step count (n = 21). Seventeen studies reported on arm-hand behaviors. Twenty-two studies reported metrics of intensity, 10 reported on energy expenditure. Reliability and validity were the most frequently reported properties, both for commercial and non-commercial devices. Facilitators and barriers included: resource costs, technical aspects, perceived usability, and ecological legitimacy. Two additional categories emerged from the survey: safety and knowledge, attitude, and clinical skill.

CONCLUSIONS

This provides an initial foundation for a field experiencing rapid growth, new opportunities and the promise that mHealth technologies affords for envisioning a better future for stroke survivors. We synthesized findings into a set of recommendations for clinicians and clinician-scientists about how best to choose mHealth technologies for one's individual objective.Implications for RehabilitationRehabilitation professionals are encouraged to consider the measurement properties of those technologies that are used to monitor functional locomotor and object-interaction skills in the stroke survivors they serve.Multi-modal knowledge translation strategies (research synthesis, educational courses or videos, mentorship from experts, etc.) are available to rehabilitation professionals to improve knowledge, attitude, and skills pertaining to mHealth technologies.Consider the selection of commercially available devices that are proven to be valid, reliable, accurate, and responsive to the targeted clinical population.Consider usability and privacy, confidentiality and safety when choosing a specific device or smartphone application.

Implementation of Wearable Sensing Technology for Movement: Pushing Forward into the Routine Physical Rehabilitation Care Field

While the promise of wearable sensor technology to transform physical rehabilitation has been around for a number of years, the reality is that wearable sensor technology for the measurement of human movement has remained largely confined to rehabilitation research labs with limited ventures into clinical practice. The purposes of this paper are to: (1) discuss the major barriers in clinical practice and available wearable sensing technology; (2) propose benchmarks for wearable device systems that would make it feasible to implement them in clinical practice across the world and (3) evaluate a current wearable device system against the benchmarks as an example. If we can overcome the barriers and achieve the benchmarks collectively, the field of rehabilitation will move forward towards better movement interventions that produce improved function not just in the clinic or lab, but out in peoples' homes and communities.

Reliability and Validity of Commercially Available Wearable Devices for Measuring Steps, Energy Expenditure, and Heart Rate: Systematic Review

Background

Consumer-wearable activity trackers are small electronic devices that record fitness and health-related measures.

Objective

The purpose of this systematic review was to examine the validity and reliability of commercial wearables in measuring step count, heart rate, and energy expenditure.

Methods

We identified devices to be included in the review. Database searches were conducted in PubMed, Embase, and SPORTDiscus, and only articles published in the English language up to May 2019 were considered. Studies were excluded if they did not identify the device used and if they did not examine the validity or reliability of the device. Studies involving the general population and all special populations were included. We operationalized validity as criterion validity (as compared with other measures) and construct validity (degree to which the device is measuring what it claims). Reliability measures focused on intradevice and interdevice reliability.

Results

We included 158 publications examining nine different commercial wearable device brands. Fitbit was by far the most studied brand. In laboratory-based settings, Fitbit, Apple Watch, and Samsung appeared to measure steps accurately. Heart rate measurement was more variable, with Apple Watch and Garmin being the most accurate and Fitbit tending toward underestimation. For energy expenditure, no brand was accurate. We also examined validity between devices within a specific brand.

Conclusions

Commercial wearable devices are accurate for measuring steps and heart rate in laboratory-based settings, but this varies by the manufacturer and device type. Devices are constantly being upgraded and redesigned to new models, suggesting the need for more current reviews and research.

An investigation into the validity and reliability of mHealth devices for counting steps in chronic stroke survivors

Objective:

To investigate the validity and test–retest reliability of mHealth devices (Google Fit, Health, STEPZ, Pacer, and Fitbit Ultra) to estimate the number of steps in individuals after chronic stroke and to compare whether the measurement of the number of steps is affected by their location on the body (paretic and non-paretic side).

Design:

Observational study with repeated measures.

Setting:

University laboratory.

Subjects:

Fifty-five community-dwelling individuals with chronic stroke.

Intervention:

Not applicable.

Main measures:

The number of steps was measured using mHealth devices (Google Fit, Health, STEPZ, Pacer, and Fitbit Ultra), and compared against criterion-standard measure during the Two-Minute Walk Test using habitual speed.

Results:

Our sample was 54.5% men, mean age of 62.5 years (SD 14.9) with a chronicity after stroke of 66.8 months (SD 55.9). There was a statistically significant association between the actual number of steps and those estimated by the Google Fit, STEPZ Iphone and Android applications, Pacer iphone and Android, and Fitbit Ultra (0.30 ⩽  r ⩾ 0.80). The Pacer iphone application demonstrated the highest reliability coefficient (ICC(2,1) = 0.80; P < 0.001). There were no statistically significant differences in device measurements that depended on body location.

Conclusions:

mHealth devices (Pacer–iphone, Fitbit Ultra, Google Fit, and Pacer–Android) are valid and reliable for step counting in chronic stroke survivors. Body location (paretic or non-paretic side) does not affect validity or reliability of the step count metric.