Step count accuracy of StepWatch and FitBit One™ among individuals with a unilateral transtibial amputation

Comparison of three device generations of the StepWatch Activity Monitor: analysis of model version agreement in pediatric and adult independent ambulators

Purpose

Devices such as the StepWatch Activity Monitor (SAM) have been available for 20 years and have been shown to accurately measure ambulatory activity. This study aimed to evaluate the agreement among the three generations of the StepWatch Activity Monitor (SW3, SW4, and SW5) with respect to stride count.

Methods

A total of 36 participants (age range, 6-55 years) participated in this institutional review board-approved study. The participants concurrently wore three different SAM model devices on the same leg and performed a 6-min walk test (6MWT). A research staff member of the laboratory manually counted the number of strides for the first 2 min of the test (2MWT). Agreement among the device models was evaluated by calculating ANOVAs and interclass correlation coefficients (ICCs) and creating Bland-Altman plots.

Results

There was no significant difference among the model versions during the 6MWT and 2MWT (p > 0.05). The ICC for the total stride count was 0.993 (95% CI = 0.988-0.996) during the 2MWT and 0.992 (95% CI = 0.986-0.996) during the 6MWT. There was a near-perfect agreement (ICC ≥ 0.990) of each model version to the manually counted strides during the 2MWT. The systematic bias of all three SAM model versions was <1 step.

Conclusions

The results from the present study demonstrate that the stride counts among all three devices are comparable and relative to the manual stride count. All three SAM model versions had an ICC of >0.90. Researchers can safely incorporate historical data from previous SAM model versions with newer data collected with the latest SAM model version.

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.

Adults with lower-limb amputation: Reduced multifidi muscle activity and extensor muscle endurance is associated with worse physical performance

Trunk muscles may be an overlooked region of deficits following lower-limb amputation (LLA). This study sought to determine the extent that trunk muscle deficits are associated with physical function following amputation. Sedentary adults with a unilateral transtibial- (n = 25) or transfemoral-level (n = 14) amputation were recruited for this cross-sectional research study. Participants underwent a clinical examination that included ultrasound imaging of the lumbar multifidi muscles, the modified Biering-Sorensen Endurance Test (mBSET), and performance-based measures, that is, the Timed Up and Go (TUG), Berg Balance Scale (BBS), and 10-m Walk Test (10mWT). Associations between trunk muscle metrics and performance were explored with regression modeling, while considering covariates known to impact performance postamputation (p ≤ 0.100). Average ultrasound-obtained, lumbar multifidi activity was 14% and 16% for transfemoral- and transtibial-level amputations, respectively, while extensor endurance was 37.34 and 12.61 s, respectively. For TUG, nonamputated-side multifidi activity and an interaction term (level x non-amputated-side multifidi activity) explained 9.4% and 6.2% of the total variance, respectively. For 10mWT, beyond covariates, non-amputated-side multifidi activity and the interaction term explained 6.1% and 5.8% of the total variance, respectively. For TUG, extensor endurance and an interaction term (level x mBSET) explained 11.9% and 8.3% of the total variance beyond covariates; for BBS and 10mWT, extensor endurance explained 11.2% and 17.2% of the total variance, respectively. Findings highlight deficits in lumbar multifidi activity and extensor muscle endurance among sedentary adults with a LLA; reduced muscle activity and endurance may be important factors to target during rehabilitation to enhance mobility-related outcomes.

Clinical mobility metrics estimate and characterize physical activity following lower-limb amputation

Background

Regular physical activity following a lower-limb amputation is essential for maintaining health and a high quality of life. Most adults with a lower-limb amputation, however, participate in insufficient daily physical activity, and thus, are predisposed to poor health outcomes. Estimating physical activity after lower-limb amputation via common mobility metrics may aid in clinical decisions regarding treatment prioritization and prosthesis prescription. The objectives of this study were (a) to examine associations between daily physical activity and patient-reported and performance-based mobility metrics among adults with lower-limb amputation, and (b) to determine whether patient-reported and performance-based mobility metrics can distinguish between physical activity status [i.e., sedentary (< 5000 steps/day) or non-sedentary (≥ 5000 steps/day)] of adults with lower-limb amputation.

Methods

A cross-sectional study involving 35 adults with a unilateral transtibial (N = 23; 63.0 ± 10.4 years) or transfemoral amputation (N = 12; 58.8 ± 9.5 years) was conducted. Participants completed patient-reported (Prosthesis Evaluation Questionnaire-Mobility Subscale) and performance-based mobility metrics (L-Test, 10-m Walk Test, 6-min Walk Test). Physical activity, i.e., average steps/day, was measured with an accelerometer.

Results

Patient-reported and performance-based mobility metrics were associated with daily physical activity (p < 0.050). Prosthesis Evaluation Questionnaire-Mobility Subscale scores, L-Test time, 10-m Walk Test speed and 6-min Walk Test distance independently explained 11.3%, 31.8%, 37.6% and 30.7% of the total variance in physical activity. Receiver operating characteristic curves revealed patient-reported and performance-based mobility metrics significantly distinguish between physical activity status, i.e., sedentary (< 5000 steps/day) versus non-sedentary (≥ 5000 steps/day). Preliminary cut-points for mobility metrics to classify physical activity status were determined.

Conclusions

Following a lower-limb amputation, patient-reported and performance-based mobility metrics may estimate daily physical activity, thereby aiding clinical decisions regarding treatment prioritization as well as prosthesis selection.

Residual and sound limb hip strength distinguish between sedentary and nonsedentary adults with transtibial amputation

Following a transtibial amputation (TTA), physical activity has known benefits for health and quality of life. Adults post-TTA, however, demonstrate reduced physical activity, predisposing them to adverse health outcomes. Identifying adults at the risk of sedentarism post-TTA via commonly used, objective clinical measures may enhance clinical decisions, including prosthesis prescription. The study's purpose was to determine whether residual and sound limb hip strength distinguishes between sedentary and nonsedentary adults post-TTA. A secondary analysis of a cross-sectional dataset (n = 44) was conducted. Participant residual and sound limb hip flexion, extension, abduction and adduction strength were assessed via handheld dynamometry. Physical activity was monitored for 7 days and participants were classified as sedentary (<5000 steps/day; n = 13) or nonsedentary (≥5000 steps/day; n = 31). Receiver operating curves revealed that residual and sound limb hip extension, abduction and adduction strength distinguished between sedentary and nonsedentary adults post-TTA (P < 0.050). Preliminary cut-points for hip strength measures to classify adults at the risk of sedentarism were determined. A hip strength composite score (0-6) estimates a 2.2× increased odds of being sedentary with each additional hip strength deficit. Post-TTA, residual and sound limb hip strength can help identify adults at risk of sedentarism to aid clinical decision making, including prosthesis prescription.

Accurate Step Count with Generalized and Personalized Deep Learning on Accelerometer Data

Physical activity (PA) is globally recognized as a pillar of general health. Step count, as one measure of PA, is a well known predictor of long-term morbidity and mortality. Despite its popularity in consumer devices, a lack of methodological standards and clinical validation remains a major impediment to step count being accepted as a valid clinical endpoint. Previous works have mainly focused on device-specific step-count algorithms and often employ sensor modalities that may not be widely available. This may limit step-count suitability in clinical scenarios. In this paper, we trained neural network models on publicly available data and tested on an independent cohort using two approaches: generalization and personalization. Specifically, we trained neural networks on accelerometer signals from one device and either directly applied them or adapted them individually to accelerometer data obtained from a separate subject cohort wearing multiple distinct devices. The best models exhibited highly accurate step-count estimates for both the generalization (96-99%) and personalization (98-99%) approaches. The results demonstrate that it is possible to develop device-agnostic, accelerometer-only algorithms that provide highly accurate step counts, positioning step count as a reliable mobility endpoint and a strong candidate for clinical validation.

Reported Outcome Measures in Studies of Real-World Ambulation in People with a Lower Limb Amputation: A Scoping Review

Background: The rapidly increasing use of wearable technology to monitor free-living ambulatory behavior demands to address to what extent the chosen outcome measures are representative for real-world situations. This scoping review aims to provide an overview of the purpose of use of wearable activity monitors in people with a Lower Limb Amputation (LLA) in the real world, to identify the reported outcome measures, and to evaluate to what extent the reported outcome measures capture essential information from real-world ambulation of people with LLA. Methods: The literature search included a search in three databases (MEDLINE, CINAHL, and EMBASE) for articles published between January 1999 and January 2022, and a hand-search. Results and conclusions: 98 articles met the inclusion criteria. According to the included studies’ main objective, the articles were classified into observational (n = 46), interventional (n = 34), algorithm/method development (n = 12), and validity/feasibility studies (n = 6). Reported outcome measures were grouped into eight categories: step count (reported in 73% of the articles), intensity of activity/fitness (31%), type of activity/body posture (27%), commercial scores (15%), prosthetic use and fit (11%), gait quality (7%), GPS (5%), and accuracy (4%). We argue that researchers should be more careful with choosing reliable outcome measures, in particular, regarding the frequently used category step count. However, the contemporary technology is limited in providing a comprehensive picture of real-world ambulation. The novel knowledge from this review should encourage researchers and developers to engage in debating and defining the framework of ecological validity in rehabilitation sciences, and how this framework can be utilized in the development of wearable technologies and future studies of real-world ambulation in people with LLA.

Validity of measures for life space mobility and physical activity in older adults with lower-limb amputation

BACKGROUND

Older adults with lower-limb amputations (LLAs) often experience lack of confidence and poor balance, which limits their mobility. There are few validated measures for assessing these outcomes in the LLA population.

OBJECTIVES

To assess the validity of the Life Space Assessment (LSA) and the Physical Activity Scale for the Elderly (PASE) for older adults with LLA.

STUDY DESIGN

Secondary analyses of cross-sectional data.

METHODS

Sixty-eight older adults with LLA across Canada were recruited to complete the LSA and the PASE. Validity was assessed via correlations with the Activities-specific Balance Confidence (ABC), Four-Square Step Test (FSST), and Two-Minute Walk Test (2-MWT).

RESULTS

As hypothesized, the LSA was positively correlated with the ABC (ρ = 0.36, 95% confidence interval [CI] [0.17, 0.62]) and 2-MWT (r = 0.49, 95% CI [0.27, 0.70]) and negatively correlated with FSST (ρ = -0.39, 95% CI [-0.56, -0.10]). The PASE was positively correlated with the ABC (ρ = 0.34, 95% CI [0.10, 0.56]) and 2-MWT (ρ = 0.32, 95% CI [0.05, 0.52]), and negatively correlated with FSST (ρ = -0.36, 95% CI [-0.53, -0.07]).

CONCLUSIONS

The LSA has validity in measuring life space mobility. The PASE captures the physical activity with weaker support of validity in older adults with LLA.

CLINICAL RELEVANCE

The LSA and PASE are quick low-cost tools for clinicians to assess mobility-related functional health and physical activity, respectively, in older adults with LLA. However, the PASE may contain activities that are not common among older adults with LLA.

Quantifying Step Count and Oxygen Consumption with Portable Technology during the 2-Min Walk Test in People with Lower Limb Amputation

Step counts and oxygen consumption have yet to be reported during the 2-min walk test (2MWT) test in persons with lower-limb amputations (LLA). The purpose of this study was to determine step counts and oxygen consumption during the 2MWT in LLA. Thirty-five men and women walked for two minutes as quickly as possible while wearing activity monitors (ActiGraph Link on the wrist (LW) and ankle (LA), Garmin vivofit^®3 on the wrist (VW) and ankle (VA), and a modus StepWatch on the ankle (SA), and a portable oxygen analyzer. The StepWatch on the ankle (SA) and the vivofit3 on the wrist (VW) had the least error and best accuracy of the activity monitors studied. While there were no significant differences in distance walked, oxygen consumption (VO₂) or heart rate (HR) between sexes or level of amputation (p > 0.05), females took significantly more steps than males (p = 0.034), and those with unilateral transfemoral amputations took significantly fewer steps than those with unilateral transtibial amputations (p = 0.023). The VW and SA provided the most accurate step counts among the activity monitors and were not significantly different than hand counts. Oxygen consumption for all participants during the 2MWT was 8.9 ± 2.9 mL/kg/min, which is lower than moderate-intensity activity. While some may argue that steady-state activity has not yet been reached in the 2MWT, it may also be possible participants are not walking as fast as they can, thereby misclassifying their performance to a lower standard.

Recommendations for determining the validity of consumer wearable and smartphone step count: expert statement and checklist of the INTERLIVE network

Consumer wearable and smartphone devices provide an accessible means to objectively measure physical activity (PA) through step counts. With the increasing proliferation of this technology, consumers, practitioners and researchers are interested in leveraging these devices as a means to track and facilitate PA behavioural change. However, while the acceptance of these devices is increasing, the validity of many consumer devices have not been rigorously and transparently evaluated. The Towards Intelligent Health and Well-Being Network of Physical Activity Assessment (INTERLIVE) is a joint European initiative of six universities and one industrial partner. The consortium was founded in 2019 and strives to develop best-practice recommendations for evaluating the validity of consumer wearables and smartphones. This expert statement presents a best-practice consumer wearable and smartphone step counter validation protocol. A two-step process was used to aggregate data and form a scientific foundation for the development of an optimal and feasible validation protocol: (1) a systematic literature review and (2) additional searches of the wider literature pertaining to factors that may introduce bias during the validation of these devices. The systematic literature review process identified 2897 potential articles, with 85 articles deemed eligible for the final dataset. From the synthesised data, we identified a set of six key domains to be considered during design and reporting of validation studies: target population, criterion measure, index measure, validation conditions, data processing and statistical analysis. Based on these six domains, a set of key variables of interest were identified and a 'basic' and 'advanced' multistage protocol for the validation of consumer wearable and smartphone step counters was developed. The INTERLIVE consortium recommends that the proposed protocol is used when considering the validation of any consumer wearable or smartphone step counter. Checklists have been provided to guide validation protocol development and reporting. The network also provide guidance for future research activities, highlighting the imminent need for the development of feasible alternative 'gold-standard' criterion measures for free-living validation. Adherence to these validation and reporting standards will help ensure methodological and reporting consistency, facilitating comparison between consumer devices. Ultimately, this will ensure that as these devices are integrated into standard medical care, consumers, practitioners, industry and researchers can use this technology safely and to its full potential.

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.

Performance-based outcome measures are associated with cadence variability during community ambulation among individuals with a transtibial amputation

BACKGROUND

In the United States, Medicare Functional Classification Level (K-level) guidelines require demonstration of cadence variability to justify higher-level prosthetic componentry prescription; however, clinical assessment of cadence variability is subjective. Currently, no clinical outcome measures are associated with cadence variability during community ambulation.

OBJECTIVES

Evaluate whether physical performance, i.e. 10-meter Walk Test (10mWT)-based walking speeds, L-Test, and Figure-of-8 Walk Test scores, is associated with community-based cadence variability among individuals with a transtibial amputation.

STUDY DESIGN

Cross-sectional.

METHODS

Forty-nine participants, aged 18-85 years, with a unilateral transtibial amputation were included. Linear regression models were conducted to determine whether physical performance was associated with cadence variability (a unitless calculation from FitBit® One^TM minute-by-minute step counts), while controlling for sex, age, and time since amputation (p ⩽ .013).

RESULTS

Beyond covariates, self-selected gait speed explained the greatest amount of variance in cadence variability (19.2%, p < .001). Other outcome measures explained smaller, but significant, amounts of the variance (11.1-17.1%, p = .001-.008). For each 0.1 m/s-increase in self-selected and fast gait speeds, or each 1-s decrease in L-Test and F8WT time, community-based cadence variability increased by 1.76, 1.07, 0.39, and 0.79, respectively (p < .013).

CONCLUSIONS

In clinical settings, faster self-selected gait speed best predicted increased cadence variability during community ambulation.

CLINICAL RELEVANCE

The 10-meter Walk Test may be prioritized during prosthetic evaluations to provide objective self-selected walking speed data, which informs the assessment of cadence variability potential outside of clinical settings.

Technology for monitoring everyday prosthesis use: a systematic review

BACKGROUND

Understanding how prostheses are used in everyday life is central to the design, provision and evaluation of prosthetic devices and associated services. This paper reviews the scientific literature on methodologies and technologies that have been used to assess the daily use of both upper- and lower-limb prostheses. It discusses the types of studies that have been undertaken, the technologies used to monitor physical activity, the benefits of monitoring daily living and the barriers to long-term monitoring, with particular focus on low-resource settings.

METHODS

A systematic literature search was conducted in PubMed, Web of Science, Scopus, CINAHL and EMBASE of studies that monitored the activity of prosthesis users during daily-living.

RESULTS

Sixty lower-limb studies and 9 upper-limb studies were identified for inclusion in the review. The first studies in the lower-limb field date from the 1990s and the number has increased steadily since the early 2000s. In contrast, the studies in the upper-limb field have only begun to emerge over the past few years. The early lower-limb studies focused on the development or validation of actimeters, algorithms and/or scores for activity classification. However, most of the recent lower-limb studies used activity monitoring to compare prosthetic components. The lower-limb studies mainly used step-counts as their only measure of activity, focusing on the amount of activity, not the type and quality of movements. In comparison, the small number of upper-limb studies were fairly evenly spread between development of algorithms, comparison of everyday activity to clinical scores, and comparison of different prosthesis user populations. Most upper-limb papers reported the degree of symmetry in activity levels between the arm with the prosthesis and the intact arm.

CONCLUSIONS

Activity monitoring technology used in conjunction with clinical scores and user feedback, offers significant insights into how prostheses are used and whether they meet the user's requirements. However, the cost, limited battery-life and lack of availability in many countries mean that using sensors to understand the daily use of prostheses and the types of activity being performed has not yet become a feasible standard clinical practice. This review provides recommendations for the research and clinical communities to advance this area for the benefit of prosthesis users.