Comparing Accuracy of Step Count Detection Algorithm at Different Activity Monitor Wear Locations

2021 ◽  
Vol 102 (10) ◽  
pp. e79
Author(s):  
Akhila Veerubhotla ◽  
Naphtaly Ehrenberg ◽  
Oluwaseun Ibironke ◽  
Rakesh Pilkar
Keyword(s):  
Activity Monitor ◽  
Detection Algorithm ◽  
Step Count

scholarly journals Formative Evaluation of Consumer-Grade Activity Monitors Worn by Older Adults: Test-Retest Reliability and Criterion Validity of Step Counts (Preprint)

2019 ◽  
Author(s):  
Stephanie A Maganja ◽  
David C Clarke ◽  
Scott A Lear ◽  
Dawn C Mackey
Keyword(s):  
Older Adults ◽  
Activity Monitor ◽  
Criterion Validity ◽  
Step Count ◽  
Retest Reliability ◽  
Activity Monitors ◽  
Limited Mobility ◽  
Step Counts ◽  
Test Retest Reliability ◽  
Mobility Status

BACKGROUND To assess whether commercial-grade activity monitors are appropriate for measuring step counts in older adults, it is essential to evaluate their measurement properties in this population. OBJECTIVE This study aimed to evaluate test-retest reliability and criterion validity of step counting in older adults with self-reported intact and limited mobility from 6 commercial-grade activity monitors: Fitbit Charge, Fitbit One, Garmin vívofit 2, Jawbone UP2, Misfit Shine, and New-Lifestyles NL-1000. METHODS For test-retest reliability, participants completed two 100-step overground walks at a usual pace while wearing all monitors. We tested the effects of the activity monitor and mobility status on the absolute difference in step count error (%) and computed the standard error of measurement (SEM) between repeat trials. To assess criterion validity, participants completed two 400-meter overground walks at a usual pace while wearing all monitors. The first walk was continuous; the second walk incorporated interruptions to mimic the conditions of daily walking. Criterion step counts were from the researcher tally count. We estimated the effects of the activity monitor, mobility status, and walk interruptions on step count error (%). We also generated Bland-Altman plots and conducted equivalence tests. RESULTS A total of 36 individuals participated (n=20 intact mobility and n=16 limited mobility; 19/36, 53% female) with a mean age of 71.4 (SD 4.7) years and BMI of 29.4 (SD 5.9) kg/m<sup>2</sup>. Considering test-retest reliability, there was an effect of the activity monitor (<i>P</i>&lt;.001). The Fitbit One (1.0%, 95% CI 0.6% to 1.3%), the New-Lifestyles NL-1000 (2.6%, 95% CI 1.3% to 3.9%), and the Garmin vívofit 2 (6.0%, 95 CI 3.2% to 8.8%) had the smallest mean absolute differences in step count errors. The SEM values ranged from 1.0% (Fitbit One) to 23.5% (Jawbone UP2). Regarding criterion validity, all monitors undercounted the steps. Step count error was affected by the activity monitor (<i>P</i>&lt;.001) and walk interruptions (<i>P</i>=.02). Three monitors had small mean step count errors: Misfit Shine (−1.3%, 95% CI −19.5% to 16.8%), Fitbit One (−2.1%, 95% CI −6.1% to 2.0%), and New-Lifestyles NL-1000 (−4.3%, 95 CI −18.9% to 10.3%). Mean step count error was larger during interrupted walking than continuous walking (−5.5% vs −3.6%; <i>P</i>=.02). Bland-Altman plots illustrated nonsystematic bias and small limits of agreement for Fitbit One and Jawbone UP2. Mean step count error lay within an equivalence bound of ±5% for Fitbit One (<i>P</i>&lt;.001) and Misfit Shine (<i>P</i>=.001). CONCLUSIONS Test-retest reliability and criterion validity of step counting varied across 6 consumer-grade activity monitors worn by older adults with self-reported intact and limited mobility. Walk interruptions increased the step count error for all monitors, whereas mobility status did not affect the step count error. The hip-worn Fitbit One was the only monitor with high test-retest reliability and criterion validity.

scholarly journals Step and Distance Measurement From a Low-Cost Consumer-Based Hip and Wrist Activity Monitor: Protocol for a Validity and Reliability Assessment (Preprint)

2020 ◽  
Author(s):  
Thomas Carlin ◽  
Nicolas Vuillerme
Keyword(s):  
Walking Speed ◽  
Low Cost ◽  
Activity Monitor ◽  
Distance Measurement ◽  
Step Count ◽  
Mobile Technologies ◽  
Experimental Session ◽  
Validity And Reliability ◽  
Activity Monitors ◽  
Study Results

BACKGROUND Self-tracking via wearable and mobile technologies is becoming an essential part of personal health management. At this point, however, little information is available to substantiate the validity and reliability of low-cost consumer-based hip and wrist activity monitors, with regard more specifically to the measurements of step counts and distance traveled while walking. OBJECTIVE The aim of our study is to assess the validity and reliability of step and distance measurement from a low-cost consumer-based hip and wrist activity monitor specific in various walking conditions that are commonly encountered in daily life. Specifically, this study is designed to evaluate whether and to what extent validity and reliability could depend on the sensor placement on the human body and the walking task being performed. METHODS Thirty healthy participants will be instructed to wear four PBN 2433 (Nakosite) activity monitors simultaneously, with one placed on each hip and each wrist. Participants will attend two experimental sessions separated by 1 week. During each experimental session, two separate studies will be performed. In study 1, participants will be instructed to complete a 2-minute walk test along a 30-meter indoor corridor under 3 walking speeds: very slow, slow, and usual speed. In study 2, participants will be required to complete the following 3 conditions performed at usual walking speed: walking on flat ground, upstairs, and downstairs. Activity monitor measured step count and distance values will be computed along with the actual step count (determined from video recordings) and distance (measured using a measuring tape) to determine validity and reliability for each activity monitor placement and each walking condition. RESULTS Participant recruitment and data collection began in January 2020. As of June 2020, we enrolled 8 participants. Dissemination of study results in peer-reviewed journals is expected in spring 2021. CONCLUSIONS To the best of our knowledge, this is the first study that examines the validity and reliability of step and distance measurement during walking using the PBN 2433 (Nakosite) activity monitor. Results of this study will provide beneficial information on the effects of activity monitor placement, walking speed, and walking tasks on the validity and reliability of step and distance measurement. We believe such information is of utmost importance to general consumers, clinicians, and researchers. INTERNATIONAL REGISTERED REPORT DERR1-10.2196/21262

scholarly journals Evaluation of the FitBark Activity Monitor for Measuring Physical Activity in Dogs

Animals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 781
Author(s):  
Jessica Colpoys ◽  
Dean DeCock
Keyword(s):  
Physical Activity ◽  
Video Analysis ◽  
Activity Monitor ◽  
Criterion Validity ◽  
Step Count ◽  
Phase 3 ◽  
Activity Data ◽  
Phase Approach ◽  
Low Correlation ◽  
Three Phase

Accelerometers track changes in physical activity which can indicate health and welfare concerns in dogs. The FitBark 2 (FitBark) is an accelerometer for use with dogs; however, no studies have externally validated this tool. The objective of this study was to evaluate FitBark criterion validity by correlating FitBark activity data to dog step count. Dogs (n = 26) were fitted with a collar-mounted FitBark and individually recorded for 30 min using a three-phase approach: (1) off-leash room explore; (2) human–dog interaction; and (3) on-leash walk. Video analysis was used to count the number of times the front right paw touched the ground (step count). Dog step count and FitBark activity were moderately correlated across all phases (r = 0.65, p < 0.001). High correlations between step count and FitBark activity were observed during phases 1 (r = 0.795, p < 0.001) and 2 (r = 0.758, p < 0.001), and a low correlation was observed during phase 3 (r = 0.498, p < 0.001). In conclusion, the FitBark is a valid tool for tracking physical activity in off-leash dogs; however, more work should be done to identify the best method of tracking on-leash activity.

scholarly journals Formative Evaluation of Consumer-Grade Activity Monitors Worn by Older Adults: Test-Retest Reliability and Criterion Validity of Step Counts

10.2196/16537 ◽  
2020 ◽  
Vol 4 (8) ◽  
pp. e16537 ◽  
Author(s):  
Stephanie A Maganja ◽  
David C Clarke ◽  
Scott A Lear ◽  
Dawn C Mackey
Keyword(s):  
Older Adults ◽  
Activity Monitor ◽  
Criterion Validity ◽  
Step Count ◽  
Retest Reliability ◽  
Activity Monitors ◽  
Limited Mobility ◽  
Step Counts ◽  
Test Retest Reliability ◽  
Mobility Status

Background To assess whether commercial-grade activity monitors are appropriate for measuring step counts in older adults, it is essential to evaluate their measurement properties in this population. Objective This study aimed to evaluate test-retest reliability and criterion validity of step counting in older adults with self-reported intact and limited mobility from 6 commercial-grade activity monitors: Fitbit Charge, Fitbit One, Garmin vívofit 2, Jawbone UP2, Misfit Shine, and New-Lifestyles NL-1000. Methods For test-retest reliability, participants completed two 100-step overground walks at a usual pace while wearing all monitors. We tested the effects of the activity monitor and mobility status on the absolute difference in step count error (%) and computed the standard error of measurement (SEM) between repeat trials. To assess criterion validity, participants completed two 400-meter overground walks at a usual pace while wearing all monitors. The first walk was continuous; the second walk incorporated interruptions to mimic the conditions of daily walking. Criterion step counts were from the researcher tally count. We estimated the effects of the activity monitor, mobility status, and walk interruptions on step count error (%). We also generated Bland-Altman plots and conducted equivalence tests. Results A total of 36 individuals participated (n=20 intact mobility and n=16 limited mobility; 19/36, 53% female) with a mean age of 71.4 (SD 4.7) years and BMI of 29.4 (SD 5.9) kg/m2. Considering test-retest reliability, there was an effect of the activity monitor (P<.001). The Fitbit One (1.0%, 95% CI 0.6% to 1.3%), the New-Lifestyles NL-1000 (2.6%, 95% CI 1.3% to 3.9%), and the Garmin vívofit 2 (6.0%, 95 CI 3.2% to 8.8%) had the smallest mean absolute differences in step count errors. The SEM values ranged from 1.0% (Fitbit One) to 23.5% (Jawbone UP2). Regarding criterion validity, all monitors undercounted the steps. Step count error was affected by the activity monitor (P<.001) and walk interruptions (P=.02). Three monitors had small mean step count errors: Misfit Shine (−1.3%, 95% CI −19.5% to 16.8%), Fitbit One (−2.1%, 95% CI −6.1% to 2.0%), and New-Lifestyles NL-1000 (−4.3%, 95 CI −18.9% to 10.3%). Mean step count error was larger during interrupted walking than continuous walking (−5.5% vs −3.6%; P=.02). Bland-Altman plots illustrated nonsystematic bias and small limits of agreement for Fitbit One and Jawbone UP2. Mean step count error lay within an equivalence bound of ±5% for Fitbit One (P<.001) and Misfit Shine (P=.001). Conclusions Test-retest reliability and criterion validity of step counting varied across 6 consumer-grade activity monitors worn by older adults with self-reported intact and limited mobility. Walk interruptions increased the step count error for all monitors, whereas mobility status did not affect the step count error. The hip-worn Fitbit One was the only monitor with high test-retest reliability and criterion validity.

Associations of Activity Monitor Output and an Estimate of Aerobic Fitness With Pulse Wave Velocities: The Nakanojo Study

2015 ◽  
Vol 12 (1) ◽  
pp. 139-144 ◽  
Author(s):  
Makoto Ayabe ◽  
Sungjin Park ◽  
Roy J. Shephard ◽  
Yukitoshi Aoyagi
Keyword(s):  
Physical Activity ◽  
Arterial Stiffness ◽  
Aerobic Fitness ◽  
Walking Speed ◽  
Pulse Wave ◽  
Activity Monitor ◽  
Step Count ◽  
Daily Step ◽  
Metabolic Equivalents ◽  
Daily Step Count

Background:We examined the relative contributions of habitual physical activity and aerobic fitness to the prevention of arteriosclerosis.Methods:Elderly individuals (97 men and 109 women, aged > 65 y) each wore a uniaxial activity monitor continuously for 1 year, with activity data summarized as an average daily step count and duration of activity > 3 metabolic equivalents (METs). Aerobic fitness was assessed by a standardized 5-m walking test measure of maximal walking speed. Central arterial stiffness was determined using an automatic waveform analyzer measure of cardio-femoral pulse wave velocity (cfPWV).Results:The cfPWV was negatively associated with daily step count, duration of activity > 3 METs, and maximal walking speed (P < .05). Multiple stepwise regression analysis revealed that the step count, duration of activity > 3 METs, and maximal walking speed were all significant predictors of cfPWV, accounting for 11%, 7%, and 4% of total variance, respectively.Conclusions:In contrast to findings from studies using potentially fallible questionnaires, our data suggest that a measure of health (arterial stiffness) is more closely related to objective measures of physical activity than to an estimate of aerobic fitness.

scholarly journals SenseWear Armband and Stroke: Validity of Energy Expenditure and Step Count Measurement during Walking

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Patricia J. Manns ◽  
Robert G. Haennel
Keyword(s):  
Energy Expenditure ◽  
Intraclass Correlation ◽  
Activity Monitor ◽  
Step Count ◽  
Walk Test ◽  
Sensewear Armband ◽  
Six Minute Walk Test ◽  
Metabolic Cart ◽  
Minute Walk ◽  
Significant Underestimation

The purpose of this study was to test the validity of the SenseWear Pro Armband (SWA) for the measurement of energy expenditure (EE) and step count against a criterion in persons with stroke. Twelve participants with chronic stroke (mean age64.2±10.4years; mean gait speed0.67±0.25 m/sec) completed two trials of a six-minute walk test, while wearing a SenseWear Armband (SWA) on each arm and being continuously monitored using a portable metabolic cart. Agreement between estimates of energy expenditure from the SWA and the metabolic cart was fair for the armband on the hemiplegic arm (intraclass correlation cefficient(ICC)=0.586) and good for the armband on the unaffected arm (ICC=0.702). Agreement between the SWA estimate of step count, and step count as measured by the Step Activity Monitor was poor (ICC<0.352), with significant underestimation by the SWA. Our results show that, for these moderately impaired persons with stroke, the SWA should be used with caution for the measurement of energy expenditure and should not be used to measure step count.

scholarly journals Step and Distance Measurement From a Low-Cost Consumer-Based Hip and Wrist Activity Monitor: Protocol for a Validity and Reliability Assessment

10.2196/21262 ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. e21262
Author(s):  
Thomas Carlin ◽  
Nicolas Vuillerme
Keyword(s):  
Walking Speed ◽  
Low Cost ◽  
Activity Monitor ◽  
Distance Measurement ◽  
Step Count ◽  
Mobile Technologies ◽  
Experimental Session ◽  
Validity And Reliability ◽  
Activity Monitors ◽  
Study Results

Background Self-tracking via wearable and mobile technologies is becoming an essential part of personal health management. At this point, however, little information is available to substantiate the validity and reliability of low-cost consumer-based hip and wrist activity monitors, with regard more specifically to the measurements of step counts and distance traveled while walking. Objective The aim of our study is to assess the validity and reliability of step and distance measurement from a low-cost consumer-based hip and wrist activity monitor specific in various walking conditions that are commonly encountered in daily life. Specifically, this study is designed to evaluate whether and to what extent validity and reliability could depend on the sensor placement on the human body and the walking task being performed. Methods Thirty healthy participants will be instructed to wear four PBN 2433 (Nakosite) activity monitors simultaneously, with one placed on each hip and each wrist. Participants will attend two experimental sessions separated by 1 week. During each experimental session, two separate studies will be performed. In study 1, participants will be instructed to complete a 2-minute walk test along a 30-meter indoor corridor under 3 walking speeds: very slow, slow, and usual speed. In study 2, participants will be required to complete the following 3 conditions performed at usual walking speed: walking on flat ground, upstairs, and downstairs. Activity monitor measured step count and distance values will be computed along with the actual step count (determined from video recordings) and distance (measured using a measuring tape) to determine validity and reliability for each activity monitor placement and each walking condition. Results Participant recruitment and data collection began in January 2020. As of June 2020, we enrolled 8 participants. Dissemination of study results in peer-reviewed journals is expected in spring 2021. Conclusions To the best of our knowledge, this is the first study that examines the validity and reliability of step and distance measurement during walking using the PBN 2433 (Nakosite) activity monitor. Results of this study will provide beneficial information on the effects of activity monitor placement, walking speed, and walking tasks on the validity and reliability of step and distance measurement. We believe such information is of utmost importance to general consumers, clinicians, and researchers. International Registered Report Identifier (IRRID) DERR1-10.2196/21262

Characterization of Step Count Accuracy of Actigraph Activity Monitor in Persons With Lower Limb Amputation

2009 ◽  
Vol 21 (4) ◽  
pp. 208-214 ◽  
Author(s):  
Teri G. Rosenbaum Chou ◽  
Joseph B. Webster ◽  
Maryam Shahrebani ◽  
Toni L. Roberts ◽  
Roy D. Bloebaum
Keyword(s):  
Lower Limb ◽  
Activity Monitor ◽  
Lower Limb Amputation ◽  
Step Count ◽  
Limb Amputation

Read, Understand, Learn, & Excel: Development and Testing of an Automated Reading Strategy Detection Algorithm for Postsecondary Students

2019 ◽  
Vol 28 (3) ◽  
pp. 1257-1267 ◽  
Author(s):  
Priya Kucheria ◽  
McKay Moore Sohlberg ◽  
Jason Prideaux ◽  
Stephen Fickas
Keyword(s):  
Academic Success ◽  
Undergraduate Students ◽  
Expository Text ◽  
Reading Strategy ◽  
Detection Algorithm ◽  
Expository Texts ◽  
Human Observer ◽  
Behavioral Strategies ◽  
Periodic Review ◽  
Wide Range

PurposeAn important predictor of postsecondary academic success is an individual's reading comprehension skills. Postsecondary readers apply a wide range of behavioral strategies to process text for learning purposes. Currently, no tools exist to detect a reader's use of strategies. The primary aim of this study was to develop Read, Understand, Learn, & Excel, an automated tool designed to detect reading strategy use and explore its accuracy in detecting strategies when students read digital, expository text.MethodAn iterative design was used to develop the computer algorithm for detecting 9 reading strategies. Twelve undergraduate students read 2 expository texts that were equated for length and complexity. A human observer documented the strategies employed by each reader, whereas the computer used digital sequences to detect the same strategies. Data were then coded and analyzed to determine agreement between the 2 sources of strategy detection (i.e., the computer and the observer).ResultsAgreement between the computer- and human-coded strategies was 75% or higher for 6 out of the 9 strategies. Only 3 out of the 9 strategies–previewing content, evaluating amount of remaining text, and periodic review and/or iterative summarizing–had less than 60% agreement.ConclusionRead, Understand, Learn, & Excel provides proof of concept that a reader's approach to engaging with academic text can be objectively and automatically captured. Clinical implications and suggestions to improve the sensitivity of the code are discussed.Supplemental Materialhttps://doi.org/10.23641/asha.8204786

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