ResProt JMIR Res Protoc JMIR Research Protocols 1929-0748 JMIR Publications Toronto, Canada v10i1e21262 33439138 10.2196/21262 Protocol Protocol Step and Distance Measurement From a Low-Cost Consumer-Based Hip and Wrist Activity Monitor: Protocol for a Validity and Reliability Assessment Eysenbach Gunther Svoboda Zdenek Lim Shannon Carlin Thomas MSc 1 2 https://orcid.org/0000-0001-9058-1723 Vuillerme Nicolas PhD 1
AGEIS University Grenoble Alpes Faculty of Medicine Grenoble, France 33 4 76 63 71 04 nicolas.vuillerme@univ-grenoble-alpes.fr
2 3 https://orcid.org/0000-0003-3773-393X AGEIS University Grenoble Alpes Grenoble France LabCom Telecom4Health University Grenoble Alpes & Orange Labs Grenoble France Institut Universitaire de France Paris France Corresponding Author: Nicolas Vuillerme nicolas.vuillerme@univ-grenoble-alpes.fr 1 2021 13 1 2021 10 1 e21262 9 6 2020 25 6 2020 2 7 2020 14 7 2020 ©Thomas Carlin, Nicolas Vuillerme. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 13.01.2021. 2021

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on http://www.researchprotocols.org, as well as this copyright and license information must be included.

 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

 activity monitor pedometer measurement validity reliability walking step count distance Introduction

Self-tracking via wearable and mobile technologies is becoming an essential part of personal health management [1,2]. In recent years, wearable devices such as those made by Fitbit (eg, One, Flex, Ultra) and ActiGraph (GT9X, GT3X) have been widely introduced into the consumer market as physical activity monitors. The relatively low cost, interface capabilities, ease of use, and wide commercial availability of these devices may ultimately change the way researchers and clinicians alike monitor their patients’ physical activity [3,4] by providing remote access to patient-generated data [5]. In particular, Fitbit [6-14] and ActiGraph [15-25] trackers have received considerable attention.

Depending on the type of activity monitor, companies recommend wearing them at the waist, wrist, pocket, hip, or bra. These wearables devices contain different tools for measurement such as piezoelectric pedometers, single triaxial accelerometers, or inertial measurement unit that combine accelerometers, gyroscopes, and sometimes magnetometers. Using proprietary algorithms, data from measures collected along with information input by the user can estimate steps, distance, physical activity, kilocalories, and sleep [4,5,25,26]. Among these outputs, step and distance measurements while walking remain the most popular and translatable outputs in use today [4,25,27-29].

At this point, it is important to recall that valid and reliable step count and distance estimates are vital output metrics and constitute crucial selection criteria for use in clinical practice [28]. However, little information is available to substantiate the validity and reliability of step and distance measurement from consumer-based hip and wrist activity monitors [26,30,31]. More specifically, despite the increasing number of published works on the evaluation of the most well-known activity monitors [17,25,27,32,33], only a few addressed low-cost activity monitors. For instance, the GT3X (ActiGraph LLC), one of the most well-known and studied accelerometer in research and clinical setting [6-14], costs around €225 (US $250) for one device [34] plus the price of the software and accessories. Fitbit activity trackers also have been the subject of many studies [15-25]; for example, the Charge (Fitbit Inc) costs around €150 (US $170) [35]. This observation is all the more relevant as the selling price is a main barrier to purchase [36]. Indeed, numerous activity monitors available on the market are rather expensive and beyond the financial means of a significant segment of society.

Within this context, 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 to various walking conditions commonly encountered in daily life. This study is designed to evaluate whether and to what extent validity and reliability of step and distance measurement from a consumer-based hip and wrist activity monitor could depend on the sensor placement on the human body and the walking task being performed. Human locomotion in daily life involves walking at non–self-selected speeds, walking upstairs, walking downstairs, turning... in other words, not just straight line walking on flat ground at a comfortable speed. While reliability and validity of activity monitors for walking on flat ground is quite well documented in the growing literature on the subject [20,23,26,37-54], ascending and descending stairs has received less attention [20,23,44-48,50,51,53,55].

 Methods Participants

Young healthy adults aged 18 to 40 years will voluntarily participate to this work. Participants will be recruited in the Grenoble area (France) through open recruitment and direct invitation. From previous similar studies, we have identified that a minimum of 30 participants will be necessary to demonstrate significant differences between the experimental settings [38,47,56,57]. Participants cannot have any history of injury, surgery, or pathology to lower extremities that affects their gait.

The following participant demographic and anthropometric data will be collected: gender, age, body height, body weight, foot length, dominant leg, dominant arm, leg length, arm length, and physical activity level.

Each participant will sign a written informed consent prior to their participation in compliance with the Declaration of Helsinki. This study was approved by the local ethics committee (CER Grenoble Alpes, Avis 2019-04-09-4).

 Materials Activity Monitors

The PBN 2433 (Nakosite USA Ltd) activity monitor has been selected according to previous recommendations that an activity monitor should cost less than €150 (US $185), require no monthly costs for a subscription, provide real-time feedback to the user, and have no chest strap for heart rate measurements [58,59].

The PBN 2433 is a small, inexpensive activity monitor (dimensions: 12 mm × 8 mm × 4 mm; weight: 31.2 g; €15 [US $20]) worn on a wrist band or clipped on the hip. The PBN 2433 tracks step count (total steps per day), calories burned (kcal/day), distance traveled (km/day), and exercise time (h/day). A multiple LCD screen displays direct feedback on outputs. No Bluetooth connection, supplementary app, or mobile or smartphone are needed. It sets up with weight (kg) and stride length (cm). Weight will be obtained by asking participant about their approximative weight. For stride length measurement, participant will be asked to walk 10 steps and the distance traveled will be divided by 10 to obtain an average stride length as is recommended by the manufacturer.

During all experiments, participants will be asked to wear four PBN 2433 activity monitors simultaneously in these locations on their body:

Fitted on the right hip, positioned over the right anterior iliac spine via the manufacturer-provided silicone clip

Fitted on the left hip, positioned over the left anterior iliac spine via the manufacturer-provided silicone clip

Fitted to the right wrist using the manufacturer-provided wristband and positioned on the dorsal aspect of the wrist just proximal to the radial and ulnar processes

Fitted to the left wrist using the manufacturer-provided wristband and positioned on the dorsal aspect of the wrist just proximal to the radial and ulnar processes

 Video Processing

Participants will also be videorecorded with an embedded camera (HERO4, GoPro Inc) fixed on the chest thanks to the dedicated harness. The camera lens will be oriented toward the ground in order to capture all steps taken by the participant. In other words, as previously done by others [19,22,23,30,38,43,45,56,58,60-64], we will use the video-based step count as the gold standard for actual step count. Video-based step counting will be independently conducted by two observers, with a third observer repeating the count in case of discrepancy between obtained step counts [27,28,65,66].

 Experimental Procedure

Participants will attend two similar experimental sessions in an indoor environment separated by 1 week. During each experimental session, two different experiments will be conducted.

In experiment 1, as was previously proposed in published studies designed to evaluate the validity of activity monitors for measuring step counts and distance traveled while walking [18,20,24,54], participants will be required to complete a standard 2-minute walk test during which they will be videotaped. This walking task will be performed in an enclosed, wide, long, flat, 30-m corridor with the instruction to walk back and forth on the course all throughout the 2-minute period. This walking task will be performed under 3 walking speed [67]: (1) very slow walking speed, with the instruction “Walk very slowly”; (2) slow walking speed, with the instruction “Walk a little faster, but slower than normal”; and (3) usual walking speed, with the instruction “Walk at your normal, preferred speed.”

In experiment 2, participants will be videotaped during the walking task performed at usual walking speed under 3 conditions [68,69]: walking on flat ground, walking upstairs, and walking downstairs.

During the walking on flat ground condition, participants will complete a standard 2-minute walk test as proposed in experiment 1. During the walking upstairs condition, participants will be asked to ascend flights of stairs located inside a building stairwell for 2 minutes. During the walking downstairs condition, participants will be asked to descend flights of stairs located inside a building stairwell for 2 minutes. At this point, it is important to mention that handrails do represent important safety features to assist users to maintain their balance and prevent falls on stairs. However, for methodological reasons, participants will not be permitted to use handrails on stairs in the walking upstairs and walking downstairs experimental conditions.

During each experimental session and for each experiment, the order of the 3 experimental conditions will be randomized over participants to reduce potential carryover effects. Only one 2-minute walking trial per condition will be performed. Before to the formal walking trial, participants will complete a practice trial to familiarize themselves with the walking task. A 2-minute rest period will be given between each walking trial in order to record the step and distance counts from each activity monitor. During this period, participants will be instructed to stand still. The number of steps and walking distance measured by each activity monitor will be noted from the tracker display before and immediately after the completion of each trial.

 Statistical Analysis

Descriptive statistics and their corresponding 95% confidence intervals will be determined for all dependent variables. Step count and walking distance errors from each activity monitor will further be calculated as follows:

Step count error = [(steps measured – actual steps) / actual steps] x 100%

Distance error= [(distance measured – actual distance) / actual distance] x 100%

where:

Steps counted and distance measured are the value of steps and distance provided by the activity monitor

Actual steps is the number of steps manually counted from video

Actual distance is the distance measured using a measuring tape

An error score of zero indicates no difference; a positive error score represents an overestimation of the step and distance counts; a negative error score represents an underestimation.

Validity will be determined by comparing the activity monitor outputs (step and walking distance) with the criterion measures (ie, step count determined from video recordings and distance measured using a measuring tape), using mean differences, mean absolute percentage errors (MAPE), and intraclass correlation coefficients (ICC). According to Feito et al [70,71], a MAPE exceeding 5% can be considered as a practically relevant difference. Repeated-measures analysis of variance (ANOVA) will be used to determine whether a significant difference exists between validity of activity monitor placements and walking conditions. In cases when ANOVA shows a significant difference, post hoc analysis will be performed via Bonferroni tests or, when variances is not assumed to be equal, via Games-Howell tests.

The correlation and level of agreement of the steps and distances estimated by the activity monitor to the criterion measures will be further assessed by calculating a Spearman correlation coefficient or Pearson correlation coefficient (r) and ICC, respectively. The parametrical or nonparametrical correlation formula is selected based on the linearity of the relationship between the two measured variables. A correlation coefficient value from .00 to .20 is considered poor, .20 to .40 fair, .40 to .60 moderate, .60 to .80 substantial, and .80 to 1.00 almost perfect [72]. An ICC value from .00 to .40 is considered poor, .40 to .59 fair, .60 to .74 good, and .75 to 1.00 excellent [73]. Bland-Altman plots will further be constructed to visually assess agreement of activity monitor estimates with the criterion measures [74].

Between-day reliability will be determined by calculating ICC between results obtained during session 1 and session 2. We will also compute the mean differences, standard error of measurements, and the MAPE between both experimental sessions. Significant differences between session 1 and session 2 will be determined by paired-sample t test or its nonparametric equivalent, the Wilcoxon signed-rank test. A Bland-Altman plot will be constructed to analyze the agreement between the two assessments.

Statistical significance will be set a priori at P<.05. All statistical calculations will be completed using the R software environment version 3.1.0 (R Foundation for Statistical Computing).

 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.

 Discussion

Physical activity is now widely recognized as crucial for health status maintenance [75-78], whereas physical inactivity has been identified as one of the most important factors in the rise of noncommunicable diseases [78,79]. For these reasons, regular daily physical activity is fully recommended [41,80,81]. It is known that real-time monitoring of physical activity can lead to a perceptible improvement of the physical activity level [2,82-84]. Various activity monitors are available on the market for this purpose. Most of them are designed to measure steps and distance traveled while walking [4,5,26,27]. Although their beneficial effect on health is now well documented [2,82-84], little information is available to substantiate the validity and reliability of step and distance measurement, especially from low-cost consumer-based hip and wrist activity monitors.

To the best of our knowledge, this is the first study that examines the validity and reliability of step and distance measurement during walking conditions using the PBN 2433 activity monitor. To achieve this goal, young healthy participants will be asked to wear four PBN 2433 activity monitors simultaneously, placed on each hip and each wrist. Participants will be also instructed to perform various walking conditions that are commonly encountered in daily life during two experimental sessions.

On the whole, considering the existing literature on the topic, we hypothesize that the validity and reliability of step count and distance output from the PBN 2433 activity monitors will depend on the following factors:

Sensor placement locations on the user’s body [21,38,46,51,85,86]

Walking speed [38,55,87-91]

Walking tasks being performed [23,46,50,55]

Taken together, these will provide beneficial information on the effects of activity monitor placement, walking speed, and walking tasks on validity and reliability of step and distance measurement. We believe that such information is of utmost importance to general consumers, clinicians, and researchers.

 Abbreviations ANOVA

analysis of variance

 ICC

intraclass correlation coefficient

 MAPE

mean absolute percentage error

This work was supported by the French National Research Agency in the framework of the Investissements d’avenir program (ANR-10-AIRT-05 and ANR-15-IDEX-02). The sponsors had no involvement in the study or approval of the manuscript for publication. This work forms part of a broader translational and interdisciplinary project, GaitAlps (NV).

None declared.

 Kumahara H Ishii K Tanaka H Physical activity monitoring for health management: practical techniques and methodological issues Int J Sport Health Sci 2006 4 380 393 10.5432/ijshs.4.380 Bravata DM Smith-Spangler C Sundaram V Gienger AL Lin N Lewis R Stave CD Olkin I Sirard JR Using pedometers to increase physical activity and improve health: a systematic review JAMA 2007 11 21 298 19 2296 2304 10.1001/jama.298.19.2296 18029834 298/19/2296 Bassett DR John D Use of pedometers and accelerometers in clinical populations: validity and reliability issues Physical Therapy Rev 2013 07 19 15 3 135 142 10.1179/1743288x10y.0000000004 Tudor-Locke CE Myers AM Methodological considerations for researchers and practitioners using pedometers to measure physical (ambulatory) activity Res Q Exerc Sport 2001 03 72 1 1 12 10.1080/02701367.2001.10608926 11253314 Tudor-Locke C Lutes L Why do pedometers work? A reflection upon the factors related to successfully increasing physical activity Sports Med 2009 39 12 981 993 10.2165/11319600-000000000-00000 19902981 2 Chomistek A Yuan C Matthews C Troiano R Bowles H Rood J Barnett J Willett W Rimm E Bassett D Physical activity assessment with the ActiGraph GT3X and doubly labeled water Med Sci Sports Exerc 2017 09 49 9 1935 1944 10.1249/MSS.0000000000001299 28419028 PMC5561512 Hänggi JM Phillips LR Rowlands AV Validation of the GT3X ActiGraph in children and comparison with the GT1M ActiGraph J Sci Med Sport 2013 01 16 1 40 44 10.1016/j.jsams.2012.05.012 22749938 S1440-2440(12)00110-7 Kim Y Barry VW Kang M Validation of the ActiGraph GT3X and activPAL accelerometers for the assessment of sedentary behavior Measurement Physical Educ Exercise Sci 2015 08 19 19 3 125 137 10.1080/1091367x.2015.1054390 Romanzini M Petroski EL Ohara D Dourado AC Reichert FF Calibration of ActiGraph GT3X, Actical and RT3 accelerometers in adolescents Eur J Sport Sci 2014 14 1 91 99 10.1080/17461391.2012.732614 24533499 Santos-Lozano A Santín-Medeiros F Cardon G Torres-Luque G Bailón R Bergmeir C Ruiz JR Lucia A Garatachea N Actigraph GT3X: validation and determination of physical activity intensity cut points Int J Sports Med 2013 11 34 11 975 982 10.1055/s-0033-1337945 23700330 Santos-Lozano A Torres-Luque G Marín P J Ruiz J Lucia A Garatachea N Intermonitor variability of GT3X accelerometer Int J Sports Med 2012 12 33 12 994 999 10.1055/s-0032-1312580 22791617 Santos-Lozano A Marín P Torres-Luque G Ruiz JR Lucía A Garatachea N Technical variability of the GT3X accelerometer Med Eng Phys 2012 07 34 6 787 790 10.1016/j.medengphy.2012.02.005 22417978 S1350-4533(12)00029-X Wanner M Martin BW Meier F Probst-Hensch N Kriemler S Effects of filter choice in GT3X accelerometer assessments of free-living activity Med Sci Sports Exerc 2013 01 45 1 170 177 10.1249/MSS.0b013e31826c2cf1 22895373 García-Massó X Serra-Añó P García-Raffi LM Sánchez-Pérez EA López-Pascual J Gonzalez LM Validation of the use of Actigraph GT3X accelerometers to estimate energy expenditure in full time manual wheelchair users with spinal cord injury Spinal Cord 2013 12 51 12 898 903 10.1038/sc.2013.85 23999111 sc201385 Haghayegh S Khoshnevis S Smolensky MH Diller KR Castriotta RJ Accuracy of wristband Fitbit models in assessing sleep: systematic review and meta-analysis J Med Internet Res 2019 11 28 21 11 e16273 10.2196/16273 31778122 v21i11e16273 PMC6908975 Gorny AW Liew SJ Tan CS Müller-Riemenschneider F Fitbit Charge HR wireless heart rate monitor: validation study conducted under free-living conditions JMIR Mhealth Uhealth 2017 10 20 5 10 e157 10.2196/mhealth.8233 29055881 v5i10e157 PMC5670315 Feehan LM Geldman J Sayre EC Park C Ezzat AM Yoo JY Hamilton CB Li LC Accuracy of Fitbit devices: systematic review and narrative syntheses of quantitative data JMIR Mhealth Uhealth 2018 08 09 6 8 e10527 10.2196/10527 30093371 v6i8e10527 PMC6107736 Haegele J Brian A Wolf D Accuracy of the Fitbit Zip for measuring steps for adolescents with visual impairments Adapt Phys Activ Q 2017 04 34 2 195 200 10.1123/apaq.2016-0055 28556761 Diaz KM Krupka DJ Chang MJ Peacock J Ma Y Goldsmith J Schwartz JE Davidson KW Fitbit: An accurate and reliable device for wireless physical activity tracking Int J Cardiol 2015 04 15 185 138 140 10.1016/j.ijcard.2015.03.038 25795203 S0167-5273(15)00276-4 PMC4406840 Chandrasekar A Hensor EM Mackie SL Backhouse MR Harris E Preliminary concurrent validity of the Fitbit-Zip and ActiGraph activity monitors for measuring steps in people with polymyalgia rheumatica Gait Posture 2018 03 61 339 345 10.1016/j.gaitpost.2018.01.035 29427859 S0966-6362(18)30046-8 Kooiman TJM Dontje ML Sprenger SR Krijnen WP van der Schans CP de Groot M Reliability and validity of ten consumer activity trackers BMC Sports Sci Med Rehabil 2015 10 7 24 10.1186/s13102-015-0018-5 26464801 18 PMC4603296 Wong CK Mentis HM Kuber R The bit doesn’t fit: evaluation of a commercial activity-tracker at slower walking speeds Gait Posture 2018 01 59 177 181 10.1016/j.gaitpost.2017.10.010 Huang Y Xu J Yu B Shull PB Validity of FitBit, Jawbone UP, Nike+ and other wearable devices for level and stair walking Gait Posture 2016 07 48 36 41 10.1016/j.gaitpost.2016.04.025 Paul SS Tiedemann A Hassett LM Ramsay E Kirkham C Chagpar S Sherrington C Validity of the activity tracker for measuring steps in community-dwelling older adults BMJ Open Sport Exerc Med 2015 07 1 1 e000013 10.1136/bmjsem-2015-000013 27900119 bmjsem-2015-000013 PMC5117050 Evenson KR Goto MM Furberg RD Systematic review of the validity and reliability of consumer-wearable activity trackers Int J Behav Nutr Phys Act 2015 12 1 159 10.1186/s12966-015-0314-1 26684758 10.1186/s12966-015-0314-1 PMC4683756 An H Jones GC Kang S Welk GJ Lee J How valid are wearable physical activity trackers for measuring steps? Eur J Sport Sci 2017 04 17 3 360 368 10.1080/17461391.2016.1255261 27912681 Bassett DR Toth LP LaMunion SR Crouter SE Step counting: a review of measurement considerations and health-related applications Sports Med 2017 07 47 7 1303 1315 10.1007/s40279-016-0663-1 28005190 10.1007/s40279-016-0663-1 PMC5488109 Saint-Maurice PF Troiano RP Bassett DR Graubard BI Carlson SA Shiroma EJ Fulton JE Matthews CE Association of daily step count and step intensity with mortality among US adults JAMA 2020 03 24 323 12 1151 1160 10.1001/jama.2020.1382 32207799 2763292 PMC7093766 O'Driscoll R Turicchi J Beaulieu K Scott S Matu J Deighton K Finlayson G Stubbs J How well do activity monitors estimate energy expenditure? A systematic review and meta-analysis of the validity of current technologies Br J Sports Med 2020 03 54 6 332 340 10.1136/bjsports-2018-099643 30194221 bjsports-2018-099643 Alinia P Cain C Fallahzadeh R Shahrokni A Cook D Ghasemzadeh H How accurate is your activity tracker? A comparative study of step counts in low-intensity physical activities JMIR Mhealth Uhealth 2017 08 11 5 8 e106 10.2196/mhealth.6321 28801304 v5i8e106 PMC5572056 Thorup CB Andreasen JJ Sørensen EE Grønkjær M Dinesen BI Hansen J Accuracy of a step counter during treadmill and daily life walking by healthy adults and patients with cardiac disease BMJ Open 2017 03 31 7 3 e011742 10.1136/bmjopen-2016-011742 Corder K Brage S Ekelund U Accelerometers and pedometers: methodology and clinical application Curr Opin Clin Nutr Metab Care 2007 09 10 5 597 603 10.1097/MCO.0b013e328285d883 17693743 00075197-200709000-00006 Kenyon A McEvoy M Sprod J Maher C Validity of pedometers in people with physical disabilities: a systematic review Arch Phys Med Rehabil 2013 06 94 6 1161 1170 10.1016/j.apmr.2012.11.030 23201318 S0003-9993(12)01193-8 McMinn D Acharya R Rowe D Gray S Allan J Measuring activity energy expenditure: accuracy of the GT3X+ and Actiheart monitors Int J Exerc Sci 2013 6 3 5 Ricchio K Lyter-Antonneau PM Reliability of fitness trackers at different prices for measuring steps and heart rate: a pilot study Centr Eur J Sport Sci Med 2018 24 57 64 10.18276/cej.2018.4-06 Gualtieri L Rosenbluth S Phillips J Can a free wearable activity tracker change behavior? The impact of trackers on adults in a physician-led wellness group JMIR Res Protoc 2016 11 30 5 4 e237 10.2196/resprot.6534 27903490 v5i4e237 PMC5156822 Fortune E Lugade V Morrow M Kaufman K Validity of using tri-axial accelerometers to measure human movement - part II: step counts at a wide range of gait velocities Med Eng Phys 2014 06 36 6 659 669 10.1016/j.medengphy.2014.02.006 24656871 S1350-4533(14)00028-9 PMC4030415 Ehrler F Weber C Lovis C Influence of pedometer position on pedometer accuracy at various walking speeds: a comparative study J Med Internet Res 2016 10 06 18 10 e268 10.2196/jmir.5916 27713114 v18i10e268 PMC5073206 Beltrán-Carrillo VJ Jiménez-Loaisa A Alarcón-López M Elvira JLL Validity of the "Samsung Health" application to measure steps: a study with two different samsung smartphones J Sports Sci 2019 04 37 7 788 794 10.1080/02640414.2018.1527199 30332917 Dowd KP Harrington DM Donnelly AE Criterion and concurrent validity of the activPAL™ professional physical activity monitor in adolescent females PLoS One 2012 7 10 e47633 10.1371/journal.pone.0047633 23094069 PONE-D-12-13369 PMC3477132 Powell KE Paluch AE Blair SN Physical activity for health: What kind? How much? How intense? On top of what? Annu Rev Public Health 2011 32 349 365 10.1146/annurev-publhealth-031210-101151 21128761 Hergenroeder AL Barone Gibbs B Kotlarczyk MP Perera S Kowalsky RJ Brach JS Accuracy and acceptability of commercial-grade physical activity monitors in older adults J Aging Phys Act 2019 04 01 27 2 222 229 10.1123/japa.2018-0036 30117355 PMC7023914 Simpson L Eng J Klassen T Lim S Louie D Parappilly B Sakakibara B Zbogar D Capturing step counts at slow walking speeds in older adults: comparison of ankle and waist placement of measuring device J Rehabil Med 2015 10 05 47 9 830 835 10.2340/16501977-1993 26181670 Leicht AS Crowther RG Influence of non-level walking on pedometer accuracy J Sci Med Sport 2009 05 12 3 361 365 10.1016/j.jsams.2008.01.007 18356103 S1440-2440(08)00008-X O'Connell S ÓLaighin G Kelly L Murphy E Beirne S Burke N Kilgannon O Quinlan LR These shoes are made for walking: sensitivity performance evaluation of commercial activity monitors under the expected conditions and circumstances required to achieve the international daily step goal of 10,000 steps PLoS One 2016 11 5 e0154956 10.1371/journal.pone.0154956 27167121 PONE-D-15-48144 PMC4864247 Horvath S Taylor DG Marsh JP Kriellaars DJ The effect of pedometer position and normal gait asymmetry on step count accuracy Appl Physiol Nutr Metab 2007 06 32 3 409 415 10.1139/H07-001 17510675 h07-001 Chen M Kuo C Pellegrini C Hsu M Accuracy of wristband activity monitors during ambulation and activities Med Sci Sports Exerc 2016 10 48 10 1942 1949 10.1249/MSS.0000000000000984 27183123 Magistro D Brustio PR Ivaldi M Esliger DW Zecca M Rainoldi A Boccia G Validation of the ADAMO Care Watch for step counting in older adults PLoS One 2018 13 2 e0190753 10.1371/journal.pone.0190753 29425196 PONE-D-17-15209 PMC5806873 Martin JB Krč KM Mitchell EA Eng JJ Noble JW Pedometer accuracy in slow walking older adults Int J Ther Rehabil 2012 07 03 19 7 387 393 10.12968/ijtr.2012.19.7.387 24795762 PMC4008448 Hazell TJ Ellery CV Cohen TR Vanstone CA Rodd CJ Weiler HA Assessment of pedometer accuracy in capturing habitual types of physical activities in overweight and obese children Pediatr Res 2016 11 80 5 686 692 10.1038/pr.2016.133 27486704 pr2016133 Battenberg AK Donohoe S Robertson N Schmalzried TP The accuracy of personal activity monitoring devices Sem Arthroplasty 2017 06 28 2 71 75 10.1053/j.sart.2017.07.006 Xie J Wen D Liang L Jia Y Gao L Lei J Evaluating the validity of current mainstream wearable devices in fitness tracking under various physical activities: comparative study JMIR Mhealth Uhealth 2018 04 12 6 4 e94 10.2196/mhealth.9754 29650506 v6i4e94 PMC5920198 Kaewkannate K Kim S A comparison of wearable fitness devices BMC Public Health 2016 12 24 16 433 10.1186/s12889-016-3059-0 27220855 10.1186/s12889-016-3059-0 PMC4877805 Fulk GD Combs SA Danks KA Nirider CD Raja B Reisman DS Accuracy of 2 activity monitors in detecting steps in people with stroke and traumatic brain injury Phys Ther 2014 02 94 2 222 229 10.2522/ptj.20120525 24052577 ptj.20120525 Steeves J Tyo B Connolly C Gregory D Stark N Bassett D Validity and reliability of the Omron HJ-303 tri-axial accelerometer-based pedometer J Phys Act Health 2011 09 8 7 1014 1020 10.1123/jpah.8.7.1014 21885893 O'Connell S ÓLaighin G Quinlan LR When a step is not a step! Specificity analysis of five physical activity monitors PLoS One 2017 12 1 e0169616 10.1371/journal.pone.0169616 28085918 PONE-D-16-29880 PMC5234787 Fokkema T Kooiman T Krijnen W Van der Schans CP De Groot M Reliability and validity of ten consumer activity trackers depend on walking speed Med Sci Sports Exerc 2017 04 49 4 793 800 10.1249/MSS.0000000000001146 28319983 00005768-201704000-00021 Ummels D Beekman E Theunissen K Braun S Beurskens AJ Counting steps in activities of daily living in people with a chronic disease using nine commercially available fitness trackers: cross-sectional validity study JMIR Mhealth Uhealth 2018 04 02 6 4 e70 10.2196/mhealth.8524 29610110 v6i4e70 PMC5902695 Beekman E Braun SM Ummels D van Vijven K Moser A Beurskens AJ Validity, reliability and feasibility of commercially available activity trackers in physical therapy for people with a chronic disease: a study protocol of a mixed methods research Pilot Feasibility Stud 2017 3 64 10.1186/s40814-017-0200-5 29204293 200 PMC5701363 Klassen TD Simpson LA Lim SB Louie DR Parappilly B Sakakibara BM Zbogar D Eng JJ “Stepping up” activity poststroke: ankle-positioned accelerometer can accurately record steps during slow walking Phys Ther 2016 03 96 3 355 360 10.2522/ptj.20140611 26251478 ptj.20140611 PMC4774387 Lauritzen J Muñoz A Luis Sevillano J Civit A The usefulness of activity trackers in elderly with reduced mobility: a case study Stud Health Technol Inform 2013 192 759 762 23920659 Toth LP Park S Springer CM Feyerabend MD Steeves JA Bassett DR Video-recorded validation of wearable step counters under free-living conditions Med Sci Sports Exerc 2018 06 50 6 1315 1322 10.1249/MSS.0000000000001569 29381649 Tophøj KH Petersen MG Sæbye C Baad-Hansen T Wagner S Validity and reliability evaluation of four commercial activity trackers' step counting performance Telemed J E Health 2018 09 24 9 669 677 10.1089/tmj.2017.0264 29303680 McCullagh R Dillon C O'Connell AM Horgan NF Timmons S Step-count accuracy of 3 motion sensors for older and frail medical inpatients Arch Phys Med Rehabil 2017 02 98 2 295 302 10.1016/j.apmr.2016.08.476 27666157 S0003-9993(16)30981-9 Shephard RJ Limits to the measurement of habitual physical activity by questionnaires—commentary Br J Sports Med 2003 06 37 3 197 206 10.1136/bjsm.37.3.197 12782543 PMC1724653 Witt DR Kellogg RA Snyder MP Dunn J Windows into human health through wearables data analytics Curr Opin Biomed Eng 2019 03 9 28 46 10.1016/j.cobme.2019.01.001 31832566 PMC6907085 Eppeland S Myklebust G Hodt-Billington C Moe-Nilssen R Gait patterns in subjects with rheumatoid arthritis cannot be explained by reduced speed alone Gait Posture 2009 04 29 3 499 503 10.1016/j.gaitpost.2008.11.010 19121943 S0966-6362(08)00379-2 Ayabe M Aoki J Ishii K Takayama K Tanaka H Pedometer accuracy during stair climbing and bench stepping exercises J Sports Sci Med 2008 7 2 249 254 24149457 PMC3761450 Huang Y Xu J Yu B Shull PB Validity of FitBit, Jawbone UP, Nike+ and other wearable devices for level and stair walking Gait Posture 2016 07 48 36 41 10.1016/j.gaitpost.2016.04.025 Feito Y Bassett DR Thompson DL Evaluation of activity monitors in controlled and free-living environments Med Sci Sports Exerc 2012 04 44 4 733 741 10.1249/MSS.0b013e3182351913 21904249 Feito Y Garner HR Bassett DR Evaluation of ActiGraph's low-frequency filter in laboratory and free-living environments Med Sci Sports Exerc 2015 01 47 1 211 217 10.1249/MSS.0000000000000395 24870583 Landis JR Koch GG The measurement of observer agreement for categorical data Biometrics 1977 03 33 1 159 174 843571 Fleiss J Levin B Paik M Statistical Methods for Rates and Proportions. 3rd Edition 2003 Hoboken Wiley-Interscience Bland JM Altman D Statistical methods for assessing agreement between two methods of clinical measurement Lancet 1986 03 08 1 8476 307 310 2868172 S0140-6736(86)90837-8 Althoff T Sosič R Hicks JL King AC Delp SL Leskovec J Large-scale physical activity data reveal worldwide activity inequality Nature 2017 07 20 547 7663 336 339 10.1038/nature23018 28693034 nature23018 Heath GW Parra DC Sarmiento OL Andersen LB Owen N Goenka S Montes F Brownson RC Lancet Physical Activity Series Working Group Evidence-based intervention in physical activity: lessons from around the world Lancet 2012 07 21 380 9838 272 281 10.1016/S0140-6736(12)60816-2 22818939 S0140-6736(12)60816-2 PMC4978123 Ekelund U Steene-Johannessen J Brown WJ Fagerland MW Owen N Powell KE Bauman A Lee I Does physical activity attenuate, or even eliminate, the detrimental association of sitting time with mortality? A harmonised meta-analysis of data from more than 1 million men and women Lancet 2016 09 388 10051 1302 1310 10.1016/S0140-6736(16)30370-1 Kohl HW Craig CL Lambert EV Inoue S Alkandari JR Leetongin G Kahlmeier S The pandemic of physical inactivity: global action for public health Lancet 2012 07 21 380 9838 294 305 10.1016/S0140-6736(12)60898-8 22818941 S0140-6736(12)60898-8 Lee I Shiroma EJ Lobelo F Puska P Blair SN Katzmarzyk PT Lancet Physical Activity Series Working Group Effect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy Lancet 2012 07 21 380 9838 219 229 10.1016/S0140-6736(12)61031-9 22818936 S0140-6736(12)61031-9 PMC3645500 Westerterp KR Pattern and intensity of physical activity Nature 2001 03 29 410 6828 539 10.1038/35069142 11279482 35069142 Global Advocacy Council for Physical Activity International Society for Physical Activity and Health The Toronto charter for physical activity: a global call for action J Phys Act Health 2010 11 7 Suppl 3 S370 S385 10.1123/jpah.7.s3.s370 21116016 Bird EL Baker G Mutrie N Ogilvie D Sahlqvist S Powell J Behavior change techniques used to promote walking and cycling: a systematic review Health Psychol 2013 08 32 8 829 838 10.1037/a0032078 23477577 2013-07768-001 PMC3727344 Kang M Marshall SJ Barreira TV Lee J Effect of pedometer-based physical activity interventions: a meta-analysis Res Q Exerc Sport 2009 09 80 3 648 655 10.1080/02701367.2009.10599604 19791652 Kanejima Y Kitamura M Izawa KP Self-monitoring to increase physical activity in patients with cardiovascular disease: a systematic review and meta-analysis Aging Clin Exp Res 2018 04 30 31 2 163 173 10.1007/s40520-018-0960-7 29714027 10.1007/s40520-018-0960-7 Graser S Pangrazi R Vincent W Effects of placement, attachment, and weight classification on pedometer accuracy J Phys Act Health 2007 10 4 4 359 369 10.1123/jpah.4.4.359 18209228 Sears T Avalos E Lawson S Eschbach C Bunn J Wrist-worn physical activity trackers tend to underestimate steps during walking Int J Exerc Sci 2017 10 5 764 773 Beevi FH Miranda J Pedersen CF Wagner S An evaluation of commercial pedometers for monitoring slow walking speed populations Telemed J E Health 2016 05 22 5 441 449 10.1089/tmj.2015.0120 26451900 Giannakidou DM Kambas A Ageloussis N Fatouros I Christoforidis C Venetsanou F Douroudos I Taxildaris K The validity of two Omron pedometers during treadmill walking is speed dependent Eur J Appl Physiol 2012 01 112 1 49 57 10.1007/s00421-011-1951-y 21479653 Melanson EL Knoll JR Bell ML Donahoo WT Hill J Nysse LJ Lanningham-Foster L Peters JC Levine JA Commercially available pedometers: considerations for accurate step counting Prev Med 2004 08 39 2 361 368 10.1016/j.ypmed.2004.01.032 15226047 S0091743504000714 Presset B Laurenczy B Malatesta D Barral J Accuracy of a smartphone pedometer application according to different speeds and mobile phone locations in a laboratory context J Exerc Sci Fit 2018 08 16 2 43 48 10.1016/j.jesf.2018.05.001 30662492 S1728-869X(17)30316-7 PMC6323165 Washburn R Chin MK Montoye HJ Accuracy of pedometer in walking and running Res Q Exerc Sport 1980 12 51 4 695 702 10.1080/02701367.1980.10609330 7209126