Systematic Review of Fitbit Charge 2 Validation Studies for Exercise Tracking : Translational Journal of the American College of Sports Medicine

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Review Article

Systematic Review of Fitbit Charge 2 Validation Studies for Exercise Tracking

Irwin, Crista; Gary, Rebecca

Author Information
Translational Journal of the ACSM: Fall 2022 - Volume 7 - Issue 4 - p 1-7
doi: 10.1249/TJX.0000000000000215
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Abstract

INTRODUCTION

Background

Current universal guidelines recommend at least 150 min of weekly moderate-intensity exercise of between 3 and 6 metabolic equivalent of task for persons across the health strata (1). Moderate-intensity exercise can be achieved by brisk walking at a pace of 100 steps per minute or measured at 60%–70% of heart rate (HR) maximum (2). Persons with chronic conditions who routinely participate in physical activity at moderate intensity for a minimum of 150 min·wk−1 exhibit significant improvements in cardiovascular function and reduction in inflammation (1,3–12). Incorporating exercise prescriptions into healthcare protocols show major benefits among a variety of health conditions including cardiovascular disease, depression, and HIV, as well as for preventative medicine (13). Providers need cost-effective, reliable wearable devices that accurately measure physical activity to assess and provide feedback to patients regarding their physical activity and to fully utilize the benefits of an exercise prescription.

Current research-grade devices have been validated to measure either HR using electrocardiography (ECG) (14), step count using an ActiGraph accelerometer (15), or sensing HR pulse using a Polar chest strap (16), but to date, no wearable device has been validated to measure both HR and steps concurrently. Exercise equipment manufacturers continuously develop multifunction activity trackers worn as watches that purport to accurately capture steps and HR; however, these wearable activity trackers have been tested against research-grade accelerometers and HR monitors with variable results. The Fitbit Charge 2 (FBC2; Fitbit Inc., San Francisco, CA) is a low-cost, wearable device that tracks steps and HR and has been studied in a variety of populations in home-based and healthcare settings. The purpose of this review is to examine validation studies of the FBC2 for accurately measuring HR and step count and to evaluate the device’s reliability to determine whether the device can be recommended by healthcare providers for use by patients.

Features of the FBC2

Fitbit trackers use microelectronic triaxial accelerometer and proprietary algorithms to measure step gait and distance and continuous light-emitting diode (LED) lighting to measure pulse continually. They are multifunctional, wrist-worn devices that not only measure steps and HR but include a multitude of user-friendly features. The device must be wirelessly connected via Bluetooth to a network-connected mobile phone. Through this connectivity, the device may receive text and call notifications. The device may be connected to the owner’s contact list to develop community support networks for exercise motivation with special permission. The device software often sends supportive messages to encourage movement throughout the day or once the owner achieves personal activity goals set by him/herself. The software package also includes workout videos that can be accessed on the mobile phone application. The device also functions as a watch and has timer, mileage, relaxation, and stopwatch features.

Limitations of the FBC2

Because the device requires smart phone and Internet access and has an average price of $150, the FBC2 may be a difficult option for low-income populations. Many basic and low-functioning mobile phones lack the capability to support the Fitbit application. The watch is rechargeable and includes a charging cord, which is easily misplaced and/or broken, and needs 6- to 7-h charging time, which lasts for approximately 3–4 d. Consumers report frequent watchband and equipment failure after 12–18 months of use. In addition, the manufacturer does not report whether the updated models, which are released about every 18 months, have been altered significantly and therefore require updated testing and validation.

METHODS

Design

This review was registered on the International Prospective Register of Systematic Reviews (PROSPERO), and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were used in conducting the review and reporting the appropriate articles (17). Fig. 1 illustrates the PRISMA flow diagram of included articles. Eight articles on the validation of FBC2 in adult ambulatory populations that were published between 2018 and 2019 were examined for this review. Seven of the articles were randomized control trials, and one was a test of a single participant who wore multiple trackers. Articles were excluded if they did not assess the FBC2 model or did not assess HR or step counts, or if the population sample was younger than 18 yr. The relatively small article publication time range is due in part to the speed at which commercially available wearable exercise tracker technology changes.

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Figure 1:
PRISMA flow diagram for systematic review of FBC2 validation studies. CINHL, Cumulative Index to Nursing and Allied Health Literature; FB, Fitbit.

Strategy

The methods for this review included a search of PubMed, the Cumulative Index to Nursing and Allied Health Literature, Cochran, Embase, World of Science, hand searches, and assistance by Emory University’s Health Sciences Librarian. Key words and combinations of words used in the search were “Fitbit Charge 2,” “exercise tracker,” “activity tracker,” “activity monitor,” “heart rate,” “steps,” and “validation.” Article inclusion criteria were HR and/or steps validation studies for the FBC2 in adult ambulatory populations.

Data Extraction

Each validation article included in this review was required to assess HR and step count accuracy. Articles were also included if they evaluated intrareliability testing between the FBC2 trackers used in the testing as well as interreliability among other trackers assessed. Criterion measures for HR were based on the research-validated ECG and the Polar chest strap for ambulatory activities (14,15). Step count data were compared with the validated ActiGraph wGT3X-BT (16).

To assess the tracker’s accuracy, seven of the eight studies in this review explained the differences in the data collected by the FBC2 using the following measures (Table 1): mean error, as in the difference between the criterion measure and the consumer device; mean absolute error, as in the average absolute distance between the data from the consumer and the criterion devices; mean percent error or relative error rate (RER), as in the difference between the criterion measure and the consumer device, represented by a percentage; and mean absolute percent error (MAPE), as in the average of the individual absolute percent errors. MAPE analyzes individual overestimation and underestimation values taken by the device and therefore may be a more appropriate representation of the activity monitors when comparing studies.

TABLE 1 - Summary of Measurements.
Study Author, Year Criterion Measure HR Steps CCC ICC PC BA ME MAE MPE/RER MAPE Risk of Bias
Hwang et at., 2019 (18) ECG X X X Low
Klepin et at., 2019 (19) V̇O2max X X X Some concerns
Nelson and Allen, 2019 (20) ECG X X X X X Some concerns
O’Driscoll et al., 2019 (21) Polar chest strap X X X X X Low
Reddy et al., 2018 (22) Polar chest strap X X X X X X Low
Tedesco et al., 2019 (23) ActiGraph wGT3X-BT and New-Lifestyles NL2000i X X X X X Low
Thomson et al., 2019 (24) ECG X X X X Low
Vetrovsky et al., 2019 (25) ActiGraph wGT3X-BT X X X Low
BA, Bland–Altman analysis; MAE, mean absolute error; ME, mean error; MPE, mean percent error; PC, Pearson correlation.

Concordance correlation coefficient (CCC) 95% confidence intervals (CI) were used to describe the strength of agreement between the devices in four studies (20,22,24). Interclass correlation coefficient (ICC) was used when comparing multiple devices with each other and with the criterion. In addition, because precise data congruency collected between consumer devices is unlikely, Bland–Altman analysis was used by four studies to evaluate proximity to data measured by criterion devices (18,20,21,24).

Another article was included in this validation review because the authors tested the FBC2 tracker’s accuracy for measuring cardiorespiratory fitness (CRF) compared with maximal oxygen uptake (V̇O2max) (26). CRF, defined as the circulatory and respiratory systems’ transport and utilization of oxygen to the skeletal muscles, is typically measured by maximal graded exercise testing on a treadmill and measured in units of mL·kg−1·min−1. Under strict laboratory protocols by a trained exercise physiologist using precise equipment, the gold standard for evaluating CRF levels is by V̇O2max (19). Researchers have found that low levels of CRF measured by V̇O2max treadmill testing have been associated with cardiovascular disease risk (26–28). The FBC2 purports to evaluate CRF using proprietary algorithms, which include an individual user’s age, weight, height, resting HR, and peak HR.

Articles were evaluated by two independent researchers, and inclusion agreement was discussed in detail. Validation articles included in this review are listed and described in Tables 1 and 2.

TABLE 2 - Summary of Study Findings.
Study Author, Year Sample Population Design/Methods Summary of Findings
Hwang et at., 2019 (18) N = 51, mean (SD) age: 44.4 (16.6) yr, n = 24 female, Korean Compared FBC2 with ECG; participants with history of paroxysmal SVT were undergoing electrophysiological study; baseline HR during induced SVT and postablation of SVT were measured FBC2 accurately measured HR (94%) compared with ECG
Klepin et at., 2019 (19) N = 60, mean (SD) age: 31 (7.3) yr, n = 33 female, race not reported Compared FBC2 with V̇O2max; all healthy adults; study duration: 1 wk; 3 GPS tracked 15-min outdoor runs and were worn continuously FBC2 60-s CRF: highly associated with V̇O2max; MAPE: 9.14%
Nelson and Allen, 2019 (20) N = 1, age: 29 yr, White male Compared FBC2 with ECG; single subject, healthy adult male, used to minimize variable differences; 24-h data collected across sedentary, walking, running, ADL, and sleeping FBC2 mean difference: −3.47 bpm compared with criterion and comparable tracker; MAE: 5.96%, CCC: 91% compared with ECG over 24 h, MAPE: 9.21% walking
O’Driscoll et al., 2019 (21) N = 59, mean (SD) age: 44.2 (14.1) yr, n = 41 female, European Compared FBC2 with Polar chest strap; activities evaluated in a 1-d laboratory setting included running, walking, cycling, mimicked ADL, and sedentary conditions with rest periods between FBC2 HR = CM, but not consistent across activity levels; MAPE: 31% walking incline; MAPE: 69% walking
Reddy et al., 2018 (22) N = 20, mean (SD) age: 27.5 (6.0) yr, n = 11 female, n = 17 (85%) White Compared FBC2 with Polar chest strap; 2-d data collection; all healthy adults; V̇O2max testing included resistance exercise, interval training, and ADL conditions FBC2 > error high-intensity exercise; MAPE: 10.79%
Tedesco et al., 2019 (23) N = 20, mean (SD) age: 70.2 (2.9) yr, n = 11 female, all White (English/Irish) Compared FBC2 with ActiGraph; 24-h free-living data collection; all older, healthy adults; activities assessed included a range of moderate to vigorous walking and sleeping conditions All devices highly correlated (ICC >0.89); FBC2 overcounted steps; MAPE: 12.36%
Thomson et al., 2019 (24) N = 30, mean (SD) age: 23.5 (3) yr, n = 15 female, race not reported Compared FBC2 with ECG; measurements taken at intervals: rest (3 min), standing (2 min), treadmill (every 3 min with gradual speed and uphill increase until volitional fatigue), recovery FBC2 error rate (3.9%–13.5%). RER per activity level: light (5.36%), moderate (9.20%), vigorous (11%)
Vetrovsky et al., 2019 (25) Healthy control participants: n = 15, mean (SD) age: 65.5 (12.6) yr, n = 6 female;
HF field-based study: n = 14, mean (SD) age: 43.3 (18.9) yr, n = 9 female (Czech Republic)
Compared FBC2 with accelerometer; main purpose was to evaluate step accuracy of activity trackers in persons with HF; laboratory and field study FBC2 healthy participants MAPE: 12%; HF study MAPE: 46%; >correlation low speeds on treadmill
ADL, activities of daily living; GPS, Global Positioning System; SVT, supraventricular tachyarrhythmia.

Risk-of-Bias Assessment

Each study was evaluated for risk of bias (Table 2). Criteria used for the assessment included randomization bias, recruitment bias, protocol deviation bias including criterion tool bias, missing outcome bias, and reporting bias. The selected studies were consistently evaluated as high quality based on these criteria with few concerns for risk of bias. Most of the concerns were regarding racially homogenous or small samples. One study included a single participant, and most of the studies included majority White persons and healthy populations. The risk-of-bias visualization tool (robvis; Bristol, AC, United Kingdom) was used to create the risk of bias assessment (Fig. 2) (29).

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Figure 2:
Risk-of-bias assessment.

RESULTS

Accuracy Testing

Of the eight studies found, five reported MAPE values of the FBC2 against the criterion for each study, which are considered acceptable at <10%. The MAPE values for the studies evaluating HR accuracy include 9.21% (20), 10.79% (22), and 69% (21). MAPE values investigating step count acuity were 12.36% (23), 46% for participants with heart failure (HF), and 12% among healthy controls (25). Another study measured the HR difference between the FBC2 and the criterion using RER (light activity, 5.36%, to moderate activity, 9.3%) (24).

Intrareliability Testing

A 24-h evaluation study found 91% CCC (95% CI: 0.896–0.914) agreement of the criterion with the FBC2 in a single participant (male, age 29 yr) (20). Another study cited 92% CCC (95% CI: 0.92–0.93) agreement of the criterion with the FBC2 in their randomized controlled trial including 20 participants (mean (SD) age: 27.5 (6) yr; 55% female) while walking on a treadmill (22). In addition, researchers collected data from 30 participants (mean (SD) age: 23.5 (3) yr; 50% female) and found that, as exercise intensity increased, agreement decreased (24). At very low HR, intensity ranging between 55 and 90 bpm, CCC agreement between the criterion and the FBC2 was 89% (95% CI: 0.79–0.95) (24). When HR ranged between 90 and 120 bpm, CCC agreement was moderate at 55% (96% CI: 0.28–0.74) and CCC was poor at 26% (95% CI: 0.01–0.46) when HR ranged between 110 and 150 bpm (24). In contrast, step counting criterion reliability increased with treadmill speeds in a 3-d field study of 15 participants (mean (SD) age: 65.5 (12.6) yr; 40% female) with HF compared with 14 (mean (SD) age: 43 (18.9) yr; 64% female) healthy controls (25). CCC agreement of the step criterion with the FBC2 was 38% (95% CI: 0.00–0.67) at 2.4 km·h−1 (slow walk), 82% (95% CI: 0.68–0.97) at 3.0 km·h−1 (moderate walk), and 99% (95% CI: 0.98–1.0) at 3.6 km·h−1 (brisk walk) (25).

Interreliability Testing

In a 24-h study of 20 (mean (SD) age: 70.2 (2.9) yr; 55% female) older healthy adults in Ireland, results showed >0.89 ICC strength of agreement between devices for step count evaluation (23). In addition, a study from Korea including 51 participants (mean (SD) age: 44.4 (16.6) yr; 53% male; 100% Asian) who were undergoing electrophysiological study and ablation to treat paroxysmal tachycardia or supraventricular tachycardia found >0.98 ICC strength of agreement between the FBC2 and the ECG for HR monitoring (18). Recorded baseline HR monitoring with the FBC2 was within ±5 bpm of the criterion ECG at 95% accuracy (18). However, device agreement of the FBC2 and criterion results by Pearson correlations assessed in other studies in the review were incongruent measuring 0.23 (poor) and 0.94 (equivalent), respectively (21,22).

Cardiorespiratory Fitness Assessment

Researchers compared the V̇O2max values obtained from the standard treadmill tests with the CRF values estimated by the FBC2 (26). In a sample of 65 healthy adults aged 18–45 yr (55% female), Bland–Altman analyses showed that the FBC2 CRF had a positive bias of 1.59 mL·kg−1·min−1 when compared with the treadmill testing at 15 s and a positive bias of 0.30 mL·kg−1·min−1 at 60 s with MAPE values <10% for each comparison (19).

DISCUSSION

HR Validation

Four studies in this review assessed the FBC2 for HR accuracy validation. All except one study included healthy participants, aged 21–73 yr, and generally reported more accuracy at lower-intensity activity levels (18,20,22–25). HR MAPE values while walking at low-to-moderate-intensity levels, at 9.21%, 10.79%, and 69%, reveal a wide interval of error results, with two of the three being similar (20–22). The RER reported by one group of researchers supports validation with their statistically moderate error rate at low-to-moderate walking intensity (light activity, 5.36%, to moderate activity, 9.3%) (24). Another study used pacing cycle length data obtained during scheduled electrophysiological studies to evaluate the HR accuracy of the FBC2 (18). At 100 bpm, the FBC2 measured within ±5 bpm when compared with the ECG criterion at a rate of 93% accuracy with atrial pacing and 80% accuracy with ventricular pacing (18). However, the FBC2 device became significantly less accurate at higher beats per minute (18). HR and steps inherently fluctuate with intensity. These results are similar to the other studies reviewed.

Step Count Validation

In the Irish study of older adults, the FBC2 overestimated step count (MAPE: 12.36%, approaching the acceptable range of <10%) but had vastly different results from the study comparing the older HF subjects (MAPE: 46%) with younger healthy controls (MAPE: 12%) (23,25). The explanation for why the MAPE values of the two healthy populations in the studies were similar, while the MAPE values among the HF participants showed much higher error rates is unclear. However, alterations in gait and slower walking speed among the HF patients likely challenge the FBC2 to track steps reliably and may be a concern when using this device to track steps in populations with ambulation limitations or considerable exercise intolerance due to symptom severity.

FBC2 as HR Monitor

Reliability results as determined by criterion agreement with the FBC2 reported in this review were markedly varied. Scores <0.50 indicate poor reliability; 0.50 to 0.75, moderate reliability; and >0.75, good reliability (30). Nelson and Allen (20) and Reddy et al. (22) reported high CCC scores of >90%. However, Thomson et al. (24) showed decreasing reliability from 56% (moderate) to 26% (poor) as HR intensity increased. Pearson coefficient results from two studies revealed the widest reliability agreement strength discrepancy from 0.23 (weak) and 0.94 (equivalent) (21,22). Finally, Bland–Altman analysis plots revealed HR underestimation measured by the FBC2 compared with the criterion at all intensity levels (20,21,24). The differences of the results may be caused by erratic arm movements or misplacement of the tracker bands as the participants move and perspiration. These varied results make it difficult to reach a definitive conclusion regarding reliability across intensity levels but support reliability at low-to-moderate exercise dose levels.

FBC2 as Step Counter

Reliability of the FBC2 is in agreement with the step criterion, which is the opposite of the HR results. CCC agreement increased from 38% at lower speeds to 99% at a brisk walk (25). ICC results of >0.89 support evidence for high agreement strength between the FBC2 step counter and actigraphy (23).

Cardiorespiratory Fitness Validation

Researchers reported that the FBC2 could be validated to evaluate CRF in relatively young, healthy persons, especially those with a high level of fitness (19). Nearly 92% of the total participants in this study were classified as having high CRF (19). Although the study found CRF agreement between the FBC2 and the Balke treadmill test among users with lower fitness levels, the low numbers in the “good” or “poor” fitness-leveled groups sampled in the study do not provide sufficient evidence of variation to determine validity, nor is the sample representative of the general population who are typically less engaged in CRF activities. Validation studies are needed in populations with chronic conditions or who have ambulation challenges to further evaluate the CRF feature in the FBC2.

Study Limitations

Validation consensus of the FBC2 is limited because of the studies’ small sample sizes (n = 1 to n = 60) and nonstandardized activity settings with some conducted in laboratories on treadmills and others in free-living conditions. Most of the HR examinations were only conducted using young and healthy subjects and may not be generalizable to populations who have chronic conditions or to older adults with other physical limitations. The study that compared HF subjects with healthy controls included far different age demographics (25). In addition, the review is limited by the small number of relevant studies available within a short time span, which is due in part to the development speed of new technology. The Fitbit company released the FBC2 in 2016 and the FBC3 became available in 2018. The cost and research effort needed to perpetually study and validate new technology limit the viability of commercial wearable devices such as the FBC2 for research and use in primary care. Developers of commercial devices would benefit monetarily from strategic collaborations with healthcare researchers in producing devices that are technologically consistent and reliable. There is great potential for wide use of more accessible and affordable devices by healthcare providers worldwide.

Conclusions

Although the FBC2 has been validated for moderate HR and step count accuracy in some studies, more investigation controlling testing and measurement congruency is needed to validate both HR and step capabilities. The literature supports the validity of the FBC2 to accurately monitor HR at low-to-moderate exercise intensities, but validation for step count is inconclusive and may not be suitable for recommended use by populations with gait speed or ambulation challenges.

The authors would like to acknowledge Sharon Leslie, the librarian for the Nell Hodgson Woodruff School of Nursing at Emory University, for her guidance in devising a strategic plan for this review. The authors also appreciate the support of Jeannine Cimiotti for her editorial and educational contributions. The results of the study do not constitute endorsement by the American College of Sports Medicine.

The authors of this project have no conflicts of interest to declare. This project was partially supported by the T32 training grant in Interventions to Improve Outcomes in Chronic Conditions (T32NR012715-06, Dunbar S., Song M. (co-principal investigators)) and by the Healing Hearts and Mending Minds “Fitbrain” study (R-01 NR014963, Gary R. and Waldrop D. (co-principal investigators)).

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