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Validity of Wearable Activity Monitors during Cycling and Resistance Exercise (Boudreaux et al., 2019)

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Validity of Wearable Activity Monitors during Cycling and Resistance Exercise (Boudreaux et al., 2019)

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- subjects were 8 wearable devices (6 wrist, one chest and one ear)
- Both HR and EE differed among the 8 wearable devices during both cycling and resistance exercises
- HR measures was more accurate when at rest or lower working intensities
- All but one wearable device overestimated EE supporting previous theories
- EE measures in these devices should only be used as estimation due to issues with their validity

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Validity of Wearable Activity Monitors during Cycling and Resistance Exercise (Boudreaux et al, 2019)

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Validity of Wearable Activity Monitors during Cycling and Resistance Exercise (Boudreaux et al, 2019)

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-Polar H7 and BSP valid during both cycling and resistance exercise

-Increase exercise intensity = increase underestimation of HR

-No device valid for EE

-No device medical – claiming users should be cautious in use

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Comparison of four Fitbit and Jawbone activity monitors with a research- grade ActiGraph accelerometer for estimating PA and energy expenditure (Imboden et al, 2017) 

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Comparison of four Fitbit and Jawbone activity monitors with a research- grade ActiGraph accelerometer for estimating PA and energy expenditure (Imboden et al, 2017) 

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Thirty men and women (18-80 YO) wore Fitbit One (at waist), Fitbit Zip (waist), Fitbit Flex (wrist), Jawbone UP24 (wrist) and one waist-worn research grade accelerometer (ActiGraph), whilst doing 80min protocol.....

Findings/conclusion
Consumer monitors had similar results for PA as the ActiGraph. However, due to differences amongst monitors, individuals should still be cautious when comparing the data that other devices show that were not involved in the study. Furthermore, there wasn’t a wide range of activity measured, and so more research would perhaps need to be conducted to gain more conclusive data.

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Current State of Commercial Wearable Technology in Physical Activity Monitoring 2015-2017 (Bunn et al., 2017)

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Current State of Commercial Wearable Technology in Physical Activity Monitoring 2015-2017 (Bunn et al., 2017)

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this systematic review looked at multiple different sensors that are popular in the market. The study found that most of them underestimated the energy expenditure, it also found that wrist and forearm sensors underestimated Heart rate (HR) whilst performing exercises but was fairly accurate at rest.

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A relatively recent study which  compared and contrasted the performance of wearable sensors in classifying physical activity amongst a cohort of 20 older adults both in real life vs lab scenarios

Wearable devices developed in controlled lab settings did not reciprocate the same results in real-life conditions...

Macro-gait accuracy =
91.9 - 97.3%

Extracted wearable signal features (from inertial sensor signals): standard deviation,

skewness, energy, spectral centroid, etc.

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Validity of Wearable Activity Monitors during Cycling and Resistance Exercise.

Polar H7 and BSP were valid during cycling and res

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A Practical Guide to Measuring Physical Activity (Sylvia et al.,  2014)

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A Practical Guide to Measuring Physical Activity (Sylvia et al.,  2014)

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- Doubly labelled water still remains the Gold Standard for measuring PA. However, it is expensive, includes higher subject burden, time intensiveness and difficulty capturing qualitative data.

- Therefore, resorting to wearable Tech measures for physical activity is often relied upon.

Methods include:
Accelerometers
-Gained large popularity due to their accuracy of large data and effectiveness.
-Devices can be worn on various parts of the body and track movement in the anteroposterior, mediolateral, and vertical planes.
-Captures activity intensities and data in large quantities, work very well with children due to ease of use.
-HOWEVER, they are expensive, need tech savviness etc.

Pedometers
-Measures number of steps taken, with a force beyond a certain threshold.
-Low Cost and effectiveness to pick up short periods of exercise (that self-report surveys do not pick up)
-Pedometers work best for documenting relative changes in PA or ranking individuals.
-Cannot provide data for horizontal motion during periods of inactivity.

HR Monitors
-Good Monitors of Intensity and PA Zones. Which may be harder to measure from other methods of movement.
- InObtrusive and low effort measures, for a long period of time.
- Best suited when categorising activity (very active vs sedentary etc) rather than measuring exact amounts.
- Not good for when doing moderate/low intensity activity which may not raise HR too much.
- HR related discrepancies

Armbands
-More recent technology developed using DLW in an attempt to counteract the limitations of other Wearable Devices.

Conclusion
-PA is a multi dimensional construct
- investigators should approach PA measure selection with a clear concept of the
type of data they intend to collect
-must also pay close
attention to each assessment’s strengths and limitations
-Measures will vary depending on age and genders etc.

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Validity of Wearable Activity Monitors during Cycling and Resistance Exercise.

Devices:
Apple Watch Series 2, Fitbit Blaze, Fitbit Charge 2, Polar H7, Polar A360, Garmin Vivosmart HR, TomTom Touch, BSP.

Methodology:
- 50 participants (18-35y/o men + women)
- Participants wore 8 wearable devices (6 wrist-worn, 1 chest-worn, and 1 ear-worn) simultaneously for the study.

Results:
- Polar H7 and Bose Soundsport Pulse headphones (BSP) were valid during the graded cycling exercise test on cycle ergometer and 4 resistance exercises of 10 reps 3 sets at max load.
- During cycling, the Apple Watch Series 2 had the greatest HR validity. - During resistance exercise, BSP had the greatest HR accuracy.
- The wearable that had the strongest correlation with the metabolic analyzer was the GVHR. However, all wearable devices tended to overestimate EE during resistance exercise, lacking validity for EE during cycling or resistance exercise.
- Across all devices, as exercise intensity increased, underestimation of HR also increased. HR was more accurate at rest and lower exercise intensities vs higher intensities.
- Overall, this study revealed that both HR and EE differed among all the wearable devices during both cycling and resistance exercise, and had varying levels of validity when compared with a six-lead ECG and metabolic analyzer.

Limitations:
- Device latency of HR from devices.

Future research:
- Devices should be used for estimation purposes only.
- More research required for other modalities of physical activity such as, swimming and HIIT and to further explore the validity of the devices on HR and EE during different exercises.

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Systematic review of the validity and reliability of consumer-wearable activity trackers. (Evenson et al., 2015)

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Systematic review of the validity and reliability of consumer-wearable activity trackers. (Evenson et al., 2015)

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KEY POINTS:
- Fitbit and Jawbone were studied.
- Fitbit overestimated slower speeds in one study, and underestimated faster speeds.
- Inter-device reliability reported for Fitbit across 7 studies, but no reliability reported for Jawbone.
- Fitbit: consistency of results during sleep were high, and there was consistent reliability in  terms of steps, distance and energy expenditure.
- Jawbone: underestimated energy expenditure, sleep. distance measurements were consistent, no matter where devices were placed (hip or front pocket).
- OVERALL: Not ideal for slower speeds i.e. older adults but a study suggests placing the device on the hip for people with slower gait speeds.
- FUTURE RESEARCH: Due to the constant upgrades, people need to keep testing newer devices as even if the company says they have similar hardware, these changes can still cause large discrepancies.
- if you had to pick one of the 2, FITBIT was overall better than the Jawbone devices.