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. 2021 Feb 18;21(4):1411.
doi: 10.3390/s21041411.

The Validity of MotionSense HRV in Estimating Sedentary Behavior and Physical Activity under Free-Living and Simulated Activity Settings

Sunku Kwon  1 , Neng Wan  2 , Ryan D Burns  1 , Timothy A Brusseau  1 , Youngwon Kim  3   4 , Santosh Kumar  5 , Emre Ertin  6 , David W Wetter  7 , Cho Y Lam  7 , Ming Wen  8 , Wonwoo Byun  1
Affiliations

The Validity of MotionSense HRV in Estimating Sedentary Behavior and Physical Activity under Free-Living and Simulated Activity Settings

Sunku Kwon et al. Sensors (Basel). .

Abstract

MotionSense HRV is a wrist-worn accelerometery-based sensor that is paired with a smartphone and is thus capable of measuring the intensity, duration, and frequency of physical activity (PA). However, little information is available on the validity of the MotionSense HRV. Therefore, the purpose of this study was to assess the concurrent validity of the MotionSense HRV in estimating sedentary behavior (SED) and PA. A total of 20 healthy adults (age: 32.5 ± 15.1 years) wore the MotionSense HRV and ActiGraph GT9X accelerometer (GT9X) on their non-dominant wrist for seven consecutive days during free-living conditions. Raw acceleration data from the devices were summarized into average time (min/day) spent in SED and moderate-to-vigorous PA (MVPA). Additionally, using the Cosemed K5 indirect calorimetry system (K5) as a criterion measure, the validity of the MotionSense HRV was examined in simulated free-living conditions. Pearson correlations, mean absolute percent errors (MAPE), Bland-Altman (BA) plots, and equivalence tests were used to examine the validity of the MotionSense HRV against criterion measures. The correlations between the MotionSense HRV and GT9X were high and the MAPE were low for both the SED (r = 0.99, MAPE = 2.4%) and MVPA (r = 0.97, MAPE = 9.1%) estimates under free-living conditions. BA plots illustrated that there was no systematic bias between the MotionSense HRV and criterion measures. The estimates of SED and MVPA from the MotionSense HRV were significantly equivalent to those from the GT9X; the equivalence zones were set at 16.5% for SED and 29% for MVPA. The estimates of SED and PA from the MotionSense HRV were less comparable when compared with those from the K5. The MotionSense HRV yielded comparable estimates for SED and PA when compared with the GT9X accelerometer under free-living conditions. We confirmed the promising application of the MotionSense HRV for monitoring PA patterns for practical and research purposes.

Keywords: MotionSense HRV; accelerometer; mobile health; physical activity; sedentary behavior; validity.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Pearson Correlations (r) for sedentary behavior and physical activity (PA) estimates between the GT9X and MotionSense HRV (MSHRV) under free-living conditions. SED: sedentary behavior; LPA: light PA; MVPA: moderate-to-vigorous PA; TPA: total PA; * p < 0.05.
Figure 2
Figure 2
Pearson Correlations (r) for sedentary behavior and physical activity (PA) estimates between the Cosmed K5 (K5) and MotionSense HRV (MSHRV) under simulated free-living conditions. SED: sedentary behavior; LPA: light PA; MVPA: moderate-to-vigorous PA; TPA: total PA; * p < 0.05.
Figure 3
Figure 3
Bland–Altman plots illustrating the level of agreement in sedentary behavior and PA estimates between the GT9X and MotionSense HRV (MSHRV) under free-living conditions. Dashed lines show 95% limits of agreement (±1.96 standard deviation). SED: sedentary behavior; LPA: light PA; MVPA: moderate-to-vigorous PA; TPA: total PA.
Figure 4
Figure 4
Bland–Altman plots illustrating the level of agreement in sedentary behavior and PA estimates between the Cosmed K5 and MotionSense HRV (MSHRV) under simulated free-living conditions. Dashed lines show 95% limits of agreement (±1.96 standard deviation). SED: sedentary behavior; LPA: light PA; MVPA: moderate-to-vigorous PA; TPA: total PA.
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