Currently submitted to: JMIR Biomedical Engineering
Date Submitted: Apr 3, 2020
Open Peer Review Period: Apr 3, 2020 - Apr 20, 2020
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Development of Physical Activity Evaluation Systems Using a Voice Recognition Application
The use of Web-based physical activity systems has been proposed as an easy method for collecting physical activity data. Behavior recording using a voice recognition system via the WEB might be effective.
The objective of this study was to develop a behavior-recording application (APP) using voice recognition. The results from our developed APP were compared with objective data from a 3-axis accelerometer to assess the strengths and weaknesses of the new measurement system.
A total of 20 participants (14 men, 6 women, 19.1 (SD 0.9) years of age) wore a 3-axis accelerometer and inputted behavioral data into their smartphones for a period of 7 days. The measure of intensity was metabolic equivalents (METs).
The Pearson correlations for the METs between the two methods were all positive and significant when the analysis was for over 10 hours, r = 0.545 (P =.017), and for over 14 hours with voice input, r = 0.750 (P =.008). The Bland-Altman 95% limits of agreement ranged from –0.35 to 0.54 METs (over 10 hours) and -0.26 to 0.47 (over 14 hours) between the two methods. The exercise intensity was higher according to the APP compared with the 3-axis accelerometer, indicating overestimation.
Voice recognition APP appear to be useful for assessing physical activity with high accuracy. However, voice input compliance is an important factor.
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