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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

  • Hideyuki Namba; 

ABSTRACT

Background:

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.

Objective:

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.

Methods:

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).

Results:

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.

Conclusions:

Voice recognition APP appear to be useful for assessing physical activity with high accuracy. However, voice input compliance is an important factor.


 Citation

Please cite as:

Namba H

Development of Physical Activity Evaluation Systems Using a Voice Recognition Application

JMIR Preprints. 03/04/2020:19088

DOI: 10.2196/preprints.19088

URL: https://preprints.jmir.org/preprint/19088

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