JMIR Publications

ABSTRACT

Background:

As the mobile environment has developed recently, there have been studies on continuous respiration monitoring. However, it is not easy for general users to access the sensors typically used to measure respiration. There is also random noise caused by various environmental variables when respiration is measured using noncontact methods in a mobile environment.

Objective:

In this study, the respiration rate was estimated using an accelerometer sensor in smartphone.

Methods:

First, data was acquired from an accelerometer sensor by a smart phone, which can easily be accessed by the general public. Second, an independent component was extracted to calibrate the 3-axis accelerometer. Last, the respiration rate was estimated using quefrency selection reflecting harmonic information because respiration has regular patterns.

Results:

The statistical results of the Wilcoxon signed ranks tests were used to determine whether the differences in the respiration counts acquired from chest belt and from the accelerometer sensor were significant. The p-value of the difference in the respiration counts acquired from the two sensors was 0.10, which was not significant. This indicates that the number of respiration counts measured using the accelerometer sensor was not different from that measured using the chest belt.

Conclusions:

There was no statistical difference in the respiration rate measured using a chest belt and the respiration rate measured using the accelerometer sensor. The approach could solve problems related to the inconvenience of chest belt attachment and the settings. It could be used to detect sleep apnea through constant respiration rate estimation in an IoT environment.