Abstract
Body acceleration due to heartbeat-induced reaction forces can be measured as mobile phone accelerometer (m-ACC) signals. Our aim was to test the feasibility of using m-ACC to detect changes induced by stress by ultra-short heart rate variability (USV) indices (standard deviation of normal-to-normal interval—SDNN and root mean square of successive differences—RMSSD). Sixteen healthy volunteers were recruited; m-ACC was recorded while in supine position, during spontaneous breathing at rest conditions (REST) and during one minute of mental stress (MS) induced by arithmetic serial subtraction task, simultaneous with conventional electrocardiogram (ECG). Beat occurrences were extracted from both ECG and m-ACC and used to compute USV indices using 60, 30 and 10 s durations, both for REST and MS. A feasibility of 93.8% in the beat-to-beat m-ACC heart rate series extraction was reached. In both ECG and m-ACC series, compared to REST, in MS the mean beat duration was reduced by 15% and RMSSD decreased by 38%. These results show that short term recordings (up to 10 s) of cardiac activity using smartphone’s accelerometers are able to capture the decrease in parasympathetic tone, in agreement with the induced stimulus.
Highlights
Technology developments and device miniaturization have opened the possibility for hand-held devices such as smartphones to be used for physiological data collection
Due the presence of ectopics beats in both rest conditions (REST) and mental stress (MS) OPT series that could result in erroneous ultra-short heart rate variability (USV) indices, another subject was discarded
To allow a paired comparison, 13 subjects were considered for further analysis
Summary
Technology developments and device miniaturization have opened the possibility for hand-held devices such as smartphones to be used for physiological data collection. Through their embedded tri-axial accelerometers, the mobile phone is sensitive enough to record the vibrations generated by the beating heart, as accelerometer signal (m-ACC) of milligravity (mg) level. In this way, the movements along the lateral, the normal, and the longitudinal direction can be detected. The feasibility and accuracy of measuring the beat-to-beat heart rate using smartphone accelerometers has been recently demonstrated [7,8,9,10,11,12,13]
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