Assessment of Ultra-Short Heart Variability Indices Derived by Smartphone Accelerometers for Stress Detection

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Assessment of Ultra-Short Heart Variability Indices Derived by Smartphone Accelerometers for Stress Detection. / Landreani, Federica; Faini, Andrea; Martin-Yebra, Alba; Morri, Mattia; Parati, Gianfranco; Caiani, Enrico Gianluca.

In: Sensors (Basel, Switzerland), Vol. 19, No. 17, 28.08.2019.

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Landreani, Federica ; Faini, Andrea ; Martin-Yebra, Alba ; Morri, Mattia ; Parati, Gianfranco ; Caiani, Enrico Gianluca. / Assessment of Ultra-Short Heart Variability Indices Derived by Smartphone Accelerometers for Stress Detection. In: Sensors (Basel, Switzerland). 2019 ; Vol. 19, No. 17.

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TY - JOUR

T1 - Assessment of Ultra-Short Heart Variability Indices Derived by Smartphone Accelerometers for Stress Detection

AU - Landreani, Federica

AU - Faini, Andrea

AU - Martin-Yebra, Alba

AU - Morri, Mattia

AU - Parati, Gianfranco

AU - Caiani, Enrico Gianluca

PY - 2019/8/28

Y1 - 2019/8/28

N2 - 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 10s 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.

AB - 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 10s 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.

KW - accelerometers

KW - ballistocardiography

KW - seismocardiography

KW - smartphone

KW - stress evaluation

KW - ultra-short heart rate variability

U2 - 10.3390/s19173729

DO - 10.3390/s19173729

M3 - Article

VL - 19

JO - Sensors

T2 - Sensors

JF - Sensors

SN - 1424-3210

IS - 17

ER -