Assessment of Ultra-Short Heart Variability Indices Derived by Smartphone Accelerometers for Stress Detection
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...
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doaj-91466b67f3564af79a42773d856085092020-11-24T20:42:55ZengMDPI AGSensors1424-82202019-08-011917372910.3390/s19173729s19173729Assessment of Ultra-Short Heart Variability Indices Derived by Smartphone Accelerometers for Stress DetectionFederica Landreani0Andrea Faini1Alba Martin-Yebra2Mattia Morri3Gianfranco Parati4Enrico Gianluca Caiani5Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milan, ItalyIstituto Auxologico Italiano, IRCCS, Department of Cardiovascular Neural and Metabolic Sciences, S. Luca Hospital, 20149 Milan, ItalyDipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milan, ItalyDipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milan, ItalyIstituto Auxologico Italiano, IRCCS, Department of Cardiovascular Neural and Metabolic Sciences, S. Luca Hospital, 20149 Milan, ItalyDipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milan, ItalyBody 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.https://www.mdpi.com/1424-8220/19/17/3729ballistocardiographyseismocardiographyultra-short heart rate variabilitystress evaluationsmartphoneaccelerometers |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Federica Landreani Andrea Faini Alba Martin-Yebra Mattia Morri Gianfranco Parati Enrico Gianluca Caiani |
spellingShingle |
Federica Landreani Andrea Faini Alba Martin-Yebra Mattia Morri Gianfranco Parati Enrico Gianluca Caiani Assessment of Ultra-Short Heart Variability Indices Derived by Smartphone Accelerometers for Stress Detection Sensors ballistocardiography seismocardiography ultra-short heart rate variability stress evaluation smartphone accelerometers |
author_facet |
Federica Landreani Andrea Faini Alba Martin-Yebra Mattia Morri Gianfranco Parati Enrico Gianluca Caiani |
author_sort |
Federica Landreani |
title |
Assessment of Ultra-Short Heart Variability Indices Derived by Smartphone Accelerometers for Stress Detection |
title_short |
Assessment of Ultra-Short Heart Variability Indices Derived by Smartphone Accelerometers for Stress Detection |
title_full |
Assessment of Ultra-Short Heart Variability Indices Derived by Smartphone Accelerometers for Stress Detection |
title_fullStr |
Assessment of Ultra-Short Heart Variability Indices Derived by Smartphone Accelerometers for Stress Detection |
title_full_unstemmed |
Assessment of Ultra-Short Heart Variability Indices Derived by Smartphone Accelerometers for Stress Detection |
title_sort |
assessment of ultra-short heart variability indices derived by smartphone accelerometers for stress detection |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2019-08-01 |
description |
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. |
topic |
ballistocardiography seismocardiography ultra-short heart rate variability stress evaluation smartphone accelerometers |
url |
https://www.mdpi.com/1424-8220/19/17/3729 |
work_keys_str_mv |
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