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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Main Authors: Federica Landreani, Andrea Faini, Alba Martin-Yebra, Mattia Morri, Gianfranco Parati, Enrico Gianluca Caiani
Format: Article
Language:English
Published: MDPI AG 2019-08-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/19/17/3729
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spelling 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
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