Assessment of Ultra-Short Heart Variability Indices Derived by Smartphone Accelerometers for Stress Detection
| Autor: | Andrea Faini, Alba Martin-Yebra, Federica Landreani, Enrico G. Caiani, Gianfranco Parati, Mattia Morri |
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| Přispěvatelé: | Landreani, F, Faini, A, Martin-Yebra, A, Morri, M, Parati, G, Caiani, E |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Male
Supine position 030204 cardiovascular system & hematology Accelerometer lcsh:Chemical technology smartphone Psychological Distress 01 natural sciences Biochemistry Standard deviation Accelerometers Ballistocardiography Seismocardiography Smartphone Stress evaluation Ultra-short heart rate variability Analytical Chemistry Electrocardiography 0302 clinical medicine Heart Rate Accelerometry Heart rate variability lcsh:TP1-1185 ultra-short heart rate variability Instrumentation medicine.diagnostic_test Atomic and Molecular Physics and Optics Cardiology Breathing Female psychological phenomena and processes Human Adult medicine.medical_specialty accelerometers stress evaluation Beat (acoustics) behavioral disciplines and activities Article 03 medical and health sciences seismocardiography Internal medicine Heart rate smartphone accelerometers medicine Humans Electrical and Electronic Engineering Psychological Distre business.industry 010401 analytical chemistry biomedical_chemical_engineering 0104 chemical sciences business Beat (music) human activities |
| Zdroj: | Sensors (Basel, Switzerland) Sensors, Vol 19, Iss 17, p 3729 (2019) Sensors Volume 19 Issue 17 Sensors (Basel) 19 (2019). doi:10.3390/s19173729 info:cnr-pdr/source/autori:Landreani F.; Faini A.; Martin-Yebra A.; Morri M.; Parati G.; Caiani E.G./titolo:Assessment of ultra-short heart variability indices derived by smartphone accelerometers for stress detection/doi:10.3390%2Fs19173729/rivista:Sensors (Basel)/anno:2019/pagina_da:/pagina_a:/intervallo_pagine:/volume:19 |
| ISSN: | 1424-8220 |
| DOI: | 10.3390/s19173729 |
| Popis: | 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&mdash SDNN and root mean square of successive differences&mdash 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&rsquo s accelerometers are able to capture the decrease in parasympathetic tone, in agreement with the induced stimulus. |
| Databáze: | OpenAIRE |
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