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Wearables and the Quantified Self: Systematic Benchmarking of Physiological Sensors

Wearable sensors are increasingly used in research, as well as for personal and private purposes. A variety of scientific studies are based on physiological measurements from such rather low-cost wearables. That said, how accurate are such measurements compared to measurements from well-calibrated,...

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Autores principales: Sagl, Günther, Resch, Bernd, Petutschnig, Andreas, Kyriakou, Kalliopi, Liedlgruber, Michael, Wilhelm, Frank H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6832271/
https://www.ncbi.nlm.nih.gov/pubmed/31615054
http://dx.doi.org/10.3390/s19204448
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author Sagl, Günther
Resch, Bernd
Petutschnig, Andreas
Kyriakou, Kalliopi
Liedlgruber, Michael
Wilhelm, Frank H.
author_facet Sagl, Günther
Resch, Bernd
Petutschnig, Andreas
Kyriakou, Kalliopi
Liedlgruber, Michael
Wilhelm, Frank H.
author_sort Sagl, Günther
collection PubMed
description Wearable sensors are increasingly used in research, as well as for personal and private purposes. A variety of scientific studies are based on physiological measurements from such rather low-cost wearables. That said, how accurate are such measurements compared to measurements from well-calibrated, high-quality laboratory equipment used in psychological and medical research? The answer to this question, undoubtedly impacts the reliability of a study’s results. In this paper, we demonstrate an approach to quantify the accuracy of low-cost wearables in comparison to high-quality laboratory sensors. We therefore developed a benchmark framework for physiological sensors that covers the entire workflow from sensor data acquisition to the computation and interpretation of diverse correlation and similarity metrics. We evaluated this framework based on a study with 18 participants. Each participant was equipped with one high-quality laboratory sensor and two wearables. These three sensors simultaneously measured the physiological parameters such as heart rate and galvanic skin response, while the participant was cycling on an ergometer following a predefined routine. The results of our benchmarking show that cardiovascular parameters (heart rate, inter-beat interval, heart rate variability) yield very high correlations and similarities. Measurement of galvanic skin response, which is a more delicate undertaking, resulted in lower, but still reasonable correlations and similarities. We conclude that the benchmarked wearables provide physiological measurements such as heart rate and inter-beat interval with an accuracy close to that of the professional high-end sensor, but the accuracy varies more for other parameters, such as galvanic skin response.
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spelling pubmed-68322712019-11-21 Wearables and the Quantified Self: Systematic Benchmarking of Physiological Sensors Sagl, Günther Resch, Bernd Petutschnig, Andreas Kyriakou, Kalliopi Liedlgruber, Michael Wilhelm, Frank H. Sensors (Basel) Article Wearable sensors are increasingly used in research, as well as for personal and private purposes. A variety of scientific studies are based on physiological measurements from such rather low-cost wearables. That said, how accurate are such measurements compared to measurements from well-calibrated, high-quality laboratory equipment used in psychological and medical research? The answer to this question, undoubtedly impacts the reliability of a study’s results. In this paper, we demonstrate an approach to quantify the accuracy of low-cost wearables in comparison to high-quality laboratory sensors. We therefore developed a benchmark framework for physiological sensors that covers the entire workflow from sensor data acquisition to the computation and interpretation of diverse correlation and similarity metrics. We evaluated this framework based on a study with 18 participants. Each participant was equipped with one high-quality laboratory sensor and two wearables. These three sensors simultaneously measured the physiological parameters such as heart rate and galvanic skin response, while the participant was cycling on an ergometer following a predefined routine. The results of our benchmarking show that cardiovascular parameters (heart rate, inter-beat interval, heart rate variability) yield very high correlations and similarities. Measurement of galvanic skin response, which is a more delicate undertaking, resulted in lower, but still reasonable correlations and similarities. We conclude that the benchmarked wearables provide physiological measurements such as heart rate and inter-beat interval with an accuracy close to that of the professional high-end sensor, but the accuracy varies more for other parameters, such as galvanic skin response. MDPI 2019-10-14 /pmc/articles/PMC6832271/ /pubmed/31615054 http://dx.doi.org/10.3390/s19204448 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Sagl, Günther
Resch, Bernd
Petutschnig, Andreas
Kyriakou, Kalliopi
Liedlgruber, Michael
Wilhelm, Frank H.
Wearables and the Quantified Self: Systematic Benchmarking of Physiological Sensors
title Wearables and the Quantified Self: Systematic Benchmarking of Physiological Sensors
title_full Wearables and the Quantified Self: Systematic Benchmarking of Physiological Sensors
title_fullStr Wearables and the Quantified Self: Systematic Benchmarking of Physiological Sensors
title_full_unstemmed Wearables and the Quantified Self: Systematic Benchmarking of Physiological Sensors
title_short Wearables and the Quantified Self: Systematic Benchmarking of Physiological Sensors
title_sort wearables and the quantified self: systematic benchmarking of physiological sensors
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6832271/
https://www.ncbi.nlm.nih.gov/pubmed/31615054
http://dx.doi.org/10.3390/s19204448
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