A Usability Study of Physiological Measurement in School Using Wearable Sensors
Measuring psychophysiological signals of adolescents using unobtrusive wearable sensors may contribute to understanding the development of emotional disorders. This study investigated the feasibility of measuring high quality physiological data and examined the validity of signal processing in a sch...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-09-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/20/18/5380 |
| _version_ | 1797553173314928640 |
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| author | Nattapong Thammasan Ivo V. Stuldreher Elisabeth Schreuders Matteo Giletta Anne-Marie Brouwer |
| author_facet | Nattapong Thammasan Ivo V. Stuldreher Elisabeth Schreuders Matteo Giletta Anne-Marie Brouwer |
| author_sort | Nattapong Thammasan |
| collection | DOAJ |
| description | Measuring psychophysiological signals of adolescents using unobtrusive wearable sensors may contribute to understanding the development of emotional disorders. This study investigated the feasibility of measuring high quality physiological data and examined the validity of signal processing in a school setting. Among 86 adolescents, a total of more than 410 h of electrodermal activity (EDA) data were recorded using a wrist-worn sensor with gelled electrodes and over 370 h of heart rate data were recorded using a chest-strap sensor. The results support the feasibility of monitoring physiological signals at school. We describe specific challenges and provide recommendations for signal analysis, including dealing with invalid signals due to loose sensors, and quantization noise that can be caused by limitations in analog-to-digital conversion in wearable devices and be mistaken as physiological responses. Importantly, our results show that using toolboxes for automatic signal preprocessing, decomposition, and artifact detection with default parameters while neglecting differences between devices and measurement contexts yield misleading results. Time courses of students’ physiological signals throughout the course of a class were found to be clearer after applying our proposed preprocessing steps. |
| first_indexed | 2024-03-10T16:11:38Z |
| format | Article |
| id | doaj.art-71de8529f2a14904bb37957b3cfc7161 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T16:11:38Z |
| publishDate | 2020-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-71de8529f2a14904bb37957b3cfc71612023-11-20T14:23:07ZengMDPI AGSensors1424-82202020-09-012018538010.3390/s20185380A Usability Study of Physiological Measurement in School Using Wearable SensorsNattapong Thammasan0Ivo V. Stuldreher1Elisabeth Schreuders2Matteo Giletta3Anne-Marie Brouwer4Human Media Interaction, Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, 7522 NB Enschede, The NetherlandsHuman Media Interaction, Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, 7522 NB Enschede, The NetherlandsDepartment Developmental Psychology, Institute of Psychology, Tilburg University, 5000 LE Tilburg, The NetherlandsDepartment Developmental Psychology, Institute of Psychology, Tilburg University, 5000 LE Tilburg, The NetherlandsPerceptual and Cognitive Systems, The Netherlands Organisation for Applied Scientific Research (TNO), 3769 DE Soesterberg, The NetherlandsMeasuring psychophysiological signals of adolescents using unobtrusive wearable sensors may contribute to understanding the development of emotional disorders. This study investigated the feasibility of measuring high quality physiological data and examined the validity of signal processing in a school setting. Among 86 adolescents, a total of more than 410 h of electrodermal activity (EDA) data were recorded using a wrist-worn sensor with gelled electrodes and over 370 h of heart rate data were recorded using a chest-strap sensor. The results support the feasibility of monitoring physiological signals at school. We describe specific challenges and provide recommendations for signal analysis, including dealing with invalid signals due to loose sensors, and quantization noise that can be caused by limitations in analog-to-digital conversion in wearable devices and be mistaken as physiological responses. Importantly, our results show that using toolboxes for automatic signal preprocessing, decomposition, and artifact detection with default parameters while neglecting differences between devices and measurement contexts yield misleading results. Time courses of students’ physiological signals throughout the course of a class were found to be clearer after applying our proposed preprocessing steps.https://www.mdpi.com/1424-8220/20/18/5380wearablesEDAheart rateperipheral physiologyambulatory monitoring |
| spellingShingle | Nattapong Thammasan Ivo V. Stuldreher Elisabeth Schreuders Matteo Giletta Anne-Marie Brouwer A Usability Study of Physiological Measurement in School Using Wearable Sensors Sensors wearables EDA heart rate peripheral physiology ambulatory monitoring |
| title | A Usability Study of Physiological Measurement in School Using Wearable Sensors |
| title_full | A Usability Study of Physiological Measurement in School Using Wearable Sensors |
| title_fullStr | A Usability Study of Physiological Measurement in School Using Wearable Sensors |
| title_full_unstemmed | A Usability Study of Physiological Measurement in School Using Wearable Sensors |
| title_short | A Usability Study of Physiological Measurement in School Using Wearable Sensors |
| title_sort | usability study of physiological measurement in school using wearable sensors |
| topic | wearables EDA heart rate peripheral physiology ambulatory monitoring |
| url | https://www.mdpi.com/1424-8220/20/18/5380 |
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