Wearable Motion-Based Heart Rate at Rest: A Workplace Evaluation
IEEE This work studies the feasibility of using low-cost motion sensors to provide opportunistic heart rate assessments from ballistocardiographic signals during restful periods of daily life. Three wearable devices were used to capture peripheral motions at specific body locations (head, wrist and...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
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Institute of Electrical and Electronics Engineers (IEEE)
2020
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| Online Access: | https://hdl.handle.net/1721.1/126835 |
| _version_ | 1811096912816766976 |
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| author | Hernandez Rivera, Javier McDuff, Daniel Jonathan Quigley, Karen Maes, Patricia Picard, Rosalind W. |
| author2 | Massachusetts Institute of Technology. Media Laboratory |
| author_facet | Massachusetts Institute of Technology. Media Laboratory Hernandez Rivera, Javier McDuff, Daniel Jonathan Quigley, Karen Maes, Patricia Picard, Rosalind W. |
| author_sort | Hernandez Rivera, Javier |
| collection | MIT |
| description | IEEE This work studies the feasibility of using low-cost motion sensors to provide opportunistic heart rate assessments from ballistocardiographic signals during restful periods of daily life. Three wearable devices were used to capture peripheral motions at specific body locations (head, wrist and trouser pocket) of 15 participants during five regular workdays each. Three methods were implemented to extract heart rate from motion data and their performance was compared to those obtained with an FDA-cleared device. With a total of 1358 hours of naturalistic sensor data, our results show that providing accurate heart rate estimations from peripheral motion signals is possible during relatively "still" moments. In our real-life workplace study, the head-mounted device yielded the most frequent assessments (22.98% of the time under 5 beats per minute of error) followed by the smartphone in the pocket (5.02%) and the wrist-worn device (3.48%). Most importantly, accurate assessments were automatically detected by using a custom threshold based on the device jerk. Due to the pervasiveness and low-cost of wearable motion sensors, this work demonstrates the feasibility of providing opportunistic large-scale low-cost samples of resting heart rate. |
| first_indexed | 2024-09-23T16:51:20Z |
| format | Article |
| id | mit-1721.1/126835 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T16:51:20Z |
| publishDate | 2020 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | mit-1721.1/1268352022-10-03T08:43:59Z Wearable Motion-Based Heart Rate at Rest: A Workplace Evaluation Hernandez Rivera, Javier McDuff, Daniel Jonathan Quigley, Karen Maes, Patricia Picard, Rosalind W. Massachusetts Institute of Technology. Media Laboratory IEEE This work studies the feasibility of using low-cost motion sensors to provide opportunistic heart rate assessments from ballistocardiographic signals during restful periods of daily life. Three wearable devices were used to capture peripheral motions at specific body locations (head, wrist and trouser pocket) of 15 participants during five regular workdays each. Three methods were implemented to extract heart rate from motion data and their performance was compared to those obtained with an FDA-cleared device. With a total of 1358 hours of naturalistic sensor data, our results show that providing accurate heart rate estimations from peripheral motion signals is possible during relatively "still" moments. In our real-life workplace study, the head-mounted device yielded the most frequent assessments (22.98% of the time under 5 beats per minute of error) followed by the smartphone in the pocket (5.02%) and the wrist-worn device (3.48%). Most importantly, accurate assessments were automatically detected by using a custom threshold based on the device jerk. Due to the pervasiveness and low-cost of wearable motion sensors, this work demonstrates the feasibility of providing opportunistic large-scale low-cost samples of resting heart rate. 2020-08-27T22:58:50Z 2020-08-27T22:58:50Z 2019-09 2019-07-24T16:30:46Z Article http://purl.org/eprint/type/JournalArticle 2168-2194 2168-2208 https://hdl.handle.net/1721.1/126835 Hernandez, Javier et al. "Wearable Motion-Based Heart Rate at Rest: A Workplace Evaluation." IEEE Journal of Biomedical and Health Informatics 23, 5 (September 2019): 1920 - 1927 © 2019 IEEE en http://dx.doi.org/10.1109/jbhi.2018.2877484 IEEE Journal of Biomedical and Health Informatics Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Institute of Electrical and Electronics Engineers (IEEE) Other repository |
| spellingShingle | Hernandez Rivera, Javier McDuff, Daniel Jonathan Quigley, Karen Maes, Patricia Picard, Rosalind W. Wearable Motion-Based Heart Rate at Rest: A Workplace Evaluation |
| title | Wearable Motion-Based Heart Rate at Rest: A Workplace Evaluation |
| title_full | Wearable Motion-Based Heart Rate at Rest: A Workplace Evaluation |
| title_fullStr | Wearable Motion-Based Heart Rate at Rest: A Workplace Evaluation |
| title_full_unstemmed | Wearable Motion-Based Heart Rate at Rest: A Workplace Evaluation |
| title_short | Wearable Motion-Based Heart Rate at Rest: A Workplace Evaluation |
| title_sort | wearable motion based heart rate at rest a workplace evaluation |
| url | https://hdl.handle.net/1721.1/126835 |
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