Accuracy and Acceptability of Wearable Motion Tracking for Inpatient Monitoring Using Smartwatches
Inertial Measurement Units (IMUs) within an everyday consumer smartwatch offer a convenient and low-cost method to monitor the natural behaviour of hospital patients. However, their accuracy at quantifying limb motion, and clinical acceptability, have not yet been demonstrated. To this end we conduc...
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| Format: | Article |
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MDPI AG
2020-12-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/20/24/7313 |
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| author | Chaiyawan Auepanwiriyakul Sigourney Waibel Joanna Songa Paul Bentley A. Aldo Faisal |
| author_facet | Chaiyawan Auepanwiriyakul Sigourney Waibel Joanna Songa Paul Bentley A. Aldo Faisal |
| author_sort | Chaiyawan Auepanwiriyakul |
| collection | DOAJ |
| description | Inertial Measurement Units (IMUs) within an everyday consumer smartwatch offer a convenient and low-cost method to monitor the natural behaviour of hospital patients. However, their accuracy at quantifying limb motion, and clinical acceptability, have not yet been demonstrated. To this end we conducted a two-stage study: First, we compared the inertial accuracy of wrist-worn IMUs, both research-grade (Xsens MTw Awinda, and Axivity AX3) and consumer-grade (Apple Watch Series 3 and 5), and optical motion tracking (OptiTrack). Given the moderate to strong performance of the consumer-grade sensors, we then evaluated this sensor and surveyed the experiences and attitudes of hospital patients (N = 44) and staff (N = 15) following a clinical test in which patients wore smartwatches for 1.5–24 h in the second study. Results indicate that for acceleration, Xsens is more accurate than the Apple Series 5 and 3 smartwatches and Axivity AX3 (RMSE 1.66 ± 0.12 m·s<sup>−2</sup>; R<sup>2</sup> 0.78 ± 0.02; RMSE 2.29 ± 0.09 m·s<sup>−2</sup>; R<sup>2</sup> 0.56 ± 0.01; RMSE 2.14 ± 0.09 m·s<sup>−2</sup>; R<sup>2</sup> 0.49 ± 0.02; RMSE 4.12 ± 0.18 m·s<sup>−2</sup>; R<sup>2</sup> 0.34 ± 0.01 respectively). For angular velocity, Series 5 and 3 smartwatches achieved similar performances against Xsens with RMSE 0.22 ± 0.02 rad·s<sup>−1</sup>; R<sup>2</sup> 0.99 ± 0.00; and RMSE 0.18 ± 0.01 rad·s<sup>−1</sup>; R<sup>2</sup> 1.00± SE 0.00, respectively. Surveys indicated that in-patients and healthcare professionals strongly agreed that wearable motion sensors are easy to use, comfortable, unobtrusive, suitable for long-term use, and do not cause anxiety or limit daily activities. Our results suggest that consumer smartwatches achieved moderate to strong levels of accuracy compared to laboratory gold-standard and are acceptable for pervasive monitoring of motion/behaviour within hospital settings. |
| first_indexed | 2024-03-10T13:55:28Z |
| format | Article |
| id | doaj.art-b2bf66c176c7454e8c12df19563e7476 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T13:55:28Z |
| publishDate | 2020-12-01 |
| publisher | MDPI AG |
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| series | Sensors |
| spelling | doaj.art-b2bf66c176c7454e8c12df19563e74762023-11-21T01:39:50ZengMDPI AGSensors1424-82202020-12-012024731310.3390/s20247313Accuracy and Acceptability of Wearable Motion Tracking for Inpatient Monitoring Using SmartwatchesChaiyawan Auepanwiriyakul0Sigourney Waibel1Joanna Songa2Paul Bentley3A. Aldo Faisal4Brain & Behaviour Lab, Department of Computing, Imperial College London, London SW7 2AZ, UKBrain & Behaviour Lab, Department of Computing, Imperial College London, London SW7 2AZ, UKDepartment of Brain Sciences, Imperial College London, London W12 0NN, UKDepartment of Brain Sciences, Imperial College London, London W12 0NN, UKBrain & Behaviour Lab, Department of Computing, Imperial College London, London SW7 2AZ, UKInertial Measurement Units (IMUs) within an everyday consumer smartwatch offer a convenient and low-cost method to monitor the natural behaviour of hospital patients. However, their accuracy at quantifying limb motion, and clinical acceptability, have not yet been demonstrated. To this end we conducted a two-stage study: First, we compared the inertial accuracy of wrist-worn IMUs, both research-grade (Xsens MTw Awinda, and Axivity AX3) and consumer-grade (Apple Watch Series 3 and 5), and optical motion tracking (OptiTrack). Given the moderate to strong performance of the consumer-grade sensors, we then evaluated this sensor and surveyed the experiences and attitudes of hospital patients (N = 44) and staff (N = 15) following a clinical test in which patients wore smartwatches for 1.5–24 h in the second study. Results indicate that for acceleration, Xsens is more accurate than the Apple Series 5 and 3 smartwatches and Axivity AX3 (RMSE 1.66 ± 0.12 m·s<sup>−2</sup>; R<sup>2</sup> 0.78 ± 0.02; RMSE 2.29 ± 0.09 m·s<sup>−2</sup>; R<sup>2</sup> 0.56 ± 0.01; RMSE 2.14 ± 0.09 m·s<sup>−2</sup>; R<sup>2</sup> 0.49 ± 0.02; RMSE 4.12 ± 0.18 m·s<sup>−2</sup>; R<sup>2</sup> 0.34 ± 0.01 respectively). For angular velocity, Series 5 and 3 smartwatches achieved similar performances against Xsens with RMSE 0.22 ± 0.02 rad·s<sup>−1</sup>; R<sup>2</sup> 0.99 ± 0.00; and RMSE 0.18 ± 0.01 rad·s<sup>−1</sup>; R<sup>2</sup> 1.00± SE 0.00, respectively. Surveys indicated that in-patients and healthcare professionals strongly agreed that wearable motion sensors are easy to use, comfortable, unobtrusive, suitable for long-term use, and do not cause anxiety or limit daily activities. Our results suggest that consumer smartwatches achieved moderate to strong levels of accuracy compared to laboratory gold-standard and are acceptable for pervasive monitoring of motion/behaviour within hospital settings.https://www.mdpi.com/1424-8220/20/24/7313healthcareclinical monitoringhospitalstrokehuman activity recognitionnatural movements |
| spellingShingle | Chaiyawan Auepanwiriyakul Sigourney Waibel Joanna Songa Paul Bentley A. Aldo Faisal Accuracy and Acceptability of Wearable Motion Tracking for Inpatient Monitoring Using Smartwatches Sensors healthcare clinical monitoring hospital stroke human activity recognition natural movements |
| title | Accuracy and Acceptability of Wearable Motion Tracking for Inpatient Monitoring Using Smartwatches |
| title_full | Accuracy and Acceptability of Wearable Motion Tracking for Inpatient Monitoring Using Smartwatches |
| title_fullStr | Accuracy and Acceptability of Wearable Motion Tracking for Inpatient Monitoring Using Smartwatches |
| title_full_unstemmed | Accuracy and Acceptability of Wearable Motion Tracking for Inpatient Monitoring Using Smartwatches |
| title_short | Accuracy and Acceptability of Wearable Motion Tracking for Inpatient Monitoring Using Smartwatches |
| title_sort | accuracy and acceptability of wearable motion tracking for inpatient monitoring using smartwatches |
| topic | healthcare clinical monitoring hospital stroke human activity recognition natural movements |
| url | https://www.mdpi.com/1424-8220/20/24/7313 |
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