Literature DB >> 33352717

Accuracy and Acceptability of Wearable Motion Tracking for Inpatient Monitoring Using Smartwatches.

Chaiyawan Auepanwiriyakul1,2, Sigourney Waibel1,3, Joanna Songa3, Paul Bentley3, A Aldo Faisal1,2,4,5.   

Abstract

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-2; R2 0.78 ± 0.02; RMSE 2.29 ± 0.09 m·s-2; R2 0.56 ± 0.01; RMSE 2.14 ± 0.09 m·s-2; R2 0.49 ± 0.02; RMSE 4.12 ± 0.18 m·s-2; R2 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-1; R2 0.99 ± 0.00; and RMSE 0.18 ± 0.01 rad·s-1; R2 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.

Entities:  

Keywords:  clinical monitoring; healthcare; hospital; human activity recognition; inertial movement unit; natural movements; optical motion tracking; stroke

Mesh:

Year:  2020        PMID: 33352717      PMCID: PMC7766923          DOI: 10.3390/s20247313

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  41 in total

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Authors:  Bruce Carse; Barry Meadows; Roy Bowers; Philip Rowe
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2.  Concurrent validation of Xsens MVN measurement of lower limb joint angular kinematics.

Authors:  Jun-Tian Zhang; Alison C Novak; Brenda Brouwer; Qingguo Li
Journal:  Physiol Meas       Date:  2013-07-26       Impact factor: 2.833

3.  Consumers' perceived attitudes to wearable devices in health monitoring in China: A survey study.

Authors:  Dong Wen; Xingting Zhang; Jianbo Lei
Journal:  Comput Methods Programs Biomed       Date:  2016-12-15       Impact factor: 5.428

4.  Validation of inertial measurement units with an optoelectronic system for whole-body motion analysis.

Authors:  Xavier Robert-Lachaine; Hakim Mecheri; Christian Larue; André Plamondon
Journal:  Med Biol Eng Comput       Date:  2016-07-05       Impact factor: 2.602

5.  Validation of an Accelerometer to Quantify a Comprehensive Battery of Gait Characteristics in Healthy Older Adults and Parkinson's Disease: Toward Clinical and at Home Use.

Authors:  Silvia Del Din; Alan Godfrey; Lynn Rochester
Journal:  IEEE J Biomed Health Inform       Date:  2015-04-02       Impact factor: 5.772

Review 6.  A review of wearable sensors and systems with application in rehabilitation.

Authors:  Shyamal Patel; Hyung Park; Paolo Bonato; Leighton Chan; Mary Rodgers
Journal:  J Neuroeng Rehabil       Date:  2012-04-20       Impact factor: 4.262

Review 7.  Systematic review of the validity and reliability of consumer-wearable activity trackers.

Authors:  Kelly R Evenson; Michelle M Goto; Robert D Furberg
Journal:  Int J Behav Nutr Phys Act       Date:  2015-12-18       Impact factor: 6.457

Review 8.  Wearable sensors for clinical applications in epilepsy, Parkinson's disease, and stroke: a mixed-methods systematic review.

Authors:  Dongni Johansson; Kristina Malmgren; Margit Alt Murphy
Journal:  J Neurol       Date:  2018-02-09       Impact factor: 4.849

9.  Towards Inertial Sensor Based Mobile Gait Analysis: Event-Detection and Spatio-Temporal Parameters.

Authors:  Wolfgang Teufl; Michael Lorenz; Markus Miezal; Bertram Taetz; Michael Fröhlich; Gabriele Bleser
Journal:  Sensors (Basel)       Date:  2018-12-22       Impact factor: 3.576

10.  The use of inertial sensors system for human motion analysis.

Authors:  Antonio I Cuesta-Vargas; Alejandro Galán-Mercant; Jonathan M Williams
Journal:  Phys Ther Rev       Date:  2010-12
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  2 in total

Review 1.  Recent Advances in Wearable Optical Sensor Automation Powered by Battery versus Skin-like Battery-Free Devices for Personal Healthcare-A Review.

Authors:  Nikolay L Kazanskiy; Muhammad A Butt; Svetlana N Khonina
Journal:  Nanomaterials (Basel)       Date:  2022-01-21       Impact factor: 5.076

2.  When does self-report of pain occur?: A study of older adults.

Authors:  Iyubanit Rodríguez; Gabriela Cajamarca; Valeria Herskovic
Journal:  PeerJ       Date:  2022-07-19       Impact factor: 3.061

  2 in total

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