Recognition of Bathroom Activities in Older Adults Using Wearable Sensors: A Systematic Review and Recommendations

Abstract

This article provides a systematic review of studies on recognising bathroom activities in older adults using wearable sensors. Bathroom activities are an important part of Activities of Daily Living (ADL). The performance on ADL activities is used to predict the ability of older adults to live independently. This paper aims to provide an overview of the studied bathroom activities, the wearable sensors used, different applied methodologies and the tested activity recognition techniques. Six databases were screened up to March 2020, based on four categories of keywords: older adults, activity recognition, bathroom activities and wearable sensors. In total, 4262 unique papers were found, of which only seven met the inclusion criteria. This small number shows that few studies have been conducted in this field. Therefore, in addition, this critical review resulted in several recommendations for future studies. In particular, we recommend to (1) study complex bathroom activities, including multiple movements; (2) recruit participants, especially the target population; (3) conduct both lab and real-life experiments; (4) investigate the optimal number and positions of wearable sensors; (5) choose a suitable annotation method; (6) investigate deep learning models; (7) evaluate the generality of classifiers; and (8) investigate both detection and quality performance of an activity.

Evidence and User Considerations of Home Health Monitoring for Older Adults: Scoping Review

“…Most studies found that technologies were not mature enough to detect activity changes or improve independence [ 88 , 89 , 92 , 105 ]. For monitoring older adults in general, % (3/N) of studies noted weak evidence for detecting changes in ADLs [ 82 - 84 ], and 2 studies showed improved QoL [ 85 , 86 ].…”

Detection of activities in bathrooms through deep learning and environmental data graphics images

“…On the other hand, these technological methods for HAR have been applied frequently in homes [ 6 ], their bathrooms being precisely one of the spaces whose activities have been monitored on several occasions [ [7] , [8] , [9] , [10] , [11] ].…”

“…Therefore, the detection and monitoring of these activities has been the object of study using technologies such as sound capture [ 7 , 8 ], images or infrared [ 9 ], wearable accelerometer [ 10 ], wearable sensors [ 11 ], among others. In these cases, although quite interesting results have been achieved, there are limitations.…”

“…Nguyen, C. Lohr, B. Leduc, I. Kanellos 2021 A survey of human activity recognition in smart homes based on IoT sensors algorithms: Taxonomies, challenges, and opportunities with deep learning [ 6 ] Sensors A 3 B. Fu, N. Damer, F. Kirchbuchner, A. Kuijper 2020 Sensing technology for human activity recognition: A comprehensive survey [ 3 ] IEEE Access A 4 Y. Zhang, I. D'haeseleer, J. Coelho, V. Vanden Abeele, B. Vanrumste 2021 Recognition of Bathroom Activities in Older Adults Using Wearable Sensors: A Systematic Review and Recommendations [ 11 ] Sensors B 5 Y. Zhang, J. Wullems, I. Dihaeseleer, V. Vanden Abeele, B. Vanrumste 2020 Bathroom activity monitoring for older adults via wearable device [ 10 ] IEEE International Conference on Healthcare Informatics B 6 K. Chapron, P. Lapointe, K. Bouchard, S. Gaboury Highly Accurate Bathroom Activity Recognition Using Infrared Proximity Sensors [ 9 ] IEEE Journal of Biomedical and Health Informatics B 7 J. Chen, A.H. Kam, J. Zhang, N. Liu, L. Shue 2005 Bathroom Activity Monitoring Based on Sound [ 8 ] Pervasive Computing: Third International Conference, PERVASIVE 2005 B A) Technology for the recognition of human activity in general. B) Technology for the recognition of human activity in bathrooms.…”

“…Thus, although privacy is tried to preserve [ 14 ], it is generally a problematic issue, especially in the case of capturing images and sounds. Even when the proposed system includes devices that the user must always carry [ 10 , 11 ], these limitations occur because they require consent and commitment to use.…”