Affiliations:
Department of Electrical Engineering, Tung Nan University, Shen-Keng, New Taipei, Taiwan, ROC
Correspondence:
[*]
Corresponding author. Hsi-Chiang Chou, Department of Electrical Engineering, Tung Nan University, No. 152, Sec. 3, PeiShen Rd., Shen-Keng, New Taipei 222, Taiwan, ROC. E-mail: [email protected].
Abstract: The rapid rates of industrialization and urbanization have induced considerable changes in family structures, increasing the number of older adults who voluntarily or involuntarily live alone. The rapid increase in the population of older adults living alone has raised many safety concerns, with fall-induced injuries and dementia presenting immediate dangers to older adults. Falls are prevalent in older adults, and not only cause injuries for the individuals, but also impose an extremely heavy burden on family members and caregivers. Furthermore, dementia is common among older adults in aging societies and is usually accompanied by dysfunctions in daily living activities, causing considerable difficulties for family members. The objective of this study was to develop a remote monitoring and control (M&C) smart floor system for detecting falls and wandering patterns in older adults with dementia in order to provide comprehensive care assistance. The proposed system integrates a floor detection sensor and Wi-Fi technology to analyze and determine the occurrence of falls and wandering in older adults with dementia. Conventionally, detection processes for falls and wandering in older adults with dementia are conducted using visual monitoring or wearable detectors, which may reduce the privacy, comfort, and convenience of older adults. By contrast, the proposed system maintains users’ privacy and eliminates the inconvenience associated with wearing detectors. The system determines fall behaviors and wandering patterns in older adults with dementia; when an accident occurs, the system can issue a warning and notify medical care units or relatives for immediate attention, thus reducing the occurrence of further accidents. The remote M&C and warning functions of the proposed system were verified through experiments.
Keywords: Fall detection, dementia, wandering patterns
