A Night-Time Monitoring System (eNightLog) to Prevent Elderly Wandering in Hostels: A Three-Month Field Study.

Older people are increasingly dependent on others to support their daily activities due to geriatric symptoms such as dementia. Some of them stay in long-term care facilities. Elderly people with night wandering behaviour may lose their way, leading to a significant risk of injuries. The eNightLog system was developed to monitor the night-time bedside activities of older people in order to help them cope with this issue. It comprises a 3D time-of-flight near-infrared sensor and an ultra-wideband sensor for detecting human presence and to determine postures without a video camera. A threshold-based algorithm was developed to classify different activities, such as leaving the bed. The system is able to send alarm messages to caregivers if an elderly user performs undesirable activities. In this study, 17 sets of eNightLog systems were installed in an elderly hostel with 17 beds in 9 bedrooms. During the three-month field test, 26 older people with different periods of stay were included in the study. The accuracy, sensitivity and specificity of detecting non-assisted bed-leaving events was 99.8%, 100%, and 99.6%, respectively. There were only three false alarms out of 2762 bed-exiting events. Our results demonstrated that the eNightLog system is sufficiently accurate to be applied in the hostel environment. Machine learning with instance segmentation and online learning will enable the system to be used for widely different environments and people, with improvements to be made in future studies.

Follow Your Virtual Trainer (FYVT): a randomised controlled trial protocol of IT-based lifestyle intervention programme to promote physical activity and health among middle-aged Hong Kong Chinese.

INTRODUCTION: Hong Kong is a highly urbanised city where many people work long hours. The limited time and lack of professional instruction are the typical barriers to exercise. The purpose of this study is to test the effectiveness of an information technology-based lifestyle intervention programme on improving physical activity (PA) level and health status in a sample of middle-aged Hong Kong adults. METHODS AND ANALYSIS: A two-arm parallel randomised controlled trial named 'Follow Your Virtual Trainer' will be conducted among 200 physically inactive Chinese adults aged from 40 to 65 years. Those randomly allocated to an intervention group will be under the instruction of a web-based computer software termed 'Virtual Trainer (VT)' to conduct a 3-month self-planned PA programme. A series of online seminars with healthy lifestyle information will be released to the participants biweekly for 3 months. After that, 6 months observation will follow. Those in the control group will only receive a written advice of standard PA recommendation and the textual content of the seminars. The assessments will be implemented at baseline, the 3rd, 6th and 9th months. The primary outcome is PA measured by accelerometer and International Physical Activity Questionnaire. The secondary outcomes include cardiorespiratory fitness, resting energy expenditure, anthropometrics, body composition, blood pressure, health-related quality of life, sleep quality and quantity, fatigue, behaviour mediators and maintenance of PA. The main effectiveness of the intervention will be assessed by a linear mixed model that tests the random effect of treatment on outcomes at the 3rd, 6th and 9th months. ETHICS AND DISSEMINATION: This trial has been approved by the Joint Chinese University of Hong Kong-New Territories East Cluster Clinical Research Ethics Committee (CRE 2015235). The study results will be presented at scientific conferences and published in peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT02553980.