Low-Cost Sensor System Design for In-Home Physical Activity Tracking
An aging and more sedentary population requires interventions aimed at monitoring physical activity, particularly within the home. This research uses simulation, optimization, and regression analyses to assess the feasibility of using a small number of sensors to track movement and infer physical activity levels of older adults. Based on activity data from the American Time Use Survey and assisted living apartment layouts, we determined that using three to four doorway sensors can be used to effectively capture a sufficient amount of movements in order to estimate activity.
Towards Unobtrusive Patient Handling Activity Recognition for Reducing Injury Risk among Caregivers
Nurses regularly perform patient handling activities. These activities with awkward postures expose healthcare providers to a high risk of overexertion injury. The recognition of patient handling activities is the first step to timely detect the injury development then reduce injury risk for caregivers. The current practice on workplace activity recognition is based on human observational approach, which is neither accurate nor projectable to a large population. In this paper, we aim at addressing these challenges.