Activity Recognition and Monitoring for Smart Wheelchair Users

In recent years, the elderly population is increasing enormously, from 9% in 1994 to 12% in 2014, and is expected to reach 21% by 2050. Elderly live often alone today and even conducting an independent daily life, some of them move with the aid of walkers or using wheelchairs. Monitoring elderly activity in mobility has become a major priority to provide them an effective care service. This paper focuses on an enhancement of a smart wheelchair based on pressure sensors to monitor users sitting on the wheelchair. If the wheelchair user assumes a dangerous posture, the system triggers audio/visual alarms to avoid critical consequences such as wheelchair overturn. The paper discusses the hardware design of the system, then analyzes and compares posture recognition methods that have been applied on pressure data we collected. The experiments demonstrate the effectiveness of the proposed method and 99.5% posture recognition accuracy has been observed.