A Detection System for the Elderly based on Embedded Systems
Bokang Yang, Huiwen Xia, Wangdi Du · 2020
As a result of ageing of population, more and more old people live alone. It is dangerous for the elderly to fall at home. A fall detection system for the elderly based on embedded systems was been studied. The system is integrated by acceleration sensors, Beidou positioning modules and communication modules. These modules cooperate with each other and can be used to monitor the user's posture in real time. The Signal Magnitude Vector algorithm (SMV) is used to distinguish whether the elderly fell. If fall was happened, the user's location information will be automatically sent to the emergency contact, and an alarm sounds. The system is easy to implement and has the advantages of high recognition rate and convenient portability.