Development of Wearable Sensor-Based Fall Detection System for Elderly using IoT - Kai Sheng, Yong; Nurfarina Zainal (Evolution in Electrical and Electronic Engineering, 2022)
Recently, there are many elderly living independently might be more dangerous in the house. This is because people who are 65 and above have a high risk of physical health problems such as musculoskeletal disorders, dizziness and imbalance. Falls among the elderly are a growing serious problem. This is because falling has many effects on the elderly and even mortality. People who live alone may not be able to seek help after falling down. In this project, an IoT system that integrates a wearable fall detector was invented to minimise elderly fall injury at home. The system consists of sensors, hardware devices, a cloud server, and the internet. The proposed system is designed with a notification, which can be sent automatically through email and the android smartphone phone of the user if detected any falling condition occurred based on the data received from the wearable device. The fall detector is also designed for indoor use with Wi-Fi conditions. If the elderly is outdoors, elderly can open a hotspot of a smartphone as Wi-Fi. The fall detector will detect the fall signal and the alert system will send a fall notification via email and push notification of the Blynk application to alert family members or caregivers without touching the wearable fall detector button. The system was developed successfully into a wearable form that can be worn at the centre of the chest and detect the fall movements and activities of daily living (ADL).