Elderly Fall Monitoring in Smart Homes Using Wearable Device

Abstract

The constant progress of technology, especially in the area of health, brings numerous benefits, one of which is the increase in human life expectancy. However, problems that occur recurrently among the elderly age group are now on the radar of studies that also seek to improve the quality of life of these people. The number of cases of falls among elderly people is worrying, even more so as this is a portion of the population that tends to live alone. In the context of smart homes, several solutions have emerged for monitoring elderly people to increase safety and provide faster assistance, if necessary. One of these solutions is the use of wearable devices responsible for identifying the person’s movements. This work presents the study and development of a wearable device capable of detecting falls and, if they occur, automatically notifying the necessary people through alert messages via the Telegram application so that they can help the person who has suffered a fall. In this work, a Wi-Fi network, MQTT protocol, accelerometer and gyroscope inertial sensors and an ESP32 board programmed using the Arduino IDE were used. Preliminary tests indicated good performance in recognizing falls, based on tilt angle analysis, gyroscope readings and accelerometer readings. The proof of concept and preliminary tests carried out demonstrate the potential for using low-cost technologies for wearable resources for application in smart homes and monitoring the health of elderly people.