A Wearable Fall Detection System based on LoRa LPWAN Technology

Abstract

The fall problem affects approximately one third of people aged over 65 years. Falls and fall-related injuries are one of the major causes of morbidity and mortality in the elderly population. Since many years, research activities have been targeted towards the development of technological solutions for the automatic detection and notification of falls. Among them, wearable based systems offer the advantage of being available ideally everywhere and cost-effective in terms of economy and computational burden. However, their use poses different challenges, from acceptability to battery usage. The choice of the communication technology, in particular, plays a fundamental role in the realization of a suitable solution, able to meet the target users’ needs. In this paper, we present a fall detection system, based on a pair of instrumented shoes. They communicate the alarming events to a supervising system through the LoRa LPWAN technology, without the need of a portable gateway. Experimental results demonstrate the effectiveness of the chosen communication technology and fall detection reliability.

LPWAN and Embedded Machine Learning as Enablers for the Next Generation of Wearable Devices

“…In line with this, a quick detection of infectious diseases is crucial in order to avoid pandemics [ 25 ]. Besides, having continuous monitoring of critical patients [ 26 ], chronic diseases [ 27 ], or elderly people [ 28 ], is greatly relevant for the patient’s quality of life. This monitoring is usually conducted in indoor environments, hence the exploitation of LPWANs for maintaining periodic contact or triggering alerts to the patient’s healthcare service may be highly beneficial [ 29 ].…”