Assistive Technology for Fall Detection Development of Integrated Wearable Sensor to Smart Home System

  • Guilherme Gerzon Torres UFRGS
  • Yuri das Neves Valadão UFRGS
  • Tiago Rodrigo Cruz UFRGS
  • Ivan Müller UFRGS


Fall detection is an assistive technology for elderly people that helps in emergency situations. This work presents the development of a wearable device to detect falls connected to a ultra low power wireless network. The device is connected to a smart home system to trigger alarms when events are detected. The fall detection is done by a threshold algorithm based on data fusion from inertial sensors. The wearable sensor is based on EnOcean protocol, which includes a wireless connection with a smart home system, according to the KNX standard, through the Home Assistant platform. The tests were performed in a prototype and the results include the evaluation of fall and nonfall movements in two different body characteristics. The results revealed sensitivity and specificity of up to 96% and 100%, respectively.

Palavras-chave: EnOcean, KNX, Wearable sensor, Sensor Fusion, Fall Detection


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TORRES, Guilherme Gerzon; VALADÃO, Yuri das Neves; CRUZ, Tiago Rodrigo; MÜLLER, Ivan. Assistive Technology for Fall Detection Development of Integrated Wearable Sensor to Smart Home System. In: TRABALHOS EM ANDAMENTO - SIMPÓSIO BRASILEIRO DE ENGENHARIA DE SISTEMAS COMPUTACIONAIS (SBESC), 11. , 2021, Evento Online. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2021 . p. 140-145. ISSN 2763-9002. DOI: