Explorando tecnologias de IoT no contexto de Health Smart Home: uma abordagem para detecção de quedas em pessoas idosas
Currently, it is increasing the number of patients who are treated at home, especially in countries like Japan, United States and European countries. In addition, the number of elderly has increased significantly in the last 15 years, and these people prefer to receive medical treatment in their homes. However, critical situations can happen during this recovery time, e.g., the elderly patient suffering a fall and aggravate the situation. In this scenario, advances in Ubiquitous Computing and Internet of Things (IoT) have contributed to avoid these situations. In particular, embedded devices, along with the motion
capture through sensors can be applied to develop solutions that offer greater safety for patients who receive treatment at home. However, there is a difficulty to classify an individual’s movements and identify, in fact, a move considered unusual. Thus, the main objective of this work is the detection and classification of movements using data sets of different sensors and embedded device. Paradigms of Artificial Intelligence (AI) were applied to the classification of the movements and tests performed in
architecture SAHHc. The results showed a 96.62% precision in identifying the activities performed by a patient/elderly.
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