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Inicio  /  Applied Sciences  /  Vol: 13 Par: 5 (2023)  /  Artículo
ARTÍCULO
TITULO

Cross-Platform Gait Analysis and Fall Detection Wearable Device

Ming-Hung Chang    
Yi-Chao Wu    
Hsi-Yu Niu    
Yi-Ting Chen and Shu-Han Juang    

Resumen

Since the fall was often occurred in elders daily, this paper focused on gait analysis with fall detection to develop a wearable device. To ensure that the mobile application, APP, could be used in different platform of mobile phone, such Android or iOS, the designed wearable device also could be used in cross-platform in mobile phone. Therefore, a cross-platform gait analysis and fall detection wearable device (CPGAFDWD) was proposed. Since CPGAFDWD APP was used in web browser without limiting to platform, it could be used for different platforms of mobile phone. The gait analysis could be detected at home. The fall detection also could be executed in any place immediately. The patients and medical staff all could query the status of rehabilitation in any place and any time via the Internet. The experimental results showed that the correct rate of gait analysis and fall detection could be up to 90% in cross-platform of mobile phone. In the future, CPGAFDWD will be planned to be verified by Institutional Review Board, IRB, for clinical treatment.