In cross-platform APP, CPAPP, a web APP by Node.js with MongoDB was designed here. Since CPGAFDWD included wearable, cross-platform APP, and cloud database, the remote accessing by the Internet was needed. Hence, the above mention was the advantages of CPGAFDWD compared to other software. Compared with other software, there is no way to call the emergency contact directly, and the emergency contact cannot receive the notification in time. Moreover, they addressed nothing for cross-platform in mobile devices, such as Android and iOS. None of them addressed the APP in mobile devices. They often aimed to improve the accuracy of fall detection, low power, and low cost. Compared with, the existed fall detection wearable device only focused on fall detection without considering gait analysis. Hence, we integrated the Arduino board with gyroscope, three-axis accelerometer, and Bluetooth to develop a gait analysis and fall detection wearable device, GAFDWD, to address the above issues. In the same condition, to detect the fall accident correctly was another important issue. In the future, CPGAFDWD will be planned to be verified by Institutional Review Board, IRB, for clinical treatment.Īlthough the residential gait analysis could reduce the time money, and manpower, how to judge the correct motion of gait analysis without any help of medical staff becomes an important issue.

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. The patients and medical staff all could query the status of rehabilitation in any place and any time via the Internet.

The fall detection also could be executed in any place immediately. The gait analysis could be detected at home. Since CPGAFDWD APP was used in web browser without limiting to platform, it could be used for different platforms of mobile phone. Therefore, a cross-platform gait analysis and fall detection wearable device (CPGAFDWD) was proposed. 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. Since the fall was often occurred in elders daily, this paper focused on gait analysis with fall detection to develop a wearable device.

Web browser arduino simulation