| Summary: | 碩士 === 義守大學 === 機械與自動化工程學系 === 107 === This study uses the machine learning technique to assist face recognition to help users evoke memories and avoid mental imbalances. This study is to design and manufacture an integrated wearable device, including the support, data processor, camera and earphone. The device is presented in a hat style, and it can transmit the audio and video data to the processor for face recognition and calculations. This study first uses computer-aided design technology (CAD) to design the device system, and uses computer-aided engineering analysis (CAE) to carry out the stress, strain and displacement of the support. In addition to improve the device design, 3D printing technology are employed to print the device. The operation of the present system is as follows: Firstly, the Haar classifier of OpenCV is used to detect the face position, and then the LBPH face recognizer is used to identify the identity of the talker. Finally, the voice response will be activated to provide the profile of the talker to the wearer. Therefore, the instant notification is realized by the people with memory cognitive impairment. The present study uses CAD, CAE and 3D printing technologies to design this wearable device, so it has the characteristics of customization and instant manufacturing. We believe it is suitable for the development of medical aids. This memory-aided device has been tested in the laboratory to prove that it is easy for the user to wear. Moreover, it can establish a personal identification database according to the users’ needs, and could be an assistive device for the people with memory cognitive impairment in the future.
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