초록

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Abstract ▼ AI-Helper

Smartphones have no age limit and are used in various fields, but when used for a long time, physical problems such as carpal tunnel syndrome may occur. To prevent carpal tunnel syndrome, proper posture and constant stretching are recommended during daily life, but it is not easy for users to recogn...

Smartphones have no age limit and are used in various fields, but when used for a long time, physical problems such as carpal tunnel syndrome may occur. To prevent carpal tunnel syndrome, proper posture and constant stretching are recommended during daily life, but it is not easy for users to recognize and execute it them themselves. Therefore, measures are needed to prevent wrist tunnel syndrome during everyday life by encouraging users to recognize risks on their own and to encourage stretching. In this paper, we propose a wrist motion recognition based carpal tunnel syndrome monitoring system. The proposed system uses acceleration and gyro sensors to recognize the risk of carpal tunnel syndrome and provide medical information and life guidelines. Smartphone usage time is set and wallpaper is automatically locked when the set time is exceeded. The system detects a user's wrist movement to unlock smartphone. To evaluate the system's performance, 4 specific wrist motions were used. Using 50 wrist motions each on 5 users, system showed a high detection rate of 98.5%. In addition, the results of the performance evaluation showed that smartphone usage time reduces when system is worn for longer period.

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