Abstract
This chapter develops a computer learning assistant system with wrist-wearable devices for the elderly, designated as WristEye, which can be used to analyze the computer learning attitudes, reactions, and behaviors of elderly individuals whilst in computer learning classes. WristEye is equipped with a kinematic sensor to effectively detect the changes in the orientation and vertical acceleration of the elderly wrist and to determine the corresponding operations in the learning computer, i.e., moving the mouse, hitting the keyboard, idle, and swinging the mouse. Furthermore, a remote backend server receives the detected signal from the wearable unit via a Wireless Sensor Network (WSN) and then identifies the corresponding computer learning effectiveness. The experimental results show that WristEye has a classification accuracy to recognize computer learning status of elderly individuals.
Published Version
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