As people are busy with their day-to-day life, it gets challenging to provide equal attention to work as well as to ailing elders in their homes. In this project, a wearable glove has been designed, which recognizes hand gestures of the patient with the help of flex sensors. By wearing the glove, the patient will be able to operate a basic electrical appliance remotely by using his finger without having anyone to help him. The patient will also be able to call for help by moving one of his fingers. Flex sensors have been used to overcome the limitations of video and body-based gesture recognition. Flex sensors provide faster response with less amount of data to be processed. ZigBee has been used to achieve good range, faster response, better reliability and security when compared to WiFi. This approach was 85% accurate however a delay of 9.2s was observed.
|Commitee:||Ary, James, Wang, Fei|
|School:||California State University, Long Beach|
|School Location:||United States -- California|
|Source:||MAI 55/03M(E), Masters Abstracts International|
|Keywords:||Remote gesture recognition, Wearable glove|
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