Abstract
Quadriplegics are people who cannot use their extremities. Existing aiding devices are costly, complex, not user friendly and they are guardian dependent for movement. In this paper, a Raspberry Pi enabled wheelchair movement control by head movement detection is presented. A head movement detection technique based on Open - Computer Vision image processing is used which detects the user's facial movement in real time using the camera. Using this, the wheelchair motors are controlled and are driven in the indicated direction. Also, numerous sensors such as temperature sensor, pulse rate sensor, accelerometer sensor and fire sensor are added to monitor patient health, safety and well-being.
Highlights
Quadriplegic is a type of paralysis that affects all four limbs
The navigation and control was efficient, cost-effective, comfortable and easy to build with the components which were readily available [1]
Health monitoring of the patient can be achieved with the temperature and pulse sensor
Summary
Quadriplegic is a type of paralysis that affects all four limbs. Quadriplegia appears as a consequence of accident or age. Open-CV algorithm is used to analyze the captured head movement and through this data, motors are controlled, and wheelchair is moved [6]. Main focus of HOG descriptor is on the structure or the shape of an object In this proposed work, a microprocessor, Raspberry Pi is used to enable a standard electric wheelchair control by facial movement detection. A microprocessor, Raspberry Pi is used to enable a standard electric wheelchair control by facial movement detection This idea utilizes a camera attached to the raspberry pi to capture facial movement. Based on the facial movement, Raspberry Pi controls the electric motors of the wheelchair. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP)
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