Publication Type : Journal Article
Publisher : IEEE Sensors Journal
Source : IEEE Sensors Journal, Volume 16, Number 17, p.6755-6765 (2016)
Url : https://ieeexplore.ieee.org/document/7501503
Keywords : Assistive devices, controller, driving motors, elders, Gesture, gesture identification, Gesture recognition, gpaD-gesture pad, hand gesture recognition method, handicapped aids, HanGes design, Infrared detectors, Injuries, interactive devices, IR sensor, IR sensor-based gesture control wheelchair, joystick-based powered wheelchair control, MCU, medical control systems, medical disorders, Medical services, medical signal processing, Navigation, Neurophysiology, Patient rehabilitation, Performance evaluation, power management circuit, rehabilitation, response time calculation, SCI patients, Sensor systems, spinal cord injury, Stroke patients, Wheelchair, Wheelchairs
Campus : Amritapuri
School : School of Engineering
Center : Amrita Innovation & Research, Humanitarian Technology (HuT) Labs
Department : Electronics and Communication
Verified : Yes
Year : 2016
Abstract : This paper presents a novel and simple hand gesture recognition method to be used in rehabilitation of people who have mobility issues particularly stroke patients and patients with spinal cord injury (SCI). Keeping in mind the reach of such a system for a wider community of people with mobility issues, the proposed low-cost control device called gpaD-gesture pad provides an alternative solution to the joystick-based powered wheelchair control through hand gestures. In this method, IR sensors are used for identifying the simple gestures to control the powered wheelchair to move in any direction. In the proposed prototype system HanGes, a gesture pad that includes IR sensors, MCU and power management circuit is designed for gesture recognition and identification and a controller for driving motors is implemented. HanGes's design, implementation, the response time calculations of the system, testing, performance evaluation with stroke and SCI patients are discussed in detail. With the average success rate of gesture recognition above 99.25% and response time as comparable with that of commercially available joystick controlled wheelchair, HanGes could be a possible alternative to the existing ones. With extensive experiments that demonstrate the accuracy of the system, the user experience, testing with patients, and the implementation cost indicate the superiority of our system.
Cite this Research Publication : Rajesh Kannan Megalingam, Rangan, V., Krishnan, S., and Alinkeezhil, A. B. Edicher, “IR Sensor-Based Gesture Control Wheelchair for Stroke and SCI Patients”, IEEE Sensors Journal, vol. 16, pp. 6755-6765, 2016.