Authors :
Balamurugan K, Sindhu S, Selva Suba Jenifer J, Saranya P.
Volume/Issue :
Volume 3 - 2018, Issue 3 - March
Google Scholar :
https://goo.gl/DF9R4u
Scribd :
https://goo.gl/EUQCsK
Thomson Reuters ResearcherID :
https://goo.gl/3bkzwv
Abstract :
According to a report from the World Health Organization, every year, 250,000-500,000 new spinal cord injuries occur around the world. A spinal cord injury shatters people’s lives in a fraction of a second, leaving them paralyzed for the rest of their lives. To aid paraplegics, variety of electric wheelchairs exists, but these cannot be used by quadriplegics, i.e. persons who cannot move any of their body parts, except head. The concept of Smart Wheelchair is implemented to facilitate locomotion and localization of the quadriplegics. We use MEMS sensor to detect the head movements and corresponding signal is fed to the microcontroller. The microcontroller controls the wheelchair directions with the help of motor drive circuits. We also include the eye blink sensor and voice recognition sensors to overcome the limitations of the existing systems.
Keywords :
Quadriplegics; MEMS sensor; PIC16F877A; Eye Blink Sensor; Motor driver; Voice Recognizer.
According to a report from the World Health Organization, every year, 250,000-500,000 new spinal cord injuries occur around the world. A spinal cord injury shatters people’s lives in a fraction of a second, leaving them paralyzed for the rest of their lives. To aid paraplegics, variety of electric wheelchairs exists, but these cannot be used by quadriplegics, i.e. persons who cannot move any of their body parts, except head. The concept of Smart Wheelchair is implemented to facilitate locomotion and localization of the quadriplegics. We use MEMS sensor to detect the head movements and corresponding signal is fed to the microcontroller. The microcontroller controls the wheelchair directions with the help of motor drive circuits. We also include the eye blink sensor and voice recognition sensors to overcome the limitations of the existing systems.
Keywords :
Quadriplegics; MEMS sensor; PIC16F877A; Eye Blink Sensor; Motor driver; Voice Recognizer.
