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Multi-Module Intelligent Wheelchair

Nehal Dash, Sanghamitra Debta

Abstract


In this modern world, automation turned into the essential reason for any new gadget. In the vast majority of the gadgets and types of equipment, MEMS go about as a compelling mix according to necessities. MEMS and sensor based wheelchair in particular “IntelliWheelZ” that gives the distinctively capable individuals with an answer for self-sufficient motion both at indoor and open air conditions. IntelliWheelZ is a minimal effort multi-segmental battery worked independent wheelchair with straightforward easy to understand ergonomics. IntelliWheelZ comprises of four modules or segments. Firstly, MEMS is most appropriate for those sort of debilitate individuals who have any one working joint in their body. Furthermore, voice recognition segment permits the wheel seat to proceed onward the premise of voice order sustained into it according to necessity. Remote control system is the third segment that controls the movement of wheel seat through switches of a remote controlled gadget on the standard of remote detecting and transfer circuit. Last segment of the wheel seat is the obstacle sensing and detection mechanism that faculties and recognizes the snag on the way and maintains a strategic distance from the wheel seat from mishaps. Consolidating every one of these modules the aggregate use of IntelliWheelZ is under 10% of the cost of autonomous and powered wheelchairs instantly accessible in the market. Consequently the automatic portability and its minimal cost permit us to say: “IntelliWheelZ”—A MEMS based multi segmental low cost autonomous wheel chair for successful indoor and outdoor mobility.

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References


Government of India, Ministry of Home Affairs. Our Census, Our Future. Available Online at; punjabcensus.gov.in/pdf/circulars/dco18.pdf.

Julianna Arva et al. Mechanical Efficiency and user power requirement with a push rim activated power assisted wheelchair. Medical Engineering & Physics. Dec 2001; 23(10): 699–705p

Howarth SJ et al. Use of a geared wheelchair wheel to reduce propulsive muscular demand during ramp ascent: Analysis of muscle activation and kinematics. Clinical Biomechanics. Jan 2010; 25(1): 21–28p.

Bruno Flament, Yanis Caritu, Movea. Use of MEMS Motion Sensors for Embedded Mobile Applications. (ebook).

Büsching F et al. Computer Methods and Programs in Biomedicine. Science Direct. May 2012; 106(2): 79–88p

Media Anugerah Ayu et al. A comparison study of classifier algorithms for mobile-phone’s accelerometer based activity recognition. Procedia Engineering. 2012; 41(224-229): 4–6p.

Anusuya MA and Katti SK. Speech Recognition by Machine: A Review. IJCSIS International Journal of Computer Science and Information Security. 2009; 6(3): 1–25p.

Kim J et al. Effectiveness of a remote accessibility assessment system for wheelchair users using virtualized reality. Archives of Physical Medicine and Rehabilitation. Mar 2008; 89(3): 470–479p.

K-one Robotics, 2nd Edn, 2009; 1–6p. http://www.springer.com/us/book.




DOI: https://doi.org/10.37591/joma.v3i3.7248

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