IJMTES – SENSORS-BASED WEARABLE SYSTEMS FOR MONITORING OF HUMAN MOVEMENT AND FALLS

Journal Title : International Journal of Modern Trends in Engineering and Science

Author’s Name : N.Dharungeeran, J.JafarAli

Volume 01 Issue o3 March 2014  

ISSN no:  2348-3121 

Page no: 44-49

Abstract— Multiple tri-axial acceleration sensor devices for joint sensing of injured body parts, when an accidental fall occurs. The model transmitted the information fed by the sensors distributed over various body parts to the computer through wireless transmission devices for further analysis and judgment, and employed cognitive adjustment method to adjust the acceleration range of various body parts in different movements .The concept of a fall is in the common sense, it is difficult to describe it precisely, and thus to specify its means of detection. If person was injured, he/she will take some time to recovery and then they will try to walk, at that time there are lots of possibilities to fall down, which we can monitor in receiving side by RF receiver. The accelerating sensors values goes abnormal then alert system (buzzer) will alert in the receiving side .The main focuses on designing a system that prevents a patient from falling down when he/she is unconsciousness. Two accelerating sensors are used to detect the position of patient who has met an accident and these sensors can be placed at different places of the body. If any abnormal activity occurs in any region, AIRBAG will be opened to prevent the person from falling. This information will be displayed in Liquid crystal display as well as PC. Front and Back fall detection is detected using x axis of accelerating sensor and Left and Right fall detection is detected using y axis of accelerating sensor.

Keywords— component, airbag, buzzer, accelerator sensor

Reference

[1] World Health Organization, [Online]. Available: http://www.who.int/topics/en/.
[2] S. R. Lord, C. Sherrington, and H. B. Menz, Falls in Older People: Risk Factors and Strategies for Prevention. Cambridge, U.K.: Cambridge Univ. Press, (2001).
[3] B. G. Celler, N. H. Lovell, and D. Chan, “The potential impact of home telecare on clinical practice,” Med. J. Australia, Vol. 171, pp.(1999).
[4] P. van de Ven, A. Bourke, C. Tavares, R. Feld, J. Nelson, A. Rocha, and G. O. Laighin, “Integration of a suite of sensors in a wireless health sensor platform,” in Prof. IEEE Sensors Conf., 2009, pp. 1678-1683.
[5] M. Chan, E. Campo, D. Estève, and J.-Y. Fourniols, “Smart homes– Current features and future perspectives,” Maturitas, Vol. 64, pp. 90–97, (2009).
[6] A. Godfrey, R. Conway, D. Meagher, and G. ÓLaighin, “Direct measurement of human movement by accelerometry,” Med. Eng. Phys. Vol. 30, pp. 1364–1386, (2008).
[7] P. Bonato, “Wearable sensors/systems and their impact on biomedical engineering,” IEEE Eng. Med. Biol. Mag., Vol. 22, pp. 18-20,(2003).
[8] S. L. Murphy, “Review of physical activity measurement using accelerometers in older adults: Considerations for research design and conduct,” Preventive Med., Vol. 48, pp. 108–114, (2009).
[9] S. J. Preece, J. Y. Goulermas, L. P. J. Kenney, D. Howard, K. Meijer, and R. Crompton, “Activity identification using body-mounted sensors- a review of classification techniques,”Physicol. Meax., Vol. 30,pp. R1–R33, (2009).
[10] M. J. Mathie, A. C. F. Coster, N. H. Lovell, and B. G. Celler, “Accelerometry: Providing an integrated, practical method for long ambulatory monitoring of human movement,” Physiol. Meax, Vol. 25, pp. R1–R20, (2004).

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