Design and Test of MEMS Attitude Measurement Unit for Fall Detection

Article Preview

Abstract:

Fall is a risky event in the elderly people’s daily life, it often cause serious injury both in physiology and psychology. A MEMS attitude measurement system is designed for fall detection in real time. This paper presents the design and error test of the attitude measurement unit. Each unit contains orthogonally mounted triads of accelerometers, magnetometers and gyros. With an integrated microcontroller for attitude calculating and flash for data storage, the size of the unit is 32mm×23mm×12mm. An extended Kalman filter based on quaternions is designed for attitude measurement. The digital angle output rate is 100Hz. A new method based on coordinate transformation for attitude measurement error test is introduced, using a single axis turntable and a fixed angle wedge. Theory of the testing method is presented and test experiments are performed. Test results show that attitude measurement error is less than 2°, which meets the requirement of fall detection precision. The fall detection system consists of five attitude measurement units fixed on the human legs and waist.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

465-470

Citation:

Online since:

June 2011

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2011 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Wiebren Z, Kamiar A. Mobility assessment in older people: new possibilities and challenges. Eur J Ageing, 2007, 4, 3-12.

Google Scholar

[2] Lord SR, Ward JA, Williams P, et al. An epidemiological study of falls in older community –dwelling women: the Randwick falls and fractures study. Aust J Public Health 1993, 17(3), 240-245.

DOI: 10.1111/j.1753-6405.1993.tb00143.x

Google Scholar

[3] D. Wild, U. S. Nayak, and B. Isaacs, How dangerous are falls in old people at home?, BrMed J (Clin Res Ed), 1981, 282, 266-8.

DOI: 10.1136/bmj.282.6260.266

Google Scholar

[4] M.N. Nyan, F. E. H. Tay, and Matthew Z.E. Mah. Application of motion analysis system in pre-impact fall detection. Journal of Biomechanics, 2008, 41, 2297-2304.

DOI: 10.1016/j.jbiomech.2008.03.042

Google Scholar

[5] Popescu M, Li Y, Skubic M, et al. An acoustic fall detector system that uses sound height information to reduce the false alarm rate. Conf Proc IEEE Eng Med Biol Soc, 2008, 4628-31.

DOI: 10.1109/iembs.2008.4650244

Google Scholar

[6] A.K. Bourke, J. V. O. B., G.M. Lyons. Evaluation of a threshold-based tri-axial accelerometer fall detection algorithm. Gait & Posture, 2007, 26, 194-199.

DOI: 10.1016/j.gaitpost.2006.09.012

Google Scholar

[7] A.K. Bourke, G.M. Lyons. A threshold-based detection algorithm using a bi-axial gyroscope sensor. Medical Engineering & Physics, 2008, 30(1), 84-90.

DOI: 10.1016/j.medengphy.2006.12.001

Google Scholar

[8] Hwang JY, Kang JM, Jang YW, et al. Development of novel algorithm and real-time monitoring ambulatory system using bluetooth module for fall detection in the elderly. Conf Proc IEEE Eng Med Biol Soc. 2004, 3, 2204-7.

DOI: 10.1109/iembs.2004.1403643

Google Scholar

[9] Analog Devices Inc., Small, low power, 3-axis ±3g accelerometer ADXL335, http: /www. analog. com/en/mems/low-g-accelerometers/adxl335/products/product. html, (2010).

Google Scholar

[10] Honeywell Inc., 3-axis digital compass IC HMC5843, http: /www. honeywell. com/sites/portal?smap=aerospace&page=Magnetic-Sensors3&theme=T15&catID=CF84B17AB-A90F-716D-10BC-A1E75441138E&id=HF916B4E0-4F71-9DB5-DFA8-51B1944918EE&sel=2&sel4=1, (2009).

Google Scholar

[11] Analog Devices Inc., Yaw rate gyroscope with SPIADIS16100, http: /www. analog. com/en/other-products/multi-chip/adis16100/products/product. html , (2006).

Google Scholar

[12] Silicon Laboratories Inc., MCU C8051F411, https: /www. silabs. com/pages/DownloadDoc. aspx?FILEURL=Support%20Documents/TechnicalDocs/C8051F41x. pdf, (2008).

Google Scholar