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Cost Efficient Gait Analysis Using Lasers

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Cost Efficient Gait Analysis Using Lasers
Cost Efficient Gait Analysis Using Lasers
Isac Zia isac.zia@hotmail.com

under the direction of Prof. Hamed Hamid Muhammed School of Technology and Health KTH

Research Academy for Young Scientists July 11, 2012

Abstract Gait analysis is the methodic measurement, description and evaluation of factors that affect human locomotion. It can be used for rehabilitation purposes, for optimizing sport results and lower risks of injury and as a diagnostic tool for neurological diseases, example given Parkinson. Hitherto, there are many precise methods of doing gait analysis. However, expensive equipment is often required, otherwise the only option is visual analysis, which is less reliable. This study will construct an inexpensive method to analyze gait, that is both reliable and portable. One laser was attached to each shoulder and two on a helmet put on the subjects’ heads. The lasers formed a formation of laser dots on the ceiling. The test subjects walked on a treadmill, which caused the laser dots to move. These were recorded with a camera. The video sequences were then analyzed with a program written in Matlab. The results showed the laser movement, as intended. By analysing the laser movement in different walking conditions, for example with different shoes, it was shown in this study that they differed and the method could be useful to compare gait. However, further research needs to be undertaken in order to confirm these findings.

Introduction
Biomechanics is an increasingly well-known field of research, which takes a mechanical approach to the human body. As a combination between mechanics and biology, it can help increase our knowledge in orthopaedics and ergonomics, but also in other areas such as rehabilitation and sports [4, 5, 7]. An important sub-field of biomechanics is gait analysis which is the methodical measurement, description and evaluation of factors that affect human locomotion [1, 6]. The invention of the camera made it possible to investigate



References: [1] RB Davis, D Tyburski, and JR Gage. A gait analysis data collection and reduction technique. Human Movement Science, 1991. [2] Sisneros Kim. Biomechanics - A Look at Motion Analysis, 2008. [3] Stacy J Morris. A Shoe-Integrated Sensor System for Wireless Gait Analysis and RealTime Therapeutic Feedback. 2004. [4] Benjamin A Smith. DETERMINATION OF NORMAL OR ABNORMAL GAIT USING A TWO- DIMENSIONAL VIDEO CAMERA DETERMINATION OF NORMAL OR ABNORMAL GAIT USING A TWO-DIMENSIONAL VIDEO CAMERA. 2007. [5] Paolo Soda, Alfonso Carta, Domenico Formica, and Eugenio Guglielmelli. A low-cost video-based tool for clinical gait analysis. Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference, 2009:3979–82, January 2009. [6] Weijun Tao, Tao Liu, Rencheng Zheng, and Hutian Feng. Gait Analysis Using Wearable Sensors. Sensors, 12(2):2255–2283, February 2012. [7] Y.C. Fung. Biomechanics, 1978. [8] Alper Yilmaz, Omar Javed, and Mubarak Shah. Object tracking: A survey. ACM Computing Surveys, 38(4):13–es, December 2006. [9] Jang-hee Yoo, Mark S Nixon, and Human Gait Database. On Laboratory Gait Analysis via Computer Vision 2 Describing Human Gait Motion. pages 109–113, 2002. 8 A clear Matlab Gait Analysis Program obj = mmreader(’name_of_file.avi’); lastFrame = read(obj, inf); endFrame = get(obj, ’NumberOfFrames’) x_koordinater = zeros(endFrame, 4); y_koordinater = zeros(endFrame, 4); for n = 1:endFrame one_frame = read(obj, [n n]); red=one_frame(:,:,1); red = red(1:540,:); BW = red > 10; se = strel(’disk’,10); BW=imclose(BW, se); if 1 %if (n >= 13) && (n

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