Journal of Biomedical Engineering Research (대한의용생체공학회:의공학회지)

The Korean Society of Medical and Biological Engineering (대한의용생체공학회)
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Determination of filtering condition and threshold for detection of Gait-Cycles under Various Gait Speeds and Walkway Slopes

다양한 보행속도와 경사각에 대한 보행수 검출을 위한 필터링 조건과 역치의 결정

  • Kwon, Yu-Ri (School of Biomedical Engineering, Konkuk University) ;
  • Kim, Ji-Won (School of Biomedical Engineering, Konkuk University) ;
  • Lee, Jae-Ho (School of Biomedical Engineering, Konkuk University) ;
  • Tack, Gye-Rae (School of Biomedical Engineering, Konkuk University) ;
  • Eom, Gwang-Moon (School of Biomedical Engineering, Konkuk University)
  • Published : 2009.12.31
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Abstract

The purpose of this study is to determine optimal filtering condition and threshold for the detection of gait-cycles for various walkway slopes as well as gait velocities. Ten young healthy subjects with accelerometer system on thigh and ankle walked on a treadmill at 9 conditions (three speeds and three slopes) for 5 minutes. Two direction signals, i.e. anterior-posterior (AP) and superior-inferior (SI) directions, of each sensor (four sensor orientations) were used to detect specific events of gait cycle. Variation of the threshold (from -1G to 1G) and lowpass cutoff frequency (fc) were applied to the event detection and their performance was evaluated according to the error index (EI), which was defined as the combination of the accuracy and false positive rate. Optimal fc and threshold were determined for each slope in terms of the EI. The optimal fc, threshold and their corresponding EI depended much on the walkway slope so that their coefficients of variation (CV) ranged 19~120%. When all data for 3 slopes were used in the identification of optimal conditions for each sensor, the best error indices for all sensor orientations were comparable ranging 1.43~1.76%, but the optimal fc and threshold depended much on the sensor position. The result indicates that the gait-cycle detection robust to walkway slope is possible by threshold method with well-defined filtering condition and threshold.

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References

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