Implementation of Gait Analysis System Based on Inertial Sensors

관성센서 기반 보행 분석 시스템 구현

  • 조재성 (한양대학교 의용생체공학과) ;
  • 강신일 (한양대학교 생체의공학과) ;
  • 이기혁 (한양대학교 생체의공학과) ;
  • 장성호 (한양대학교병원 재활의학교실) ;
  • 김인영 (한양대학교 의공학교실) ;
  • 이종실 (한양대학교 의공학연구소)
  • Received : 2015.05.01
  • Accepted : 2015.05.22
  • Published : 2015.05.30

Abstract

In this paper, we present an inertial sensor-based gait analysis system to measure and analyze lower-limb movements. We developed an integral AHRS(Attitude Heading Reference System) using a combination of rate gyroscope, accelerometer and magnetometer sensor signals. Several AHRS modules mounted on segments of the patient's body provide the quaternions representing the patient segments's orientation in space. And a method is also proposed for calculating three-dimensional inter-segment joint angle which is an important bio-mechanical measure for a variety of applications related to rehabilitation. To evaluate the performance of our AHRS module, the Vicon motion capture system, which offers millimeter resolution of 3D spatial displacements and orientations, is used as a reference. The evaluation resulted in a RMSE(Root Mean Square Error) of 1.08 and 1.72 degree in yaw and pitch angle. In order to evaluate the performance of our the gait analysis system, we compared the joint angle for the hip, knee and ankle with those provided by Vicon system. The result shows that our system will provide an in-depth insight into the effectiveness, appropriate level of care, and feedback of the rehabilitation process by performing real-time limb or gait analysis during the post-stroke recovery.

본 논문은 하지의 움직임을 측정하고 분석할 수 있는 관성센서 기반 보행분석 시스템에 관한 것이다. 본 시스템 구현을 위해 자이로스코프, 가속도계 및 지자계 신호를 이용한 자세 방위 측정장치 모듈을 일체형으로 개발하였으며, 다수의 모듈을 환자의 분절에 부착하여 공간상에서 각 분절의 방위각을 제공할 수 있도록 하였다. 또한 재활과 관련된 많은 응용에 있어 중요한 생체역학 측정값인 신체 분절간의 관절각을 추출하는 알고리즘을 제안하였다. 개발한 자세 방위 측정장치 모듈의 성능을 평가하기 위하여 3차원 공간상의 변위 및 방위를 밀리미터 해상도로 제공할 수 있는 Vicon을 참조 측정 시스템으로 이용하였으며, yaw와 pitch에서 1.08, 1.72도의 평균 제곱근 오차를 얻을 수 있었다. 보행 분석 시스템의 성능 검증을 위하여 7개의 AHRS 모듈을 하지에 부착하고 고관절, 무릎, 발목에 대한 관절각을 계산하여, Vicon과의 비교 실험을 수행하였다. 실험 결과 본 연구에서 개발한 시스템은 뇌졸중 후 회복단계 동안 사지 및 보행 동작을 실시간으로 분석, 제공함으로서 재활의 효과, 난이도 조절 및 피드백 요소를 제공할 수 있을 것으로 판단된다.

Keywords

References

  1. Perry J, Gait Analysis: Normal and PathologicalFunction. New Jersey: Slak Inc, pp.281-340, 2010.
  2. F.M. Ivey, C.E. Hafer-Macko, and R.F. Macko, "Exercise rehabilitation after stroke," The Journal of the American Society for Experimental NeuroTherapeutics, vol.3, no.4, pp.439-450, 2006.
  3. J.D. Richards, A. Pramanik, L. Sykesand and V.M. Pomeroy, "A comparison of knee kinematic characteristics of stroke patients and age-matched healthy volunteers," Clinical Rehabilitation, vol.17, no.5, pp.565-571, 2003. https://doi.org/10.1191/0269215503cr651oa
  4. A.A. Carmo, A.F.R. Kleiner, P.H. Lodo da Costa and R.M.L. Barros, "Three-dimensional kinematic analysis of upper and lower limb motion during gait of post-stroke patients," Brazilian Jounal of Medical and Biological Research, vol.45, no.6, pp. 537-545, 2012. https://doi.org/10.1590/S0100-879X2012007500051
  5. Chen CL, and Chen HC, "Gait Performance with Compensatory Adaptations in Stroke Patients with Different Degrees of Motor Recovery," Am J Phys Med Rehabil, vol.43, no.4, pp.413-420, vol.82, no.12, pp. 925-935, 2003. https://doi.org/10.1097/01.PHM.0000098040.13355.B5
  6. H. Zheng, N.D. Black, and N.D. Harris, "Position-sensing technologies for movement analysis in stroke rehabilitation," Medical & Biological Engineering & Computing, vol.43, no.4, pp.413-420, 2005. https://doi.org/10.1007/BF02344720
  7. J. Boudarham, N. Roche, D. and Pradon, C. Bonnyaud, "Variation in kinematics during clinical gait analysis in stroke patients," Plos One, vol.8, no.6, 2013.
  8. Yuta Karasawa and Yuta Teruyama, "A Trial of Making Reference Gait Data for Simple Gait Evaluation System with Wireless Inertial Sensors," 35th Annual International Conference of the IEEE EMBS, Osaka, Japan, July. 2013.
  9. R.K. Begg and W.A. Sparrow, "Ageing effects on knee and ankle joint angles at key events and phase of the gait cycle," Journal of Medical Engineering & Technology, vol.30, no.6, pp.382-389, 2006. https://doi.org/10.1080/03091900500445353
  10. Sebastian O.H. Madwick, Andrew J.L. Harrison, and Ravi Vaidyanathan, "Estimation of IMU and MARG orientation using a gradient descent algorithm," IEEE International Conference on Rehabilitation Robotics, Zurich, Switzerland, Sept. 2005.
  11. 강신일, 조재성, 임도형, 이종실, 김인영, "재활을 위한 관성센서 기반 모션 분석 시스템 구현," 한국재활복지공학회 2014, 제7권, 제2호, pp. 47-54, 2013.
  12. A. Brennan, J. Zhang, K. Deluzio, Q.Li, "Quantification of inertial sensor-based 3D joint angle measurement accuracy using an instrumented gimbal," Gait & Posture, vol. 34, pp. 320-323, 2011. https://doi.org/10.1016/j.gaitpost.2011.05.018
  13. T. Cloete, and C. Scheffer, "Benchmarking of a full-body inertial motion capture system for clinical gait analysis," presented at 30th Annual nternational IEEE EMBS Conference, 2008.