Joint Parameter Estimation Using Magneto and Inertial Measurement Units
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- 英文论文题名：Joint Parameter Estimation Using Magneto and Inertial Measurement Units
- 论文作者：Yu-Tao Liu ; Yong-An Zhang ; Ming Zeng
- 英文论文作者：Yu-Tao Liu ; Yong-An Zhang ; Ming Zeng ; Harbin Institute of Technology
- 年：2017
- 作者机构：Harbin Institute of Technology;
- 英文论文关键词：Motion capture ; Joint parameters ; Acceleration kinematics ; Least square estimation
- 会议召开时间：2017-07-26
- 会议录名称：第36届中国控制会议论文集（B）
- 英文会议录名称：Proceedings of the 36th Chinese Control Conference（B）
- 语种：英文
- 分类号：TP391.9
- 学会代码：KZLL
- 会议名称：第36届中国控制会议
- 会议地点：中国辽宁大连
- 主办单位：中国自动化学会控制理论专业委员会
- 学会名称：中国自动化学会控制理论专业委员会
- 页数：6
- 文件大小：349k
- 原文格式：D
- 会议级别：全国
摘要
This paper aims to propose an effortless procedure to determine the joint center location and limb length using Magneto and Inertial Measurement Units(M-IMU) based motion capture data. By exploiting the joint acceleration kinematic constraints, we establish an explicit relationship between the M-IMU measurements and the joint center location. Then, with a least square algorithm, the joint parameters can be estimated from the M-IMU measurements generated by a set of prescribed joint motions. The whole procedure doesn't require any knowledge about human anatomy and additional equipment. Computer simulations and experiments with four healthy subjects are conducted to validate the proposed algorithm. Simulation results show that the proposed method is robust against the measurement noise. Experiments show good limb length estimate can be obtained compared with the manual measurements.
This paper aims to propose an effortless procedure to determine the joint center location and limb length using Magneto and Inertial Measurement Units(M-IMU) based motion capture data. By exploiting the joint acceleration kinematic constraints, we establish an explicit relationship between the M-IMU measurements and the joint center location. Then, with a least square algorithm, the joint parameters can be estimated from the M-IMU measurements generated by a set of prescribed joint motions. The whole procedure doesn't require any knowledge about human anatomy and additional equipment. Computer simulations and experiments with four healthy subjects are conducted to validate the proposed algorithm. Simulation results show that the proposed method is robust against the measurement noise. Experiments show good limb length estimate can be obtained compared with the manual measurements.
This paper aims to propose an effortless procedure to determine the joint center location and limb length using Magneto and Inertial Measurement Units(M-IMU) based motion capture data. By exploiting the joint acceleration kinematic constraints, we establish an explicit relationship between the M-IMU measurements and the joint center location. Then, with a least square algorithm, the joint parameters can be estimated from the M-IMU measurements generated by a set of prescribed joint motions. The whole procedure doesn't require any knowledge about human anatomy and additional equipment. Computer simulations and experiments with four healthy subjects are conducted to validate the proposed algorithm. Simulation results show that the proposed method is robust against the measurement noise. Experiments show good limb length estimate can be obtained compared with the manual measurements.
引文
[1]K.K.Min,K.Ryu,Y.Oh,and S.R.Oh,“Implementation of real-time motion and force capturing system for telemanipulation based on semg signals and imu motion data,”in IEEE International Conference on Robotics and Automation,pp.5658-5664,2014.
[2]Y.Tao,H.Hu,and H.Zhou,“Integration of vision and inertial sensors for 3d arm motion tracking in home-based rehabilitation,”The International Journal of Robotics Research,vol.26,no.6,pp.607-624,2007.
[3]H.Zhou,H.Hu,N.D.Harris,and J.Hammerton,“Applications of wearable inertial sensors in estimation of upper limb movements,”Biomedical Signal Processing and Control,vol.1,no.1,pp.22-32,2006.
[4]K.Liu,T.Liu,K.Shibata,and Y.Inoue,“Ambulatory measurement and analysis of the lower limb 3d posture using wearable sensor system,”in International Conference on Mechatronics and Automation,pp.3065-3069,2009.
[5]B.Kayis and A.Ozok,“The anthropometry of turkish army men,”Applied ergonomics,vol.22,no.1,pp.49-54,1991.
[6]M.H.Schwartz and A.Rozumalski,“A new method for estimating joint parameters from motion data,”Journal of Biomechanics,vol.38,no.1,pp.107-116,2005.
[7]V.Camomilla,A.Cereatti,G.Vannozzi,and A.Cappozzo,“An optimized protocol for hip joint centre determination using the functional method,”Journal of Biomechanics,vol.39,no.6,pp.1096-1106,2006.
[8]K.Halvorsen,“Bias compensated least squares estimate of the center of rotation,”Journal of Biomechanics,vol.36,no.7,pp.999-1008,2003.
[9]T.F.Besier,D.L.Sturnieks,J.A.Alderson,and D.G.Lloyd,“Repeatability of gait data using a functional hip joint centre and a mean helical knee axis,”Journal of Biomechanics,vol.36,no.8,pp.1159-1168,2003.
[10]R.A.Siston and S.L.Delp,“Evaluation of a new algorithm to determine the hip joint center,”Journal of Biomechanics,vol.39,no.1,pp.125-130,2006.
[11]S.Koo and T.P.Andriacchi,“The knee joint center of rotation is predominantly on the lateral side during normal walking,”Journal of Biomechanics,vol.41,no.6,pp.1269-1273,2008.
[12]L.Y.Chang and N.S.Pollard,“Constrained least-squares optimization for robust estimation of center of rotation,”Journal of Biomechanics,vol.40,no.6,pp.1392-1400,2007.
[13]S.J.Piazza,N.Okita,and P.R.Cavanagh,“Accuracy of the functional method of hip joint center location:effects of limited motion and varied implementation,”Journal of Biomechanics,vol.34,no.7,pp.967-973,2001.
[14]S.J.Piazza,A.Erdemir,N.Okita,and P.R.Cavanagh,“Assessment of the functional method of hip joint center location subject to reduced range of hip motion,”Journal of Biomechanics,vol.37,no.3,pp.349-356,2004.
[15]J.Gabriel,J.Brostow,and J.K.Hodgins,“Automatic joint parameter estimation from magnetic motion capture data,”Georgia Institute of Technology,2000.
[16]A.G.Kirk,J.F.O’Brien,and D.A.Forsyth,“Skeletal parameter estimation from optical motion capture data,”p.1185,2005.
[17]Q.Yuan,I.-M.Chen,and A.W.Sin,“Method to calibrate the skeleton model using orientation sensors,”in Robotics and Automation(ICRA),2013 IEEE International Conference on,pp.5297-5302,IEEE,2013.
[18]M.S.Karunarathne,S.Li,S.W.Ekanayake,and P.N.Pathirana,“A machine-driven process for human limb length estimation using inertial sensors,”in IEEE International Conference on Industrial and Information Systems,pp.429-433,2015.
[2]Y.Tao,H.Hu,and H.Zhou,“Integration of vision and inertial sensors for 3d arm motion tracking in home-based rehabilitation,”The International Journal of Robotics Research,vol.26,no.6,pp.607-624,2007.
[3]H.Zhou,H.Hu,N.D.Harris,and J.Hammerton,“Applications of wearable inertial sensors in estimation of upper limb movements,”Biomedical Signal Processing and Control,vol.1,no.1,pp.22-32,2006.
[4]K.Liu,T.Liu,K.Shibata,and Y.Inoue,“Ambulatory measurement and analysis of the lower limb 3d posture using wearable sensor system,”in International Conference on Mechatronics and Automation,pp.3065-3069,2009.
[5]B.Kayis and A.Ozok,“The anthropometry of turkish army men,”Applied ergonomics,vol.22,no.1,pp.49-54,1991.
[6]M.H.Schwartz and A.Rozumalski,“A new method for estimating joint parameters from motion data,”Journal of Biomechanics,vol.38,no.1,pp.107-116,2005.
[7]V.Camomilla,A.Cereatti,G.Vannozzi,and A.Cappozzo,“An optimized protocol for hip joint centre determination using the functional method,”Journal of Biomechanics,vol.39,no.6,pp.1096-1106,2006.
[8]K.Halvorsen,“Bias compensated least squares estimate of the center of rotation,”Journal of Biomechanics,vol.36,no.7,pp.999-1008,2003.
[9]T.F.Besier,D.L.Sturnieks,J.A.Alderson,and D.G.Lloyd,“Repeatability of gait data using a functional hip joint centre and a mean helical knee axis,”Journal of Biomechanics,vol.36,no.8,pp.1159-1168,2003.
[10]R.A.Siston and S.L.Delp,“Evaluation of a new algorithm to determine the hip joint center,”Journal of Biomechanics,vol.39,no.1,pp.125-130,2006.
[11]S.Koo and T.P.Andriacchi,“The knee joint center of rotation is predominantly on the lateral side during normal walking,”Journal of Biomechanics,vol.41,no.6,pp.1269-1273,2008.
[12]L.Y.Chang and N.S.Pollard,“Constrained least-squares optimization for robust estimation of center of rotation,”Journal of Biomechanics,vol.40,no.6,pp.1392-1400,2007.
[13]S.J.Piazza,N.Okita,and P.R.Cavanagh,“Accuracy of the functional method of hip joint center location:effects of limited motion and varied implementation,”Journal of Biomechanics,vol.34,no.7,pp.967-973,2001.
[14]S.J.Piazza,A.Erdemir,N.Okita,and P.R.Cavanagh,“Assessment of the functional method of hip joint center location subject to reduced range of hip motion,”Journal of Biomechanics,vol.37,no.3,pp.349-356,2004.
[15]J.Gabriel,J.Brostow,and J.K.Hodgins,“Automatic joint parameter estimation from magnetic motion capture data,”Georgia Institute of Technology,2000.
[16]A.G.Kirk,J.F.O’Brien,and D.A.Forsyth,“Skeletal parameter estimation from optical motion capture data,”p.1185,2005.
[17]Q.Yuan,I.-M.Chen,and A.W.Sin,“Method to calibrate the skeleton model using orientation sensors,”in Robotics and Automation(ICRA),2013 IEEE International Conference on,pp.5297-5302,IEEE,2013.
[18]M.S.Karunarathne,S.Li,S.W.Ekanayake,and P.N.Pathirana,“A machine-driven process for human limb length estimation using inertial sensors,”in IEEE International Conference on Industrial and Information Systems,pp.429-433,2015.