Real-time Estimate of Body Kinematics During a Planar Squat Task Using a Single Inertial Measurement Unit

This study aimed at the real-time estimation of the lower-limb joint and torso kinematics during a squat exercise, performed in the sagittal plane, using a single inertial measurement unit placed on the lower back. The human body was modeled with a 3-DOF planar chain. The planar IMU orientation and vertical displacement were estimated using one angular velocity and two acceleration components and a weighted Fourier linear combiner. The ankle, knee, and hip joint angles were thereafter obtained through a novel inverse kinematic module based on the use of a Jacobian pseudoinverse matrix and null-space decoupling. The aforementioned algorithms were validated on a humanoid robot for which the mechanical model used and the measured joint angles virtually exhibited no inaccuracies. Joint angles were estimated with a maximal error of 1.5°. The performance of the proposed analytical and experimental methodology was also assessed by conducting an experiment on human volunteers and by comparing the relevant results with those obtained through the more conventional photogrammetric approach. The joint angles provided by the two methods displayed differences equal to 3 ± 1°. These results, associated with the real-time capability of the method, open the door to future field applications in both rehabilitation and sport.

[1]  N.V. Thakor,et al.  Adaptive cancelling of physiological tremor for improved precision in microsurgery , 1998, IEEE Transactions on Biomedical Engineering.

[2]  Aurelio Cappozzo,et al.  Minimum measured-input models for the assessment of motor ability. , 2002, Journal of biomechanics.

[3]  A. Cappozzo,et al.  Trunk orientation estimate during walking using gyroscope sensors , 2012, 2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob).

[4]  A. Laub,et al.  The singular value decomposition: Its computation and some applications , 1980 .

[5]  D. Marquardt An Algorithm for Least-Squares Estimation of Nonlinear Parameters , 1963 .

[6]  Win Tun Latt,et al.  Drift-Free Position Estimation of Periodic or Quasi-Periodic Motion Using Inertial Sensors , 2011, Sensors.

[7]  Robert B. Miller,et al.  Response time in man-computer conversational transactions , 1899, AFIPS Fall Joint Computing Conference.

[8]  Marco Donati,et al.  An enhanced estimate of initial contact and final contact instants of time using lower trunk inertial sensor data. , 2012, Gait & posture.

[9]  Nitish V. Thakor,et al.  An adaptive estimation of periodic signals using a Fourier linear combiner , 1994, IEEE Trans. Signal Process..

[10]  Wisama Khalil,et al.  Modeling, Identification and Control of Robots , 2003 .

[11]  Bruno Siciliano,et al.  Kinematic control of redundant robot manipulators: A tutorial , 1990, J. Intell. Robotic Syst..

[12]  V. L. Fuschillo,et al.  Calibrated 2D Angular Kinematics by Single-Axis Accelerometers: From Inverted Pendulum to ${\rm N}$-Link Chain , 2012, IEEE Sensors Journal.

[13]  A. Liegeois,et al.  Automatic supervisory control of the configuration and behavior of multi-body mechanisms , 1977 .

[14]  K.,et al.  Effect of Knee Position on Hip and Knee Torques During the Barbell Squat , 2003, Journal of strength and conditioning research.

[15]  D R Pedersen,et al.  A comparison of the accuracy of several hip center location prediction methods. , 1990, Journal of biomechanics.

[16]  C. Mazzà,et al.  A least-squares identification algorithm for estimating squat exercise mechanics using a single inertial measurement unit. , 2012, Journal of biomechanics.

[17]  Win Tun Latt,et al.  Double adaptive bandlimited multiple Fourier linear combiner for real-time estimation/filtering of physiological tremor , 2010, Biomed. Signal Process. Control..

[18]  Aurelio Cappozzo,et al.  An optimized Kalman filter for the estimate of trunk orientation from inertial sensors data during treadmill walking. , 2012, Gait & posture.

[19]  Daniel Tik-Pui Fong,et al.  The Use of Wearable Inertial Motion Sensors in Human Lower Limb Biomechanics Studies: A Systematic Review , 2010, Sensors.

[20]  Anthony A. Maciejewski,et al.  The Singular Value Decomposition: Computation and Applications to Robotics , 1989, Int. J. Robotics Res..

[21]  C. Mazzà,et al.  An Optimization Algorithm for Human Joint Angle Time-History Generation Using External Force Data , 2004, Annals of Biomedical Engineering.

[22]  U-Xuan Tan,et al.  Estimating Displacement of Periodic Motion With Inertial Sensors , 2008, IEEE Sensors Journal.

[23]  Yoshihiko Nakamura,et al.  Inverse kinematic solutions with singularity robustness for robot manipulator control , 1986 .