An IMU-to-Body Alignment Method Applied to Human Gait Analysis

This paper presents a novel calibration procedure as a simple, yet powerful, method to place and align inertial sensors with body segments. The calibration can be easily replicated without the need of any additional tools. The proposed method is validated in three different applications: a computer mathematical simulation; a simplified joint composed of two semi-spheres interconnected by a universal goniometer; and a real gait test with five able-bodied subjects. Simulation results demonstrate that, after the calibration method is applied, the joint angles are correctly measured independently of previous sensor placement on the joint, thus validating the proposed procedure. In the cases of a simplified joint and a real gait test with human volunteers, the method also performs correctly, although secondary plane errors appear when compared with the simulation results. We believe that such errors are caused by limitations of the current inertial measurement unit (IMU) technology and fusion algorithms. In conclusion, the presented calibration procedure is an interesting option to solve the alignment problem when using IMUs for gait analysis.

[1]  Hartmut Witte,et al.  ISB recommendation on definitions of joint coordinate system of various joints for the reporting of human joint motion--part I: ankle, hip, and spine. International Society of Biomechanics. , 2002, Journal of biomechanics.

[2]  Adriano Ferrari,et al.  ‘Outwalk’: a protocol for clinical gait analysis based on inertial and magnetic sensors , 2009, Medical & Biological Engineering & Computing.

[3]  Thomas Seel,et al.  IMU-Based Joint Angle Measurement for Gait Analysis , 2014, Sensors.

[4]  Roman Kamnik,et al.  An inertial and magnetic sensor based technique for joint angle measurement. , 2007, Journal of biomechanics.

[5]  Aurelio Cappozzo,et al.  Joint kinematics estimate using wearable inertial and magnetic sensing modules. , 2008, Gait & posture.

[6]  W. Frontera The world report on disability. , 2012, American journal of physical medicine & rehabilitation.

[7]  Begonya Garcia-Zapirain,et al.  Gait Analysis Methods: An Overview of Wearable and Non-Wearable Systems, Highlighting Clinical Applications , 2014, Sensors.

[8]  Angelo M. Sabatini,et al.  How Angular Velocity Features and Different Gyroscope Noise Types Interact and Determine Orientation Estimation Accuracy , 2015, Sensors.

[9]  G. Carter,et al.  Rehabilitation Management in Neuromuscular Disease , 1997 .

[10]  Steven Morrison,et al.  Reliability of segmental accelerations measured using a new wireless gait analysis system. , 2006, Journal of biomechanics.

[11]  Patrick Boissy,et al.  Inertial Measures of Motion for Clinical Biomechanics: Comparative Assessment of Accuracy under Controlled Conditions - Effect of Velocity , 2013, PloS one.

[12]  Keiji Hashimoto,et al.  Ability for Basic Movement as an Early Predictor of Functioning Related to Activities of Daily Living in Stroke Patients , 2007, Neurorehabilitation and neural repair.

[13]  E S Grood,et al.  A joint coordinate system for the clinical description of three-dimensional motions: application to the knee. , 1983, Journal of biomechanical engineering.

[14]  P H Veltink,et al.  Ambulatory measurement of arm orientation. , 2007, Journal of biomechanics.

[15]  Peter H. Veltink,et al.  Measuring orientation of human body segments using miniature gyroscopes and accelerometers , 2005, Medical and Biological Engineering and Computing.

[16]  Laura Rocchi,et al.  A Wearable System for Gait Training in Subjects with Parkinson's Disease , 2014, Sensors.

[17]  B M Jolles,et al.  Functional calibration procedure for 3D knee joint angle description using inertial sensors. , 2009, Journal of biomechanics.

[18]  Pietro Garofalo,et al.  First in vivo assessment of “Outwalk”: a novel protocol for clinical gait analysis based on inertial and magnetic sensors , 2009, Medical & Biological Engineering & Computing.

[19]  Shigeru Tadano,et al.  Three Dimensional Gait Analysis Using Wearable Acceleration and Gyro Sensors Based on Quaternion Calculations , 2013, Sensors.

[20]  Tao Liu,et al.  Gait Analysis Using Wearable Sensors , 2012, Sensors.

[21]  Laura Rocchi,et al.  Ambulatory measurement of shoulder and elbow kinematics through inertial and magnetic sensors , 2008, Medical & Biological Engineering & Computing.

[22]  Eduardo Palermo,et al.  Experimental evaluation of accuracy and repeatability of a novel body-to-sensor calibration procedure for inertial sensor-based gait analysis , 2014 .

[23]  B. Belgen,et al.  The association of balance capacity and falls self-efficacy with history of falling in community-dwelling people with chronic stroke. , 2006, Archives of physical medicine and rehabilitation.

[24]  M. J. Prentice Orientation Statistics Without Parametric Assumptions , 1986 .

[25]  E. Skordilis,et al.  Validity evidence of the Lateral Step Up (LSU) test for adolescents with spastic cerebral palsy , 2013, Disability and rehabilitation.

[26]  A. Leardini,et al.  Data management in gait analysis for clinical applications. , 1998, Clinical biomechanics.

[27]  L. Lin,et al.  A concordance correlation coefficient to evaluate reproducibility. , 1989, Biometrics.

[28]  Angelo M. Sabatini,et al.  Estimating Orientation Using Magnetic and Inertial Sensors and Different Sensor Fusion Approaches: Accuracy Assessment in Manual and Locomotion Tasks , 2014, Sensors.

[29]  A Brennan,et al.  Quantification of inertial sensor-based 3D joint angle measurement accuracy using an instrumented gimbal. , 2011, Gait & posture.

[30]  Andrea Giovanni Cutti,et al.  Gait analysis in children with cerebral palsy via inertial and magnetic sensors , 2012, Medical & Biological Engineering & Computing.

[31]  A. Cappozzo,et al.  A spot check for assessing static orientation consistency of inertial and magnetic sensing units. , 2011, Gait & posture.

[32]  M. Tomizuka,et al.  Clinical impact of gait training enhanced with visual kinematic biofeedback: Patients with Parkinson’s disease and patients stable post stroke , 2015, Neuropsychologia.

[33]  Angelo M. Sabatini,et al.  Assessment of walking features from foot inertial sensing , 2005, IEEE Transactions on Biomedical Engineering.