Inertial sensors for assessment of joint angles

In this paper, two approaches for estimating joint angles are presented: the first one uses only an accelerometer to estimate hip and knee angles on static postures, whereas the second approach fuses information from multiple sensors to dynamically calculate leg range of motion. Static joint angle results were evaluated against goniometer, which is used as a standard at clinics. Dynamic angles results were compared with Kinect joint segmentation, as well as a custom marker-based video tracking algorithm for angle estimation. For both approaches, the errors obtained when compared with reference systems were very low. Results support that inertial sensors are suitable for use in home-based rehabilitation exercises.

[1]  Kun-Hui Chen,et al.  Wearable Sensor-Based Rehabilitation Exercise Assessment for Knee Osteoarthritis , 2015, Sensors.

[2]  Roberto Nerino,et al.  An improved solution for knee rehabilitation at home , 2014, BODYNETS.

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

[4]  Nicolas Vuillerme,et al.  Mobile Phone-Based Joint Angle Measurement for Functional Assessment and Rehabilitation of Proprioception , 2015, BioMed research international.

[5]  K. Aminian,et al.  Quaternion-based fusion of gyroscopes and accelerometers to improve 3D angle measurement , 2006 .

[6]  Fei-Bin Hsiao,et al.  Development of a Low-Cost Attitude and Heading Reference System Using a Three-Axis Rotating Platform , 2010, Sensors.

[7]  Tao Liu,et al.  Ambulatory measurement and analysis of the lower limb 3D posture using wearable sensor system , 2009, 2009 International Conference on Mechatronics and Automation.

[8]  G. Hansson,et al.  Validity and reliability of triaxial accelerometers for inclinometry in posture analysis , 2001, Medical and Biological Engineering and Computing.

[9]  Adso Fernández-Baena,et al.  Biomechanical Validation of Upper-Body and Lower-Body Joint Movements of Kinect Motion Capture Data for Rehabilitation Treatments , 2012, 2012 Fourth International Conference on Intelligent Networking and Collaborative Systems.

[10]  James McNames,et al.  Shoulder and Elbow Joint Angle Tracking With Inertial Sensors , 2012, IEEE Transactions on Biomedical Engineering.

[11]  Rainer Bader,et al.  Accuracy of a Custom Physical Activity and Knee Angle Measurement Sensor System for Patients with Neuromuscular Disorders and Gait Abnormalities , 2015, Sensors.

[12]  Gregory L. Tangonan,et al.  Digital motion analysis system for rehabilitation using wearable sensors , 2014, 2014 International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM).

[13]  Björn Eskofier,et al.  Estimation of the Knee Flexion-Extension Angle During Dynamic Sport Motions Using Body-worn Inertial Sensors , 2013, BODYNETS.

[14]  Takeo Kanade,et al.  An Iterative Image Registration Technique with an Application to Stereo Vision , 1981, IJCAI.

[15]  References , 1971 .

[16]  Francesco Alonge,et al.  The Use of Accelerometers and Gyroscopes to Estimate Hip and Knee Angles on Gait Analysis , 2014, Sensors.

[17]  Brian Caulfield,et al.  Rehabilitation exercise assessment using inertial sensors: a cross-sectional analytical study , 2014, Journal of NeuroEngineering and Rehabilitation.

[18]  J.-Y. Bouguet,et al.  Pyramidal implementation of the lucas kanade feature tracker , 1999 .