Evaluating Accuracy and Usability of Microsoft Kinect Sensors and Wearable Sensor for Tele Knee Rehabilitation after Knee Operation

The Microsoft Kinect sensors and wearable sensors are considered as low-cost portable alternative of advanced marker-based motion capture systems for tracking human physical activities. These sensors are widely utilized in several clinical applications. Many studies were conducted to evaluate accuracy, reliability, and usability of the Microsoft Kinect sensors for tracking in static body postures, gait and other daily activities. This study was aimed to asses and compare accuracy and usability of both generation of the Microsoft Kinect sensors and wearable sensors for tracking daily knee rehabilitation exercises. Hence, several common exercises for knee rehabilitation were utilized. Knee angle was estimated as an outcome. The results indicated only second generation of Microsoft Kinect sensors and wearable sensors had acceptable accuracy, where average root mean square error for Microsoft Kinect v2, accelerometers and inertial measure units were 2.09°, 3.11°, and 4.93° respectively. Both generation of Microsoft Kinect sensors were unsuccessful to track joint position while the subject was lying in a bed. This limitation may argue usability of Microsoft Kinect sensors for knee rehabilitation applications.

[1]  Kirk Woolford,et al.  Defining accuracy in the use of Kinect v2 for exercise monitoring , 2015, MOCO.

[2]  Nelci Adriana Cicuto Ferreira Rocha,et al.  Impact of a virtual reality-based intervention on motor performance and balance of a child with cerebral palsy: a case study , 2014, Revista paulista de pediatria : orgao oficial da Sociedade de Pediatria de Sao Paulo.

[3]  Ling Bao,et al.  Activity Recognition from User-Annotated Acceleration Data , 2004, Pervasive.

[4]  B Bonnechère,et al.  Validity and reliability of the Kinect within functional assessment activities: comparison with standard stereophotogrammetry. , 2014, Gait & posture.

[5]  Christoph Kalkbrenner,et al.  Motion Capturing with Inertial Measurement Units and Kinect - Tracking of Limb Movement using Optical and Orientation Information , 2014, BIODEVICES.

[6]  Nigel H. Lovell,et al.  Implementation of a real-time human movement classifier using a triaxial accelerometer for ambulatory monitoring , 2006, IEEE Transactions on Information Technology in Biomedicine.

[7]  Alexander Scholz,et al.  Multiple Kinect Studies , 2011 .

[8]  Richard Wootton,et al.  Internet-based outpatient telerehabilitation for patients following total knee arthroplasty: a randomized controlled trial. , 2011, The Journal of bone and joint surgery. American volume.

[9]  Amee L. Seitz,et al.  Validity and reliability of Kinect skeleton for measuring shoulder joint angles: a feasibility study. , 2015, Physiotherapy.

[10]  Vassiliki Derri,et al.  The effect of Xbox Kinect intervention on balance ability for previously injured young competitive male athletes: a preliminary study. , 2014, Physical therapy in sport : official journal of the Association of Chartered Physiotherapists in Sports Medicine.

[11]  Raymond W. McGorry,et al.  The validity of the first and second generation Microsoft Kinect™ for identifying joint center locations during static postures. , 2015, Applied ergonomics.

[12]  J P Cobb,et al.  Validity and sensitivity of the longitudinal asymmetry index to detect gait asymmetry using Microsoft Kinect data. , 2017, Gait & posture.

[13]  Mansib Rahman,et al.  Beginning Microsoft Kinect for Windows SDK 2.0 , 2017, Apress.

[14]  Yu-Chee Tseng,et al.  A Wireless Human Motion Capturing System for Home Rehabilitation , 2009, 2009 Tenth International Conference on Mobile Data Management: Systems, Services and Middleware.

[15]  Martin Kampel,et al.  Performance evaluation of joint angles obtained by the Kinect v2 , 2015 .

[16]  Ferran Escalada,et al.  Effectiveness of an interactive virtual telerehabilitation system in patients after total knee arthoplasty: a randomized controlled trial. , 2013, Journal of rehabilitation medicine.

[17]  Moataz Eltoukhy,et al.  Improved kinect-based spatiotemporal and kinematic treadmill gait assessment. , 2017, Gait & posture.

[18]  Linda Denehy,et al.  Validity of the Microsoft Kinect for assessment of postural control. , 2012, Gait & posture.

[19]  John Darby,et al.  An evaluation of 3D head pose estimation using the Microsoft Kinect v2. , 2016, Gait & posture.

[20]  Sebastian Madgwick,et al.  Estimation of IMU and MARG orientation using a gradient descent algorithm , 2011, 2011 IEEE International Conference on Rehabilitation Robotics.

[21]  D. Sainsbury,et al.  Color Atlas of Skeletal Landmark Definitions, Serge Van Sint Jan. Churchill Livingstone/Elsevier (2007), 181 pages, £39, ISBN: 9-78-0443-10315-5 , 2009 .

[22]  Simon A. Neild,et al.  Estimation of Upper-Limb Orientation Based on Accelerometer and Gyroscope Measurements , 2008, IEEE Transactions on Biomedical Engineering.

[23]  Ross A Clark,et al.  Gait assessment using the Microsoft Xbox One Kinect: Concurrent validity and inter-day reliability of spatiotemporal and kinematic variables. , 2015, Journal of biomechanics.

[24]  Arantza Illarramendi,et al.  Validation of a Kinect-based telerehabilitation system with total hip replacement patients , 2016, Journal of telemedicine and telecare.

[25]  Fabian de Ponte Müller,et al.  Evaluation of AHRS algorithms for inertial personal localization in industrial environments , 2015, 2015 IEEE International Conference on Industrial Technology (ICIT).

[26]  Albert A. Rizzo,et al.  Interactive game-based rehabilitation using the Microsoft Kinect , 2012, 2012 IEEE Virtual Reality Workshops (VRW).

[27]  Winson C.C. Lee,et al.  Evaluation of the Microsoft Kinect as a clinical assessment tool of body sway. , 2014, Gait & posture.

[28]  John Sell,et al.  The Xbox One System on a Chip and Kinect Sensor , 2014, IEEE Micro.

[29]  H Moffet,et al.  In home telerehabilitation for older adults after discharge from an acute hospital or rehabilitation unit: A proof-of-concept study and costs estimation , 2006, Disability and rehabilitation. Assistive technology.

[30]  Patrick Boissy,et al.  Patients' satisfaction of healthcare services and perception with in-home telerehabilitation and physiotherapists' satisfaction toward technology for post-knee arthroplasty: an embedded study in a randomized trial. , 2011, Telemedicine journal and e-health : the official journal of the American Telemedicine Association.

[31]  Francisco Javier Díaz-Pernas,et al.  Rehabilitation Using Kinect-based Games and Virtual Reality☆ , 2015 .

[32]  D. Roetenberg,et al.  Xsens MVN: Full 6DOF Human Motion Tracking Using Miniature Inertial Sensors , 2009 .

[33]  Muhammad Tahir,et al.  Improving the Accuracy of Human Body Orientation Estimation With Wearable IMU Sensors , 2017, IEEE Transactions on Instrumentation and Measurement.

[34]  Dana Kulić,et al.  Human pose recovery using wireless inertial measurement units , 2012, Physiological measurement.