Calculating Reachable Workspace Volume for Use in Quantitative Medicine

Quantitative measures of the space an individual can reach is essential for tracking the progression of a disease and the effects of therapeutic intervention. The reachable workspace can be used to track an individuals’ ability to perform activities of daily living, such as feeding and grooming. There are few methods for quantifying upper limb performance, none of which are able to generate a reachable workspace volume from motion capture data. We introduce a method to estimate the reachable workspace volume for an individual by capturing their observed joint limits using a low cost depth camera. This method is then tested on seven individuals with varying upper limb performance. Based on these initial trials, we found that the reachable workspace volume decreased as muscular impairment increased. This shows the potential for this method to be used as a quantitative clinical assessment tool.

[1]  Ruzena Bajcsy,et al.  Evaluation of upper extremity reachable workspace using Kinect camera. , 2013, Technology and health care : official journal of the European Society for Engineering and Medicine.

[2]  Philippe Poignet,et al.  Joint angle estimation in rehabilitation with inertial sensors and its integration with Kinect , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[3]  A K Sengupta,et al.  Maximum reach envelope for the seated and standing male and female for industrial workstation design , 2000, Ergonomics.

[4]  Stacy J. Morris Bamberg,et al.  A feasibility study of an upper limb rehabilitation system using kinect and computer games , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[5]  L. Macedo,et al.  Differences in range of motion between dominant and nondominant sides of upper and lower extremities. , 2008, Journal of manipulative and physiological therapeutics.

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

[7]  R W Bohannon,et al.  Manual muscle test scores and dynamometer test scores of knee extension strength. , 1986, Archives of physical medicine and rehabilitation.

[8]  Oussama Khatib,et al.  Springer Handbook of Robotics , 2007, Springer Handbooks.

[9]  A. Fugl-Meyer,et al.  The post-stroke hemiplegic patient. 1. a method for evaluation of physical performance. , 1975, Scandinavian journal of rehabilitation medicine.

[10]  Arantza Illarramendi,et al.  KiReS: A Kinect-based telerehabilitation system , 2013, 2013 IEEE 15th International Conference on e-Health Networking, Applications and Services (Healthcom 2013).

[11]  Julius Ziegler,et al.  Tracking of the Articulated Upper Body on Multi-View Stereo Image Sequences , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[12]  Jeffrey K. Uhlmann,et al.  New extension of the Kalman filter to nonlinear systems , 1997, Defense, Security, and Sensing.

[13]  N Klopcar,et al.  A kinematic model of the shoulder complex to evaluate the arm-reachable workspace. , 2007, Journal of biomechanics.

[14]  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.

[15]  John Croney Anthropometry for designers , 1971 .

[16]  Lynne Baillie,et al.  Exploring & designing tools to enhance falls rehabilitation in the home , 2013, CHI.

[17]  D. Escolar,et al.  Clinical evaluator reliability for quantitative and manual muscle testing measures of strength in children , 2001, Muscle & nerve.

[18]  M. Brooke,et al.  Clinical trial in duchenne dystrophy. I. The design of the protocol , 1981, Muscle & nerve.

[19]  P. Enright,et al.  The six-minute walk test. , 2003, Respiratory care.

[20]  Herbert Edelsbrunner,et al.  Three-dimensional alpha shapes , 1992, VVS.

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

[22]  Jadran Lenarčič,et al.  Kinematic Model for Determination of Human Arm Reachable Workspace , 2005 .

[23]  S. Studenski,et al.  Functional reach: a new clinical measure of balance. , 1990, Journal of gerontology.

[24]  Rudolph van der Merwe,et al.  The unscented Kalman filter for nonlinear estimation , 2000, Proceedings of the IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium (Cat. No.00EX373).

[25]  Albert A. Rizzo,et al.  Development and evaluation of low cost game-based balance rehabilitation tool using the microsoft kinect sensor , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[26]  Sriram Subramanian,et al.  Talking about tactile experiences , 2013, CHI.

[27]  Ruzena Bajcsy,et al.  Reachable workspace in facioscapulohumeral muscular dystrophy (FSHD) by kinect , 2015, Muscle & nerve.

[28]  Zhengyou Zhang,et al.  Microsoft Kinect Sensor and Its Effect , 2012, IEEE Multim..

[29]  Yao-Jen Chang,et al.  A Kinect-based system for physical rehabilitation: a pilot study for young adults with motor disabilities. , 2011, Research in developmental disabilities.

[30]  C. Bombardier,et al.  Measuring the whole or the parts? Validity, reliability, and responsiveness of the Disabilities of the Arm, Shoulder and Hand outcome measure in different regions of the upper extremity. , 2001, Journal of hand therapy : official journal of the American Society of Hand Therapists.

[31]  Bryan Buchholz,et al.  ISB recommendation on definitions of joint coordinate systems of various joints for the reporting of human joint motion--Part II: shoulder, elbow, wrist and hand. , 2005, Journal of biomechanics.

[32]  Stepán Obdrzálek,et al.  Upper Extremity Reachable Workspace Evaluation with Kinect , 2013, MMVR.

[33]  Sander Oude Elberink,et al.  Accuracy and Resolution of Kinect Depth Data for Indoor Mapping Applications , 2012, Sensors.

[34]  R. Bajcsy,et al.  P.2.4 Upper extremity reachable workspace evaluation in DMD using Kinect , 2013, Neuromuscular Disorders.

[35]  Shu Li,et al.  The measurement of functional arm reach envelopes for young Chinese males , 1990 .

[36]  Gabriele Siciliano,et al.  A standardized clinical evaluation of patients affected by facioscapulohumeral muscular dystrophy: The FSHD clinical score , 2010, Muscle & nerve.

[37]  Richard W. Bohannon,et al.  Clinical measurement of range of motion. Review of goniometry emphasizing reliability and validity. , 1987, Physical therapy.

[38]  Albert A. Rizzo,et al.  Towards pervasive physical rehabilitation using Microsoft Kinect , 2012, 2012 6th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) and Workshops.

[39]  V. Mathiowetz,et al.  Adult Norms for the Nine Hole Peg Test of Finger Dexterity , 1985 .