J. C. Perry, J. Andureu, F. I. Cavallaro, J. Veneman, S. Carmien et al., Effective Game use in Neurorehabilitation, Handbook of Research on Improving Learning and Motivation through Educational Games, 2010.
DOI : 10.4018/978-1-60960-495-0.ch032

Y. Chang, S. Chen, and J. Huang, A Kinect-based system for physical rehabilitation: A pilot study for young adults with motor disabilities, Research in Developmental Disabilities, vol.32, issue.6, pp.2566-2570, 2011.
DOI : 10.1016/j.ridd.2011.07.002

H. Tannous, D. Istrate, M. C. Ho-ba-tho, and T. T. Dao, Serious game and functional rehabilitation for the lower limbs, European Research in Telemedicine / La Recherche Europ??enne en T??l??m??decine, vol.5, issue.2, pp.65-69, 2016.
DOI : 10.1016/j.eurtel.2016.05.001

J. M. Ibarra-zannatha, A. J. Tamayo, Á. D. Sánchez, J. E. Delgado, L. E. Cheu et al., Development of a system based on 3D vision, interactive virtual environments, ergonometric signals and a humanoid for stroke rehabilitation, Computer Methods and Programs in Biomedicine, vol.112, issue.2, pp.239-249, 2013.
DOI : 10.1016/j.cmpb.2013.04.021

A. Chatzitofis, D. Monaghan, E. Mitchell, F. Honohan, D. Zarpalas et al., HeartHealth: A Cardiovascular Disease Home-based Rehabilitation System, Procedia Computer Science, vol.63, pp.340-347, 2015.
DOI : 10.1016/j.procs.2015.08.352

J. Lozano-quilis, H. Gil-gómez, J. Gil-gómez, S. Albiol-pérez, G. Palacios-navarro et al., Virtual Rehabilitation for Multiple Sclerosis Using a Kinect-Based System: Randomized Controlled Trial, JMIR Serious Games 2014, p.69471, 2013.
DOI : 10.2196/games.2933

I. T. Paraskevopoulos, E. Tsekleves, C. Craig, C. Whyatt, and J. Cosmas, Design guidelines for developing customised serious games for Parkinson???s Disease rehabilitation using bespoke game sensors, Entertainment Computing, vol.5, issue.4, pp.413-424, 2014.
DOI : 10.1016/j.entcom.2014.10.006

S. Cho, J. Ku, Y. K. Cho, I. Y. Kim, Y. J. Kang et al., Development of virtual reality proprioceptive rehabilitation system for stroke patients, Computer Methods and Programs in Biomedicine, vol.113, issue.1, pp.258-265, 2014.
DOI : 10.1016/j.cmpb.2013.09.006

P. Chen, S. Wei, W. Hsieh, J. Cheen, L. Chen et al., Lower limb power rehabilitation (LLPR) using interactive video game for improvement of balance function in older people, Archives of Gerontology and Geriatrics, vol.55, issue.3, pp.677-682, 2012.
DOI : 10.1016/j.archger.2012.05.012

Q. Ding, I. H. Stevenson, N. Wang, W. Li, Y. Sun et al., Motion games improve balance control in stroke survivors: A preliminary study based on the principle of constraint-induced movement therapy, Displays, vol.34, issue.2, pp.125-131, 2013.
DOI : 10.1016/j.displa.2012.08.004

. Jintrinix, Available online: www.jintronix.com, 2016.

. Respondwell, Available online: www.respondwell.com, 2016.

R. Williamson and B. J. Andrews, Detecting absolute human knee angle and angular velocity using accelerometers and rate gyroscopes, Medical & Biological Engineering & Computing, vol.38, issue.8, pp.294-302, 2001.
DOI : 10.1007/BF02345283

R. E. Mayagoitia, A. V. Nene, and P. H. Veltink, Accelerometer and rate gyroscope measurement of kinematics: an inexpensive alternative to optical motion analysis systems, Journal of Biomechanics, vol.35, issue.4, pp.537-542, 2002.
DOI : 10.1016/S0021-9290(01)00231-7

J. Favre, B. M. Jolles, R. Aissaoui, and K. Aminian, Ambulatory measurement of 3D knee joint angle, Journal of Biomechanics, vol.41, issue.5, pp.1029-1035, 2008.
DOI : 10.1016/j.jbiomech.2007.12.003

T. Liu, Y. Inoue, and K. Shibata, Development of a wearable sensor system for quantitative gait analysis, Measurement, vol.42, issue.7, pp.978-988, 2009.
DOI : 10.1016/j.measurement.2009.02.002

R. Pérez, Ú. Costa, M. Torrent, J. Solana, E. Opisso et al., Upper Limb Portable Motion Analysis System Based on Inertial Technology for Neurorehabilitation Purposes, Sensors, vol.10, issue.12, pp.10733-10751, 2010.
DOI : 10.3390/s101210733

R. E. Kalman, A New Approach to Linear Filtering and Prediction Problems, Journal of Basic Engineering, vol.82, issue.1, pp.35-45, 1960.
DOI : 10.1115/1.3662552

J. L. Marins, X. Yun, E. R. Bachmann, R. B. Mcghee, and M. J. Zyda, An extended Kalman filter for quaternion-based orientation estimation using MARG sensors, Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180), pp.2003-2011, 2001.
DOI : 10.1109/IROS.2001.976367

F. Abyarjoo, A. Barreto, J. Cofino, and F. Ortega, Implementing a Sensor Fusion Algorithm for 3D Orientation Detection with Inertial/Magnetic Sensors, Innovations and Advances in Computing, pp.305-310, 2015.
DOI : 10.1007/978-3-319-06773-5_41

S. O. Madgwick, A. J. Harrison, and R. Vaidyanathan, Estimation of IMU and MARG orientation using a gradient descent algorithm, 2011 IEEE International Conference on Rehabilitation Robotics, pp.1-7, 2011.
DOI : 10.1109/ICORR.2011.5975346

. Shimmersensing, Available online: www.shimmersensing.com, 2016.

M. Miezal, B. Taetz, and G. Bleser, On Inertial Body Tracking in the Presence of Model Calibration Errors, Sensors, vol.16, issue.8, 1132.
DOI : 10.3390/s16071132

H. Dejnabadi, B. M. Jolles, and K. Aminian, A New Approach to Accurate Measurement of Uniaxial Joint Angles Based on a Combination of Accelerometers and Gyroscopes, IEEE Transactions on Biomedical Engineering, vol.52, issue.8, pp.1478-1484, 2005.
DOI : 10.1109/TBME.2005.851475

H. Dejnabadi, B. M. Jolles, E. Casanova, P. Fua, and K. Aminian, Estimation and Visualization of Sagittal Kinematics of Lower Limbs Orientation Using Body-Fixed Sensors, IEEE Transactions on Biomedical Engineering, vol.53, issue.7, pp.1385-1393, 2006.
DOI : 10.1109/TBME.2006.873678

J. Favre, R. Aissaoui, B. M. Jolles, J. A. De-guise, and K. Aminian, Functional calibration procedure for 3D knee joint angle description using inertial sensors, Journal of Biomechanics, vol.42, issue.14, pp.2330-2335, 2009.
DOI : 10.1016/j.jbiomech.2009.06.025

B. Bouvier, S. Duprey, L. Claudon, R. Dumas, and A. Savescu, Upper Limb Kinematics Using Inertial and Magnetic Sensors: Comparison of Sensor-to-Segment Calibrations, Sensors, vol.15, issue.8, pp.18813-18833, 2015.
DOI : 10.3390/s150818813

URL : https://hal.archives-ouvertes.fr/hal-01281093

L. Zhang, J. Sturm, D. Cremers, and D. Lee, Real-time human motion tracking using multiple depth cameras, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp.7-12, 2012.
DOI : 10.1109/IROS.2012.6385968

S. Feng and R. Murray-smith, Fusing Kinect Sensor and Inertial Sensors with Multi-Rate Kalman Filter, Proceedings of the IET Conference on Data Fusion & Target Tracking 2014: Algorithms and Applications, pp.1-8, 2014.

F. Destelle, A. Ahmadi, N. E. O-'connor, K. Moran, A. Chatzitofis et al., Daras, P. Low-Cost Accurate Skeleton Tracking Based on Fusion of Kinect and Wearable Inertial Sensors, Proceedings of the 22nd European Signal Processing Conference (EUSIPCO), pp.1-5, 2014.

A. Atrsaei, H. Salarieh, and A. Alasty, Human Arm Motion Tracking by Orientation-Based Fusion of Inertial Sensors and Kinect Using Unscented Kalman Filter, Journal of Biomechanical Engineering, vol.138, issue.9, p.91005, 2016.
DOI : 10.1115/1.4034170

C. Kalkbrenner, S. Hacker, M. Algorri, and R. Blechschmidt-trapp, Motion Capturing with Inertial Measurement Units and Kinect?Tracking of Limb Movement using Optical and Orientation Information, Proceedings of the International Conference on Biomedical Electronics and Devices, pp.3-6, 2014.

Y. Tian, X. Meng, D. Tao, D. Liu, and C. Feng, Upper limb motion tracking with the integration of IMU and Kinect, Neurocomputing, vol.159, pp.207-218, 2015.
DOI : 10.1016/j.neucom.2015.01.071

G. Glonek and A. Wojciechowski, Hybrid Method of Human Limb Joints Positioning???Hand Movement Case Study, In Information Technologies in Medicine, vol.159, pp.307-320, 2016.
DOI : 10.1007/978-3-319-39904-1_28

H. Tannous, D. Istrate, M. C. Ho-ba-tho, and T. Dao, Feasibility study of a serious game based on Kinect system for functional rehabilitation of the lower limbs, European Research in Telemedicine / La Recherche Europ??enne en T??l??m??decine, vol.5, issue.3, pp.97-104, 2016.
DOI : 10.1016/j.eurtel.2016.05.004

S. Chen, J. Brantley, T. Kim, S. Ridenour, and J. Lach, Characterising and minimising sources of error in inertial body sensor networks, International Journal of Autonomous and Adaptive Communications Systems, vol.6, issue.3, pp.253-71, 2013.
DOI : 10.1504/IJAACS.2013.054828

J. Wåhslén, I. Orhan, and T. Lindh, Local Time Synchronization in Bluetooth Piconets for Data Fusion Using Mobile Phones, pp.133-138, 2011.

R. B. Davis, S. Ounpuu, D. Tyburski, and J. R. Gage, A gait analysis data collection and reduction technique, Human Movement Science, vol.10, issue.5, pp.575-587, 1991.
DOI : 10.1016/0167-9457(91)90046-Z

I. Cleland, B. Kikhia, C. Nugent, A. Boytsov, J. Hallberg et al., Optimal Placement of Accelerometers for the Detection of Everyday Activities, Sensors, vol.13, issue.7, pp.9183-9200, 2013.
DOI : 10.3390/s130709183

L. Wang, Z. Zhang, and P. Sun, Quaternion-Based Kalman Filter for AHRS Using an Adaptive-Step Gradient Descent Algorithm, International Journal of Advanced Robotic Systems, vol.11, issue.2, p.131, 2015.
DOI : 10.5772/61313

R. L. Gajdosik and R. W. Bohannon, Clinical Measurement of Range of Motion, Physical Therapy, vol.67, issue.12, pp.1867-1872, 1987.
DOI : 10.1093/ptj/67.12.1867

L. Brosseau, M. Tousignant, J. Budd, N. Chartier, L. Duciaume et al., Intratester and intertester reliability and criterion validity of the parallelogram and universal goniometers for active knee flexion in healthy subjects, Physiotherapy Research International, vol.71, issue.3, pp.150-166, 1997.
DOI : 10.1002/pri.97

T. T. Dao, H. Tannous, P. Pouletaut, D. Gamet, D. Istrate et al., Interactive and Connected Rehabilitation Systems for E-Health, IRBM, vol.37, issue.5-6
DOI : 10.1016/j.irbm.2016.02.003

E. Olson, A passive solution to the sensor synchronization problem, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp.18-22, 2010.
DOI : 10.1109/IROS.2010.5650579

M. Rooze and S. Van-sint-jan, Validity and reliability of the Kinect within functional assessment activities: Comparison with standard stereophotogrammetry, Gait Posture, vol.39, pp.593-598, 2014.

A. Pfister, A. M. West, S. Bronner, and J. A. Noah, Comparative abilities of Microsoft Kinect and Vicon 3D motion capture for gait analysis, Journal of Medical Engineering & Technology, vol.86, issue.5, pp.274-280, 2014.
DOI : 10.3109/03091902.2014.909540

P. Plantard, E. Auvinet, A. Pierres, and F. Multon, Pose Estimation with a Kinect for Ergonomic Studies: Evaluation of the Accuracy Using a Virtual Mannequin, Sensors, vol.15, issue.1, pp.1785-1803, 2015.
DOI : 10.3390/s150101785

URL : https://hal.archives-ouvertes.fr/hal-01104045