On the development of a wireless motion capture sensor node for upper limb rehabilitation
暂无分享,去创建一个
[1] Thomas B. Moeslund,et al. A Survey of Computer Vision-Based Human Motion Capture , 2001, Comput. Vis. Image Underst..
[2] Pedro Macedo,et al. A Telerehabilitation System based on Wireless Motion Capture Sensors , 2014, PhyCS.
[3] Wai Yin Wong,et al. Clinical Applications of Sensors for Human Posture and Movement Analysis: A Review , 2007, Prosthetics and orthotics international.
[4] Mark W. Spong,et al. Robot dynamics and control , 1989 .
[5] Peter Langhorne,et al. Effects of Augmented Exercise Therapy Time After Stroke: A Meta-Analysis , 2004, Stroke.
[6] Kay Soon Low,et al. Unrestrained Measurement of Arm Motion Based on a Wearable Wireless Sensor Network , 2010, IEEE Transactions on Instrumentation and Measurement.
[7] Peter Langendörfer,et al. Detecting Elementary Arm Movements by Tracking Upper Limb Joint Angles With MARG Sensors , 2016, IEEE Journal of Biomedical and Health Informatics.
[8] Huosheng Hu,et al. Human motion tracking for rehabilitation - A survey , 2008, Biomed. Signal Process. Control..
[9] Yacine Challal,et al. Rehabilitation supervision using wireless sensor networks , 2011, 2011 IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks.
[10] Francisco José Madrid-Cuevas,et al. Automatic generation and detection of highly reliable fiducial markers under occlusion , 2014, Pattern Recognit..
[11] Pedro Macedo,et al. A Personalized Rehabilitation System based on Wireless Motion Capture Sensors , 2015, SENSORNETS.
[12] I-Ming Chen,et al. A low cost wearable wireless sensing system for upper limb home rehabilitation , 2010, 2010 IEEE Conference on Robotics, Automation and Mechatronics.
[13] C. R. Ethier,et al. Introductory Biomechanics: From Cells to Organisms , 2007 .
[14] Vicky Chan,et al. Wearable sensing for rehabilitation after stroke: Bimanual jerk asymmetry encodes unique information about the variability of upper extremity recovery , 2017, 2017 International Conference on Rehabilitation Robotics (ICORR).
[15] Francisco Javier Díaz Pernas,et al. Real-time hands, face and facial features detection and tracking: Application to cognitive rehabilitation tests monitoring , 2010, J. Netw. Comput. Appl..
[16] Yuanyuan Wang,et al. Towards an IoT-based upper limb rehabilitation assessment system. , 2017, Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference.