Recent Survey of Automated Rehabilitation Systems Using EMG Biosensors

[Purpose] In this paper, we present a survey of some recently developed techniques in the field of automatic rehabilitation systems assisted by electromyography (EMG) biosensors and their application in physically disabled patients. We also include a discussion about the implementation of several hardware and software models for rehabilitation to make the full process dynamics. [Methods] A systematic search for articles published from 2000 to March 2011 was conducted in the IEEE, Springer Link, Pub Med and ACM digital library databases. The search plan was developed using different terms referring to rehabilitation, EMG sensors and automatic systems as well as we used number of keywords related to the subject of our survey along with their synonyms. The entire survey was performed in the automatic rehabilitation lab (Biomedical Engineering) of the Universiti Malaysia Perils (UniMAP) from December 2010 to March 2011. [Result] A total of 22 articles were analyzed in our study. Of these, 17 articles were about EMG-aided recovery systems developed for the impaired human body. Finally, we confirmed that all of the EMG-supported rehabilitation systems are noninvasive, assisted by a computer or robot and most of them are real-time processes. [Conclusion] Obviously, it is difficult to complete a survey within a single article of all possible?EMG- generated rehabilitation systems. However, we expect that the references cited will cover the main theoretical and practical issues, guiding the researcher in interesting research and suggesting promising EMG-aided rehabilitation techniques that have yet to be explored.

[1]  F. Mohd-Yasin,et al.  Techniques of EMG signal analysis: detection, processing, classification and applications , 2006, Biological Procedures Online.

[2]  Toshio Fukuda,et al.  An exoskeleton system for elbow joint motion rehabilitation , 2003, Proceedings 2003 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM 2003).

[3]  Michael Hillman,et al.  Rehabilitation robotics from past to present - a historical perspective , 2003 .

[4]  Keiko Homma,et al.  A wire-driven leg rehabilitation system: development of a 4-DOF experimental system , 2003, Proceedings 2003 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM 2003).

[5]  O. Majdalawieh,et al.  Biomedical signal processing and rehabilitation engineering: a review , 2003, 2003 IEEE Pacific Rim Conference on Communications Computers and Signal Processing (PACRIM 2003) (Cat. No.03CH37490).

[6]  Youngho Kim,et al.  The Development of an EMG-based Upper Extremity Rehabilitation Training System for Hemiplegic Patients , 2009 .

[7]  Chih-Fu Wu,et al.  PC-Based Rehabilitation System with Biofeedback , 2009, HCI.

[8]  John Heng,et al.  A step towards home-based robotic rehabilitation: An interface circuit for EEG/SEMG actuated orthosis , 2009, 2009 IEEE/ASME International Conference on Advanced Intelligent Mechatronics.

[9]  G. Gini,et al.  An EMG-controlled exoskeleton for hand rehabilitation , 2005, 9th International Conference on Rehabilitation Robotics, 2005. ICORR 2005..

[10]  Zhang Xia,et al.  EMG-driven computer game for post-stroke rehabilitation , 2010, 2010 IEEE Conference on Robotics, Automation and Mechatronics.

[11]  Jens Haueisen,et al.  Virtual Reality and Robotics for Neuro-Motor Rehabilitation of Ischemic Stroke Patients , 2009 .

[12]  Jaehoon Jeong,et al.  Recognition of Lower Limb Muscle EMG Patterns by using Neural Networks during the Postural Balance Control , 2007 .

[13]  Zeung nam Bien,et al.  New EMG pattern Recognition based on Soft Computing Techniques and Its Application to Control of a Rehabilitation Robotic Arm , 2000 .

[14]  Marvin J. Dainoff,et al.  Ergonomics and Health Aspects of Work with Computers , 2007, Lecture Notes in Computer Science.

[15]  Lining Sun,et al.  A Novel Rehabilitation System for Upper Limbs , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[16]  Y. Takahashi,et al.  Basic experiments of upper limb rehabilitation using haptic device system , 2005, 9th International Conference on Rehabilitation Robotics, 2005. ICORR 2005..

[17]  Takashi Komeda,et al.  Wire-driven mechanism for finger rehabilitation device , 2010, 2010 IEEE International Conference on Mechatronics and Automation.

[18]  E. Gonzalez-Parada,et al.  A PDA-based portable wireless ECG monitor for medical personal area networks , 2006, MELECON 2006 - 2006 IEEE Mediterranean Electrotechnical Conference.

[19]  Sanjib Kumar Panda,et al.  A real time control algorithm for a myoelectric glove for the rehabilitation of wrist and elbow of stroke patients , 2010, IEEE ICCA 2010.

[20]  Rong Song,et al.  A Comparison Between Electromyography-Driven Robot and Passive Motion Device on Wrist Rehabilitation for Chronic Stroke , 2009, Neurorehabilitation and neural repair.

[21]  Munna Khan,et al.  Wireless Transmission of EMG Signal and Analysis of Its Correlation with Simultaneously Acquired Carotid Pulse Wave Using Dual Channel System , 2010, 2010 Second International Conference on eHealth, Telemedicine, and Social Medicine.

[22]  Sanjib Kumar Panda,et al.  Design of a myoelectric glove for upper limb stroke rehabilitation , 2009, i-CREATe.

[23]  D.S. Andreasen,et al.  Exoskeleton with EMG based active assistance for rehabilitation , 2005, 9th International Conference on Rehabilitation Robotics, 2005. ICORR 2005..