Hybrid Voice Controller for Intelligent Wheelchair and Rehabilitation Robot Using Voice Recognition and Embedded Technologies
Mohammed Faeik Ruzaij*,**, Sebastian Neubert*, Norbert Stoll***, and Kerstin Thurow*
*Center for Life Science Automation (celisca), University of Rostock
Rostock 18119, Germany
**Technical Institute of Babylon, Al-Furat Al-Awsat Technical University (ATU)
***Institute of Automation (IAT), University of Rostock
Rostock 18119, Germany
The use of intelligent wheelchair and rehabilitation robots has increased rapidly in the recent years owing to a growing number of patients experiencing paralysis, quadriplegia, amputation, and geriatric conditions. In this paper, the design and development of a powerful voice control system is proposed. It includes three modes of operational voice-recognition algorithms. Two sophisticated voice-recognition modules are used to achieve this goal. The system supports speaker dependent (SD) and speaker independent (SI) voice processing. Two voice-recognition algorithms are used, dynamic time warping (DTW) and Hidden Markov Model (HMM), to ensure the maximum voice-recognition accuracy and reduce voice-recognition errors. The system is validated in different noise environments to verify the performance of the system with low and high noise and to evaluate the feasibility of using the system in these environments. Three popular languages (English, German, and Chinese) were used by the system to verify performance with different pronunciations.
-  X. Lv, M. Zhang, and H. Li, “Robot Control Based on Voice Command,” Proc. IEEE Int. Conf. on Automation and Logistics, Qingdao, pp. 2490-2494, September 2008.
-  M. T. Qadri and S. A. Ahmed, “Voice Controlled Wheelchair Using DSK TMS320C6711,” Proc. of Int. Conf. on Signal Acquisition and Processing 2009, Kuala Lumpur, pp. 217-221, 2009.
-  U. Qidwai and F. Ibrahim, “Arabic Speech-Controlled Wheelchair: a Fuzzy Scenario,” Proc. of 10th Int. Conf. on Information Science, Signal Processing and their Applications, Kuala Lumpur, pp. 153-156, 2010.
-  Ronald H. Rockland Reisman S., “Voice Activated Wheelchair Controller,” Proc. IEEE 24th Annual Northeast Bioengineering Conf., Hershey, PA, pp. 128-129, 1998.
-  M. F. Ruzaij and S. Poonguzhali, “Design and Implementation of Low Cost Intelligent Wheelchair,” Proc. 2nd Int. Conf. on Recent Trends in Information Technology, Chennai, pp. 468-471, 19-21 April, 2012.
-  C. Aruna, A. Dhivya Parameswari, M. Malini, and G. Gopu, “Voice Recognition and Touch Screen Control Based Wheelchair for Paraplegic Persons,” Proc. Green Computing, Communication and Electrical Engineering, Coimbatore, pp. 1-5, 2014.
-  A. Murai, M. Mizuguchi, T. Saitoh, T. Osaki, and R. Konishi, “Elevator Available Voice Activated Wheelchair,” Proc. 18th IEEE Int. Symp. on Robot and Human Interactive Communication, Toyama, Japan, pp. 730-735, Sept. 27-Oct. 2, 2009.
-  M. Nishimori, T. Saitoh, and R. Konishi, “Voice Controlled Intelligent Wheelchair,” Proc. SICE Annual Conf. 2007, Kagawa University, Japan, pp. 336-340, Sept. 17-20, 2007.
-  K. Tanaka, K. Matsunaga, and H. O. Wang, “Electroencephalogram-Based Control of an Electric Wheelchair,” IEEE Trans. on Robotics, Vol.21, No.4, August 2005.
-  I. Iturrate, J. Antelis, and J. Minguez, “Synchronous EEG Brain-Actuated Wheelchair with Automated Navigation,” Proc. 2009 IEEE Int. Conf. on Robotics and Automation, Int. Conf. Center, Kobe, Japan, May Vol.12-17, pp. 2318-2327, 2009.
-  I. Moon, M. Lee, J. Ryu, and M. Mun, “Intelligent Robotic Wheelchair with EMG-, Gesture-, and Voice-based Interfaces,” Proc. IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, Las Vegas, Nevada, Vol.4, pp. 3453-3458, 2003.
-  S. Ohishi and T. Kondo, “A Proposal of EMG-based Wheelchair for Preventing Disuse of Lower Motor Function,” Proc. Annual Conf. of Society of Instrument and Control Engineers (SICE), Akita University, Akita, Japan, pp. 236-239, August 20-23, 2012.
-  B. Champaty, J. Jose, H. Pal, and A. Thirugnanam, “Development of EOG Based Human Machine Interface control System for Motorized Wheelchair,” Proc. Int. Conf. on Magnetics, Machines & Drives (AICERA-2014 iCMMD), Kottayam, Vol.24-26, pp. 1-7, July 2014.
-  O. Partaatmadja, B. Benhabib, A. Sun, and A. A. Goldenberg, “An Electrooptical Orientation Sensor for Robotics,” IEEE Trans. On Robotics And Automation, Vol.8, No.1, pp. 111-119, February 1992.
-  Z. Aiyun, Y. Kui, Y. Zhigang, and Z. Haibing, “Research and Application of a Robot Orientation Sensor,” Proc. Int. Conf. on Robotics Intelligent Systems and Signal Processing, Changsha, China, pp. 1069-1074, October 2003.
-  S. Manogna, S. Vaishnavi, and B. Geethanjali, “Head Movement Based Assist System For Physically Challenged,” Proc. 4th Int. Conf. on Bioinformatics and Biomedical Engineering (iCBBE), Chengdu, China, pp. 1-4, 2010.
-  EFM32GG990 DATASHEET, [Online]. Available: http://www.silabs.com. [Accessed December 20, 2014]
-  Speak Up Click User Manual Ver.101, MikroElektronika, Belgrade, Serbia, 2014.
-  EasyVR 2.0 User Manual R.3.6.6., TIGAL KG, Vienna, Austria, 2014.
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