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http://dx.doi.org/10.5369/JSST.2015.24.1.69

Smart Remote Rehabilitation System Based on the Measurement of Heart Rate from ECG Sensor and Kinect Motion-Recognition  

Kim, Jong-Jin (Department of Electronic Engineering, Pukyong National University)
Gwon, Seong-Ju (Department of Electronic Engineering, Pukyong National University)
Lee, Young-Sook (Team for Next Generation U-Healthcare Technology Development, Pukyong National University)
Chung, Wan-Young (Department of Electronic Engineering, Pukyong National University)
Publication Information
Journal of Sensor Science and Technology / v.24, no.1, 2015 , pp. 69-77 More about this Journal
Abstract
The Microsoft Kinect is a motion sensing input device which is widely used for many motion recognition applications such as fitness, sports, and rehabilitation. Until now, most of remote rehabilitation systems with the Microsoft Kinect have allowed the user or patient to do rehabilitation or fitness by following the motion of a video screen. However in this paper we propose a smart remote rehabilitation system with the Microsoft Kinect motion sensor and a wearable ECG sensor which can allow patients to offer monitoring of the individual's performance and personalized feedback on rehabilitation exercises. The proposed noble smart remote rehabilitation is able to monitor and measure the state of the patient's condition during rehabilitation exercise, and transmits it to the prescriber. This system can give feedback to a prescriber, a doctor and a patient for improving and recovering motor performance. Thus, the efficient rehabilitation training service can be provided to patient in response to changes of patient's condition during exercise.
Keywords
Rehabilitation exercise; ECG sensors; Kinect; Home healthcare;
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Times Cited By KSCI : 2  (Citation Analysis)
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1 S. T. Smith and D. Schoene, "The use of exercise-based videogames for training and rehabilitation of physical function in older adults: current practice and guidelines for future research", Aging Health, Vol. 8, No. 3, pp. 243-252, 2012.   DOI
2 J. Van Paasschen, L. Clare, K. S. L. Yuen, R. T. Woods, S. J. Evans, C. H. Parkinson, M. D. Rugg, and D. E. J. Linden," Cognitive rehabilitation changes memory-related brain activity in people with Alzheimer disease", Neurorehabil Neural Repair, Vol. 27, pp. 448-459, 2013.   DOI
3 L. H. Larsen, L. Schou, H. H. Lund, and H. Langberg, "The physical effect of exergames in healthy elderly-A systematic review", Games Health J., Vol. 2 , No. 4, pp. 205-212, 2013.   DOI
4 N. I. Han, "The effects of self-controlled feedback on the performance and learning of fencing fente", The Korean Journal of Physical Education, Vol. 42, No. 5, pp. 191-199, 2003.   과학기술학회마을
5 S. H. Han and K. Y. Kam, "Effects of augmented feedback training on the upper-limb functions and ADLs of chronic stroke patients", J. Korena Association Occupational Therapy Policy for Aged Industry, Vol. 4, No. 1, pp. 41-53, 2011.
6 J. Zhu, L Wang, R Yang, J. E. Davis, and Z. Pan," Reliability fusion of time-of-flight depth and stereo geometry for high quality depth maps", IEEE Trans Pattern Anal Mach Intell., Vol. 33, No. 7, pp. 1400-1414, 2011.   DOI
7 http://msdn.microsoft.com/en-us(retrieved on Dec. 10, 2014)
8 S. C. Lee and W. Y. Chung, "A research for removing ECG noise and transmitting 1-channel of 3-axis accelerometer signal within WSN based wearable sensor node", J. Sensor Sci. & Tech., Vol. 20, No. 2, pp. 25-29, 2011.   DOI
9 J. Pan and W. Tompkins, "A real-time QRS detection algorithm", IEEE Trans Biomed Eng, Vol. 132, pp. 230-236, 1985.
10 S. J. Jung, H. S. Shin, and W. Y. Chung, "Highly sensitive driver health condition monitoring system using nonintrusive active electrodes", Sens. Actuator B-Chem., Vol. 171-172, pp. 691-698, 2012.   DOI
11 S. H. Kim, "Finite element analysis of ultrasound propagation and nonlinear energy operator-based time-of-flight detection in bone", M.S. thesis, Dept. Biomed. Eng., Kyung Hee Univ., Seoul, 2010.
12 Y. M. Song H J. Ku, M. C. Le, and S. B. Lee, "Methods of estimation of physical activity and energy expenditure", Journal of Coaching Development, Vol. 7, No. 3, pp. 159-168, 2005.
13 L. R. Keytel, J. H. Goedecke, T. D. Noakes, H. Hiiloskorpi, R. Laukkanen, L. Van Der Merwe, and E. V. Lambert, "Prediction of energy expenditure from heart rate monitoring during submaximal exercise", J Sports Sci., Vol. 23, No. 3, pp. 11-20, 2005.