References
- B. Pavya, M.-C. Ilioub, B. Verges-Patoisc, R. Briond, C. Monperee, F. Carref, P. Aeberhardg, C. Argouachh, A. Borgnei, S. Consolij, S. Coronek, M. Fischbachl, L. Fourcadem, J.-M. Lecerfn, C. Mounier-Vehiero, F. Paillardf, B. Pierrep, B. Swynghedauwq, Y. Theodoser, D. Thomass, F. Claudott, A. Cohen-Solalq, H. Douardu, D. Marcadetv and Exercise, Rehabilitation Sport Group (GERS), "French Society of Cardiology guidelines for cardiac rehabilitation in adults", Archives of Cardiovascular Diseases, Vol. 105, No. 5, pp. 309-328, 2012. https://doi.org/10.1016/j.acvd.2012.01.010
- http://terms.naver.com/entry.nhn?docId=927726&cid=51007&categoryId=51007 (retrieved on Feb. 11, 2016).
- J. Park, J. Cho, T. Nam and J. Choi, "A unconstrained multi-channel heart rate monitoring system for exercising rehabilitation patients", 29th Annual International Conf. of the IEEE, Engineering in Medicine and Biology Society, pp. 3512-3515, Lyon, France, 2007.
- C. Wang, L. Wang, J. Qin, Z. Wu, L. Duan, Z. Li, X. Ou, Weiguangli, Z. Lu, M. Li, Y. Wang, J. Long, M. Huang and Q. Wang, "Development of a novel finger and wrist rehabilitation robot for finger and wrist training", TENCON 2015 - 2015 IEEE Region 10 Conf., pp. 1-5, Macao, China, 2015.
- A. Koenig, A. Caruso, M. Bolliger, L. Somaini, X. Omlin, M. Morari and R. Riener, "Model-based heart rate control during robot-assisted gait training", 2011 IEEE International Conf. on Robotics and Automation, pp. 4151-4156, Shanghai, China, 2011.
- R. B. Ambar, H. B. M. Poad, A. M. B. M. Ali, M. S. B. Ahmad and M. M. B. A. Jamil, "Multi-sensor arm rehabilitation monitoring device", 2012 International Conf. on Biomedical Engineering (ICoBE), pp. 424-429, Penang, Malaysia, 2012.
- C.-K. Tey, Y.-S. Lee and W.-Y. Chung, "Healthcare monitoring system combined with noncontact kinect-based rehabilitation for outpatients", KISPS Summer Conf. 2014, pp.27-28, Gyeongsan, Korea, 2014.
- C.-L. Lai, Y.-L. Huang, T.-K. Liao, C.-M. Tseng, Y.-F. Chen and D. Erdenetsogt, "A microsoft kinect-based virtual rehabilitation system to train balance ability for stroke patients", 2015 International Conference on Cyberworlds (CW), pp.54-60, Gotland, Sweden, 2015.
- C.-M. Tseng, C.-L. Lai, D. Erdenetsogt and Y.-F. Chen, "Microsoft kinect based virtual rehabilitation system", 2014 International Symposium on Computer, Consumer and Control (IS3C), pp.934-937, Taichung, Taiwan, 2014.
- R. Banerjee, A. Sinha, A. D. Choudhury and A. Visvanathan, "PhotoECG: Photoplethysmographyto estimate ECG parameters", 2014 IEEE International Conf. on Acoustic, Speech and Signal Processing (ICASSP), pp. 4404-4408, Florence, Italy, 2014.
- A. B. Hertzman, "The blood supply of various skin areas as estimated by the photoelectric plethysmography", AM. J. physiol., Vol. 124, pp. 329-340, 1938.
- T.-H. Lu, H.-C. Lin, Y.-H. Lee, R.-R. Chen, H.-L. Chen, S.-Y. Chang, J.-D. Chen, B.-R. Wu and T.-H. Wu "A Motion-Sensing Enabled Personalized Exercise System for Cardiac Rehabilitation", 2012 IEEE 14th International Conf. on e-Health Networking, Applications and Services (Healthcom), pp. 167-171, Beijing, China, 2012.
- J. Park, J. Cho, J. Choi and T. Nam, "A zigbee network-based multi-channel heart rate monitoring system for exercising rehabilitation patients", TENCON 2007 - 2007 IEEE Region 10 Conf., pp. 1-4, Taipei, Taiwan, 2007.
- W. Verkruysse, L. O Svaasand, and J S. Nelson, "Remote plethysmographic imaging using ambient light", Opt. Express, Vol. 16, pp. 21434-21445, 2008. https://doi.org/10.1364/OE.16.021434
- W. J. Jiang, S. C. Gao, P. Wittek and L. Zhao, "Real-time Quantifying Heart Beat Rate from Facial Video Recording on a Smart Phone using Kalman Filters", 2014 IEEE 16th International Conf. on e-Health Networking, Applications and Services (Healthcom), pp. 393-396, Natal, Brazil, 2014.
- R. E. Kalman, "A new approach to linear filtering and prediction problems", J. of Basic Engineering, Vol. 82, No. 1, pp. 35-45, 1960. https://doi.org/10.1115/1.3662552
- https://msdn.microsoft.com/en-us/library/hh973077(retrieved on Jan. 10, 2016).