參考文獻 |
[1] V. L. Feigin, M. H. Forouzanfar, R. Krishnamurthi, G. A. Mensah, M. Connor and D. A. Bennett, “Global and regional burden of stroke during 1990-2010: findings from the global burden of disease study 2010,” The Lancet, Vol. 383, Issue 9913, pp. 245-255, 2014.
[2] N. F. Gordon, M. Gulanick, F. Costa, G. Fletcher, B. A. Franklin and E. J. Roth, “Physical activity and exercise recommendations for stroke survivors,” Circulation, Vol. 109, pp. 2031-2041, 2004.
[3] T. Giorgino, P. Tormene, G. Maggioni, D. Capozzi, S. Quaglini and C. Pistarini, “Assessment of sensorized garments as flexible support to self-administered post-stroke physical rehabilitation,” European Journal of Physical and Rehabilitation Medicine, Vol. 45, No. 1, pp. 75-84, 2009.
[4] J. Langan, K. DeLave, L. Phillips, P. Pangilinan and S. H. Brown, “Home-based telerehabilitation shows improved upper limb function in adults with chronic stroke: a pilot study,” Journal of Rehabilitation Medicine, Vol. 45, No. 2, pp. 217-220, 2013.
[5] S. Brunnstrom, “Motor testing procedures in hemiplegia: based on sequential recovery stages,” Physical Therapy, Vol. 46, No. 4, pp. 357-375, 1966.
[6] U. B. Flansbjer, A. M. Holmback, D. Downham, C. Patten and J. Lexell, “Reliability of gait performance tests in men and women with hemiparesis after stroke,” Journal of Rehabilitation Medicine, Vol. 37, No. 2, pp. 75-82, 2005.
[7] M. D. Bland, A. Sturmoski, M. Whitson, L. T. Connor, R. Fucetola and T. Huskey, “Prediction of discharge walking ability from initial assessment in a stroke inpatient rehabilitation facility population,” Archives of Physical Medicine and Rehabilitation, Vol. 93, No. 8, pp. 1441-1447, 2012.
[8] H. Zhou and H. Hu, “Human motion tracking for rehabilitation-a survey,” Biomedical Signal Processing and Control, Vol. 3, Issue 1, pp. 1-18, 2008.
[9] S. Allin, N. Baker, E. Eckel and D. Ramanan, “Robust tracking of the upper limb for functional stroke assessment,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol. 18, No. 5, pp. 542-550, 2010.
[10] R. Schmidt, C. Disselhorst-Klug, J. Silny and G. Rau, “A marker-based measurement procedure for unconstrained wrist and elbow motions,” Journal of Biomechanics, Vol. 32, No. 6, pp. 615-621, 1999.
[11] P. S. Lum, C. G. Burgar, D. E. Kenney and H. F. M. Van der Loos, “Quantification of force abnormalities during passive and active-assisted upper-limb reaching movements in post-stroke hemiparesis,” IEEE Transactions on Biomedical Engineering, Vol. 46, No. 6, pp. 652-662, 1999.
[12] N. Jarrasse, M. Tagliabue, J. V. G. Robertson, A. Maiza, V. Crocher, A. Roby-Brami and G. Morel, “A methodology to quantify alterations in human upper limb movement during co-manipulation with an exoskeleton,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol. 18, No. 4, pp. 389-397, 2010.
[13] H. Zheng, N. D. Black and N. D. Harris, “Position-sensing technologies for movement analysis in stroke rehabilitation,” Medical & Biological Engineering & Computing, Vol. 43, No. 4, pp. 413-420, 2005.
[14] M. Sekine, Y. Abe, M. Sekimoto, Y. Higashi, T. Fujimoto, T. Tamura and Y. Fukui, “Assessment of gait parameter in hemiplegic patients by accelerometry,” Proceedings of The 22nd Annual Engineering in Medicine and Biology Society International Conference, Vol. 3, pp. 1879-1882, 2000.
[15] T. Liu, Y. Inoue and K. Shibata, “Development of a wearable sensor system for quantitative gait analysis,” Measurement, Vol. 42, Issue 7, pp. 978-988, 2009.
[16] D. Staudenmann, K. Roeleveld, D. F. Stegeman and J. H. van Dieen, “Methodological aspects of SEMG recordings for force estimation--a tutorial and review,” Journal of Electromyography and Kinesiology, Vol. 20, No. 3, pp. 375-387, 2010.
[17] F. Moosavi, A. Pasdar, H. Ehsani and M. Rostami, “An EMG-driven musculoskeletal model to predict muscle forces during performing a weight training exercise with a dumbbell,” Proceedings of The 19th Iranian Conference on Biomedical Engineering, pp. 79-84, 2012.
[18] C. Fleischer and G. Hommel, “A human--exoskeleton interface utilizing electromyography,” IEEE Transactions on Robotics, Vol. 24, No. 4, pp. 872-882, 2008.
[19] O. Tunçel, K. Altun and B. Barshan, “Classifying human leg motions with uniaxial piezoelectric gyroscopes,” Sensors, Vol. 9, No. 11, pp. 8508-8546, 2009.
[20] H. Y. Lau, K. Y. Tong and H. Zhu, “Support vector machine for classification of walking conditions of persons after stroke with dropped foot,” Human Movement Science, Vol. 28, No. 4, pp. 504-514, 2009.
[21] Q. L. Li, Y. Song and Z. G. Hou, “Estimation of lower limb periodic motions from sEMG using least squares support vector regression,” Neural Processing Letters, Vol. 41, Issue 3, pp. 371-388, 2015.
[22] C. J. De Luca, “Surface electromyography: detection and recording,” Available: http://www.delsys.com/Attachments_pdf/WP_SEMGintro.pdf
[23] E. A. Clancy, E. L. Morin and R. Merletti, “Sampling, noise-reduction and amplitude estimation issues in surface electromyography,” Journal of Electromyography and Kinesiology, Vol. 12, No. 1, pp. 1-16, 2002.
[24] A. R. Webb and K. D. Copsey, Statistical Pattern Recognition, 3rd ed., John Wiley & Sons, 2011.
[25] S. Haykin, Neural Networks: A Comprehensive Foundation, 2nd ed., Macmillan, 1994.
[26] V. Vapnik, The Nature of Statistical Learning Theory, 2nd ed., Springer, 2000.
[27] N. Cristianini and J. Shawe-Taylor, An Introduction to Support Vector Machines and Other Kernel-based Learning Methods, Cambridge University Press, 2000.
[28] C.-C. Chang and C.-J. Lin, “LIBSVM: a library for support vector machines,” ACM Transactions on Intelligent Systems and Technology, Vol. 2, No. 3, pp. 1-27, 2011.
[29] J. Yousefi and A. Hamilton-Wright, “Characterizing EMG data using machine-learning tools,” Computers in Biology and Medicine, Vol. 51, pp. 1-13, 2014.
[30] S. D. Jush, C. H. Wang, C. L. Hsieh, M. H. Chen, and C. L. Chen, “The Brunnstrom Recovery Scale: Its Reliability and Concurrent Validity,” Journal of Occupational Therapy Association R.O.C., Vol. 14, No. 1, pp. 1-12, 1996. |