V. L. Feigin, “Stroke epidemiology in the developing
world,” The Lancet, Vol. 365, No. 9478, pp. 2160-2161,
V. L. Feigin, C. M. Lawes, D. A. Bennett, and C. S.
Anderson, “Stroke epidemiology: a review of
population-based studies of incidence, prevalence, and
case-fatality in the late 20th century,” The Lancet
Neurology, Vol. 2, No.1, pp. 43-53, 2003.
G. D. Griffin, “Stroke, mTBI, Infection, Antibiotics
and Beta Blockade: Connecting the Dots,” Medical
Life Talk. [Online].
Z. S. Huang, T. L. Chiang, and T. K. Lee, “Stroke
Prevalence in Taiwan Findings From the 1994 National
Health Interview Survey,” Stroke, Vol. 28, No. 8, pp.
C. A. Kernich, “Living with Stroke A Guide for
amilies,” Neurology, Vol. 44, No. 10, pp. 1991-1991,
M. Kelly-Hayes, A. Beiser, C. S. Kase, A. Scaramucci,
R. B. Agostino, and P. A. Wolf, “The influence of
gender and age on disability following ischemic
stroke: the Framingham study,” Journal of Stroke and
Cerebrovascular Diseases, Vol. 12, No. 3, pp. 119-126,
B. M. Kissela, J. C. Khoury, K. Alwell, C. J. Moomaw,
D. Woo, O. Adeoye, and D. O. Kleindorfer, “Age at
stroke temporal trends in stroke incidence in a large,
biracial population,” Neurology, Vol. 79, No. 17, pp.
H. C. Lin, Y. J. Lin, T. C. Liu, C. S. Chen, and W. T.
Chiu, “Urbanization and stroke prevalence in Taiwan:
analysis of a nationwide survey,” Journal of Urban
Health, Vol. 84, No. 4, pp. 604-614, 2007.
S. E. Chiuve, K. M. Rexrode, D. Spiegelman, G.
Logroscino, J. E. Manson, and E. B. Rimm, “Primary
prevention of stroke by healthy lifestyle,”
Circulation, Vol. 118, No. 9, pp. 947-954, 2008.
M. Fisher, A. Dávalos, A. Rogalewski, A. Schneider,
and W. R. Schäbitz, “Toward a multimodal
europrotective treatment of stroke,” Stroke, Vol. 37,
No. 4, pp. 1129-1136, 2006.
K. J. Greenlund, W. H. Giles,Keenan, J. B. Croft, and
G. A. Mensah, “Physician advice, patient actions, and
health-related quality of life in secondary
prevention of stroke trough diet and exercise,”
Stroke, Vol. 33, No. 2, pp. 565-571, 2002.
S. Ahmed, N. E. Mayo, J. Higgins, N. M. Salbach, L.
Finch, and S. L. Wood-Dauphinée, “The Stroke
Rehabilitation Assessment of Movement (STREAM): a
comparison with other measures used to evaluate
effects of stroke and rehabilitation,” Physical
therapy, Vol. 83, No. 7, pp. 617-630, 2003.
S. L. Wolf, C. J. Winstein, J. P. Miller, E. Taub,
G.Uswatte, D. Morris, and Excite Investigators,
“Effect of constraint-induced movement therapy on
upper extremity function 3 to 9 months after stroke:
the EXCITE randomized clinical trial,” Jama, Vol.
296, No. 17, pp. 2095-2104, 2006.
S. M. Braun, A. J. Beurskens, P. J. Borm, T. Schack,
and D. T. Wade, “The effects of mental practice in
stroke rehabilitation: a systematic review,” Archives
of physical medicine and rehabilitation, Vol. 87, No.
6, pp. 842-852, 2006.
W. S. Lu, C. H. Wang, J. H. Lin, C. F. Sheu, and C.
L. Hsieh, “The minimal detectable change of the
simplified stroke rehabilitation assessment of
movement measure,” Journal of rehabilitation
medicine, Vol. 40, No. 8, pp. 615-619, 2008.
N. B. Lincoln, G. P .Mulley, A. C. Jones, E. McGuirk,
W. Lendrem, and J. R. A. Mitchell, “Effectiveness of
speech therapy for aphasic stroke patients: a
randomised controlled trial,” The Lancet, Vol. 323,
No. 8388, pp. 1197-1200, 1984.
S. Saini, D. R. A. Rambli, S. Sulaiman, M. N.
Zakaria, and S. R. M. Shukri, “A low-cost game
framework for a home-based stroke rehabilitation
system,” ICCIS, Vol. 1, pp. 55-60, Jun 2012.
A. Dinevan, Y. M. Aung, and A. Al-Jumaily, “Human
computer interactive system for fast recovery based
stroke rehabilitation,” HIS, pp. 647-652, Dec 2011.
P. Mirza-Babaei, M. Kamkarhaghighi, and K.
Gerling,“Opportunities in game-based stroke
rehabilitation,” GEM, pp. 1-4, Oct 2014.
C. H. Lee, Y. H. Chiu, H. Y. Kao, I. T. Chen, I. N.
Lee, W. H. Ho, and H. Y.Lu, “A Body-Sensed Motor
Assessment System for Stroke Upper-Limb
Rehabilitation: A Preliminary Study,” SMC, pp. 3819-
3824, Oct 2013.
D. White, K. Burdick, G. Fulk, J. Searleman, and J.
Carroll, “A virtual reality application for stroke
patient rehabilitation,” Mechatronics and Automation,
Vol. 2, pp. 1081-1086, 2005.
R. Akerkar, “Introduction to artificial
intelligence,” PHI Learning Pvt. Ltd, 2014.
S. Miksch, W. Horn, C. Popow, and F. Paky, “Utilizing
temporal data abstraction for data validation and
therapy planning for artificially ventilated newborn
infants,” Artificial intelligence in medicine, Vol.
8, No. 6, pp. 543-576, 1996.
C. Ohmann, V. Moustakis, Q. Yang, K. Lang, and Acute
Abdominal Pain Study Group, “Evaluation of automatic
knowledge acquisition techniques in the diagnosis of
acute abdominal pain,” Artificial intelligence in
medicine, Vol. 8, No. 1, pp. 23-36, 1996.
Y. Shahar, and M. A. Musen,“Knowledge-based temporal
abstraction in clinical domains,” Artificial
intelligence in medicine, Vol. 8, No. 3, pp. 267-298,
R. Bellazzi, C. Siviero, M. Stefanelli, and G.
Nicolao,“Adaptive controllers for intelligent
monitoring,” Artificial intelligence in medicine,
Vol. 7, No. 6, pp. 515-540, 1995.
R. Davis, B. Buchanan, and E. Shortliffe, “Production
rules as a representation for a knowledge-based
consultation program,” Artificial intelligence, Vol.
8, No. 1, pp. 15-45, 1977.
C. P. Langlotz, L. M. Fagan, S. W. Tu, B. I. Sikic,
and E. H. Shortliffe, “A therapy planning
architecture that combines decision theory and
artificial intelligence techniques,” Computers and
Biomedical Research, Vol. 20, No. 3, pp. 279-303,
J. S. Aikins, “Prototypical knowledge for expert
systems,” Artificial Intelligence, Vol. 20, No. 2,
pp. 163-210, 1983.
I. Werry, K. Dautenhahn,B. Ogden, and W. Harwin, “Can
social interaction skills be taught by a social
agent? The role of a robotic mediator in autism
therapy,” Cognitive technology, pp. 57-74, 2001.
K. Dautenhahn, and I. Werry, “Towards interactive
robots in autism therapy: Background, motivation and
challenges,” Pragmatics & Cognition, Vol. 12, No. 1,
pp. 1-35, 2004.
J. Fox, M. Beveridge, and D. Glasspool,
“Understanding intelligent agents: analysis and
synthesis,” Aicommunications, Vol. 16, No. 3, pp.
G. L. Clore, and J. Palmer,“Affective guidance of
intelligent agents:How emotion controls cognition,”
Cognitive systems research, Vol. 10, No. 1, pp. 21-
T. Exell, C. Freeman, K. Meadmore, M. Kutlu, E.
Rogers, A. M. Hughes, and J. Burridge, “Goal
orientated stroke rehabilitation utilising electrical
stimulation, iterative learning and microsoft
Kinect,” ICORR, pp. 1-6, Jun 2013.
L. Shires, S. Battersby, J. Lewis, D. Brown, N.
Sherkat, and P. Standen,“Enhancing the tracking
capabilities of the Microsoft Kinect for stroke
rehabilitation,” SeGAH, pp. 1-8, May 2013.
D. Webster, and O. Celik, “Experimental evaluation of
Microsoft Kinect′s accuracy and capture rate for
stroke rehabilitation applications,” HAPTICS, pp.
J. M. I. Zannatha, A. J. M. Tamayo, Á. D. G. Sánchez,
J. E. L. Delgado, L. E. R. Cheu, and W. A. S.
Arévalo, “Development of a system based on 3D vision,
interactive virtual environments, ergonometric
signals and a humanoid for stroke rehabilitation,”
Computer methods and programs in biomedicine, Vol.
112, No.2, pp. 239-249, 2013.
R. T. Azuma, “A survey of augmented reality,”
Presence, Vol. 6, No. 4, pp. 355-385, 1997.
NVIDIA. [Online]. Available:http://www.nvidia.com.tw/object/io_1270555014738.html
J. P. Cuthbert, K. Staniszewski, K. Hays, D. Gerber,
A. Natale, and D. O′Dell, “Virtual reality-based
therapy for the treatment of balance deficits in
patients receiving inpatient rehabilitation for
traumatic brain injury,” Brain injury, Vol. 28, No.
2, pp. 181-188, 2014.
H. Sin and G. Lee, “Additional virtual reality
training using Xbox Kinect in stroke survivors with
hemiplegia,” American Journal Of Physical Medicine &
Rehabilitation, Vol. 92, No.10, pp. 871-880, 2013.
B. Wiederhold and G. Riva, “Balance recovery through
virtual stepping exercises using Kinect skeleton
tracking: a follow-up study with chronic stroke
patients,” Annual Review of Cybertherapy and
Telemedicine 2012, Vol. 181, pp. 108, 2012.
K. H. Cho, K. J. Lee, and C. H. Song, “Virtual-
reality balance training with a video-game system
improves dynamic balance in chronic stroke patients,”
The Tohoku journal of experimental medicine, Vol.
228, No. 1, pp. 69-74, 2012.
A. Turolla, M. Dam, L. Ventura, P. Tonin, M.
Agostini, C. Zucconi, and L. Piron, “Virtual reality
for the rehabilitation of the upper limb motor
function after stroke: a prospective controlled
trial,” J Neuroeng Rehabil, Vol. 10, pp. 85, 2013.
I. Pastor, H. A. Hayes, and S. J. Bamberg, “A
feasibility study of an upper limb rehabilitation
system using kinect and computergames,” EMBC, pp.
1286-1289, Aug 2012.
A. Panarese, R. Colombo, I. Sterpi, F. Pisano, and S.
Micera, “Tracking motor improvement at the subtask
level during robot-aided neurorehabilitation of
stroke patients,” Neurorehabilitation and neural
repair, Vol. 26, No. 7, pp. 822-833, 2012.
Q. Ding, I. H. Stevenson, N. Wang, W. Li, Y. Sun, Q.
Wang, and K. Wei, “Motion games improve balance
control in stroke survivors: A preliminary study
based on the principle of constraint-induced movement
therapy,” Displays, Vol. 34, No. 2, pp. 125-131,
L. Paul, H. Debbie, B. Jennifer, L. Hervé,“A haptic-
robotic platform for upper-limb reaching stroke
therapy: Preliminary design and evaluation results,”
J Neuroeng Rehabil, Vol. 5, No. 15, 2008.
National Center for Biotechnology Information
S. Hesse, A. Waldner, and C. Tomelleri, “Innovative
gait robot for the repetitive practice of floor
walking and stair climbing up and down in stroke
patients,” Journal of Neuro Engineering and
Rehabilitation, Vol. 7, No. 30, 2010.
Journal of NeuroEngineering and Rehabilitation.
B. Dorey, D. Reid, and T. Chiu, “ Stroke survivor’s
experiences of computer use at home,” Technology and
Disability, Vol. 19, No. 4, pp. 179-188, 2007.
L. Rosenstein, A. L. Ridgel, A. Thota, B. Samame, and
J. L. Alberts, “Effects of combined robotic therapy
and repetitive-task practice on upper-extremity
function in a patient with chronic stroke,” American
Journal of Occupational Therapy, Vol. 62, pp. 28-35,
H. C. Huang, C. H. Yeh, C. M. Chen, Y. S. Lin, and K.
C. Chung, “Sliding and pressure evaluation on
conventional and V-shaped seats of reclining
wheelchairs for stroke patients with flaccid
hemiplegia: a crossover trial,” Journal of
NeuroEngineering and Rehabilitation, Vol. 8, No. 40,
P. Bagley, M. Hudson, A. Foster, J. Smith, and J.
Young, “A randomized trial evaluation of the Oswestry
Standing Frame for patients after stroke,” Clinical
Rehabilitation, Vol. 19, pp. 354-364, 2005.
H. A. Isma′eel, G. E. Sakr, M. M. Almedawar, J.
Fathallah , T. Garabedian, S. B. Eddine, L.
Nasreddine, and I. H. Elhajj, “Artificial neural
network modeling using clinical and knowledge
independent variables predicts salt intake reduction
behavior,” Cardiovasc Diagn Ther, Vol. 5, No. 3, pp.
219-228, Jun 2015.
H. Karamanli, T. Yalcinoz, M. A. Yalcinoz, and T.
Yalcinoz, “A prediction model based on artificial
neural networks for the diagnosis of obstructive
sleep apnea,” Sleep Breath, 2015.
S. C. Hu, “Texture Analysis for Aided Diagnosis of
Hemorrhage Transformation of Acute Middle Ischemic
Stroke in CT Images,” Department of Bio-Medical
Engineering, Mar 2012.
C. Spearman,“The proof and measurement of association
between two things,” The American journal of
psychology, Vol. 15, pp.72-101, 1904.
P. J. Rousseeuw, “Silhouettes: a graphical aid to the
interpretation and validation of cluster analysis,”
Journal of computational and applied mathematics,
Vol. 20, pp. 53-65, 1987.
CHRIS MCCORMICK. [Online].
R. E. Fan, P. H. Chen, and C. J. Lin, “Working Set
Selection Using Second Order Information for
Training Support Vector Machines,” J. Mach. Learn.
Res., Vol. 6, pp. 1889-1918, 2005.