DocumentCode
601998
Title
Automation training model construction of forced running wheel exercise for stroke recovery
Author
Chi-Chun Chen ; Shih-Chieh Chan ; Chin-Lung Yang
Author_Institution
Dept. of Electr. Eng., Nat. Chen Kung Univ., Tainan, Taiwan
fYear
2013
fDate
12-16 March 2013
Firstpage
31
Lastpage
34
Abstract
This study implemented a forced running wheel system which applied automatic exercise training model to replace the traditional treadmill that trained animals manually. The proposed platform will be further applied to the efficacy of pre-conditioning exercise induced neuroprotection to prevent the animal stroke model. This proposed forced running wheel system not only solved the shortcomings of traditional treadmill use of electric shocks to force the mice to running, but more scientific method to construct the automatic training model to train the animals to achieve the purpose of endurance exercises. The experiments were processed from the mouse without the running wheel experiences to start training until the fifth day, and the experimental data was analyzed to construct an accelerative exercise training curve of exponential type from 0 - 20 meters per minute. Preliminary results indicate that the similar increase degrees of body temperature after exercising, compared the proposed automatic platform with the traditional treadmill, verifying the feasibility of this system.
Keywords
biomechanics; neurophysiology; patient care; accelerative exercise training curve; animal stroke model; automatic exercise training model; automation training model construction; body temperature; endurance exercise; forced running wheel exercise system; neuroprotection; preconditioning exercise; stroke recovery; Acceleration; DC motors; Electric shock; Mice; Training; Wheels; Forced running wheel; automatic training model; neuroprotection; stroke; treadmill;
fLanguage
English
Publisher
ieee
Conference_Titel
Orange Technologies (ICOT), 2013 International Conference on
Conference_Location
Tainan
Print_ISBN
978-1-4673-5934-4
Type
conf
DOI
10.1109/ICOT.2013.6521150
Filename
6521150
Link To Document