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 :
بازگشت