Tanimura, Toru and Iida, Daisuke and Jono, Yusuke and Takada, Masumi and Matsuura, Yasuyuki and Takada, Hiroki (2019) Nonlinear Analysis Using Multiple Cutoff Frequencies for Local Cerebral Blood Flow during Biofeedback Training. Journal of Advances in Medicine and Medical Research, 28 (6). pp. 1-12. ISSN 24568899
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Abstract
Biofeedback (BF) is expected not only as a means for gaining control of bodily processes to increase relaxation, relieve pain and improve health, but also to develop and improve the brain's body control function. The aim of the biofeedback training (BFT) is to promote the recovery and the development of physical dysfunctions under consciousness. A BF instrument has three tasks. First is to monitor (in some way) a physiological process of interest. Second is to measure (quantify) what is monitored. Third is to present what is monitored or measured as meaningful information. One technique for non-invasive measurement of brain activity that has been developed in recent years is brain functional imaging using near-infrared spectroscopy (NIRS). Compared to other techniques of measurement of brain activity, NIRS is a low-restraint and non-invasive measuring technique. In addition, it enables a user to take electrophysiological measurements such as Electromyography and Electrocardiography during training activity or other movements. In recent years, NIRS has a high profile for investigations of the relationship between physical control and brain function.
Here, we investigated the connection between BFT and local cerebral blood flow, by performing cranial NIRS with simultaneous electromyogram (EMG), recording from the rectus femoris muscle. Our results suggest that We have succeeded in findings of the nonlinearity for hemodynamics in the cerebral blood flow on the frontal lobe during the muscle contraction and the post-rest.
Item Type: | Article |
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Subjects: | East India library > Medical Science |
Depositing User: | Unnamed user with email support@eastindialibrary.com |
Date Deposited: | 06 May 2023 08:14 |
Last Modified: | 13 Sep 2024 07:53 |
URI: | http://info.paperdigitallibrary.com/id/eprint/833 |