Publication: Linear model of peripheral nerve after surgical manipulation: Preliminary report in animal study and model shift
Issued Date
2013-10-31
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ISSN
1557170X
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2-s2.0-84886503436
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Mahidol University
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SCOPUS
Bibliographic Citation
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. (2013), 4973-4976
Suggested Citation
Dilok Puanhvuan, Sorayouth Chumnanvej, Yodchanan Wongsawat Linear model of peripheral nerve after surgical manipulation: Preliminary report in animal study and model shift. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. (2013), 4973-4976. doi:10.1109/EMBC.2013.6610664 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/31619
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Title
Linear model of peripheral nerve after surgical manipulation: Preliminary report in animal study and model shift
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Abstract
Generally, the neurophysiologic intra-operative monitoring (NIOM) is acknowledged to correlate with reducing the risk of perioperative neurological deficits. This electrophysiological method is commonly used and neurosurgeons could aware where the nervous system is at risk of being permanently injured while doing the operation under NIOM. However, this monitoring is quite a qualitative evaluation. Neurosurgeons have to use their own experiences to consider and made the estimation. Traditionally, the peripheral nerve function can be preserved by continuous electromyography (EMG) and compound muscle action potential response (CMAP) monitoring. The spike and burst EMG occur when the nerve trunk is irritated or damaged. Decreased amplitude of CMAP response is also considered as nerve damage even it might cause from a severe irritation. By using this information, the peripheral nerve function is qualitatively evaluated by the surgeons. This present study proposed a new predictive nerve model for peripheral nerve function prediction. This input and output data were used for nerve modeling in each condition. The results showed that parameters of the linear nerve model had significantly differences and tendency changes in each nerve condition. Therefore, the proposed method for predicting the nerve function by the shifted linearly nerve model might be a promising approach for peripheral nerve function estimation in the human nerve model. © 2013 IEEE.