Publication: ANN-based nerve damage preservation system for neurosurgical operation
Issued Date
2014-02-18
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2-s2.0-84946530934
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Mahidol University
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SCOPUS
Bibliographic Citation
2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014. (2014), 307-310
Suggested Citation
Dilok Puanhvuan, Sarawin Khemmachotikun, Sorayouth Chumnanvej, Yodchanan Wongsawat ANN-based nerve damage preservation system for neurosurgical operation. 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems, SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems, ISIS 2014. (2014), 307-310. doi:10.1109/SCIS-ISIS.2014.7044851 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/33677
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Title
ANN-based nerve damage preservation system for neurosurgical operation
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Abstract
© 2014 IEEE. The neurophysiologic intraoperative monitoring system (NIOM) is used for assessing the nerve function during operation. The free running electromyography (EMG) and the compound muscle action potential (CMAP) are monitored by the neurophysiologist for surgical intervention to avoid neurophysiologic deficit. However, there is a variation of surgical intervention in different neurophysiologist. 50% decrease in amplitude of CMAP response is considered as nerve damage compared with the baseline which may vary in particular case. These would make the nerve function estimation qualitative evaluated by neurophysiologist. This study aimed to investigate the quantitative method of nerve function prediction. Instead of applying one pulse stimulus, the varied current amplitude pulse train was applied to the nerve to obtain the variation of the CMAP responses. The varied CMAP responses were used as an input of artificial neuron network (ANN) for estimating the remaining nerve function. The results revealed that the estimated nerve damage level was linearly correlated with the measured nerve damage.