Wiener filtering and classification of neurographic recordings - BMES/EMBS Conference, 1999. Proceedings of the First Joint
نویسنده
چکیده
Methods were developed to improve the SIN ratio and selectivity of nerve recordings, and to allow classification of nerve signals originating from activation of different fiber diameter populations (e.g. different receptors). The need for these methods arose from our ‘bladder pacemaker’ research, where nerve cuff electrodes were placed around the feline sacral spinal roots to monitor urinary bladder afferent activity. A novel technique to design Wiener filters for neurographic recordings was developed, which resulted in improved SM ratio and selectivity of the recordings. Since the sacral roots innervate dermatomes and the rectum, the nerve signal increases had to be classified to extract bladder afferent information only. Multilayer perceptron neural network was trained with different autocorrelation functions to classify bladder, rectal and cutaneous nerve signal increases.
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Methods for modeling the relationship between extracellular recording variability and impedance prop - BMES/EMBS Conference, 1999. Proceedings of the First Joint
A finite element model has been developed to investigate the theoretical relationship between changes in extracellular resistivity and electrical potential in a chronic extracellular recording scenario. The inputs to the model are experimental results obtained from chronic recording and complex impedance measurements in cerebral cortex of adult guinea pigs. Using the measured tissueelectrode im...
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Pii: S0165-0270(01)00334-x
Electroneurographic recordings suffer from low signal to noise (S/N) ratios. The S/N ratio can be improved by different signal processing methods including optimal filtering. A method to design two types of optimal filters (Wiener and Matched filters) was developed for use with neurographic signals, and the calculated filters were applied to nerve cuff recordings from the cat S1 spinal root tha...
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