31 March 2009 Neuroelectronics and modeling of electrical signals for monitoring and control of Parkinson's disease
Author Affiliations +
Abstract
The brain and the human nervous system are perhaps the most researched but least understood components of the human body. This is so because of the complex nature of its working and the high density of functions. The monitoring of neural signals could help one better understand the working of the brain and newer recording and monitoring methods have been developed ever since it was discovered that the brain communicates internally by means of electrical pulses. Neuroelectronics is the field which deals with the interface between electronics or semiconductors to living neurons. This includes monitoring of electrical activity from the brain as well as the development of feedback devices for stimulation of parts of the brain for treatment of disorders. In this paper these electrical signals are modeled through a nano/microelectrode arrays based on the electronic equivalent model using Cadence PSD 15.0. The results were compared with those previously published models such as Kupfmuller and Jenik's model, McGrogan's Neuron Model which are based on the Hodgkin and Huxley model. We have developed and equivalent circuit model using discrete passive components to simulate the electrical activity of the neurons. The simulated circuit can be easily be modified by adding some more ionic channels and the results can be used to predict necessary external stimulus needed for stimulation of neurons affected by the Parkinson's disease (PD). Implementing such a model in PD patients could predict the necessary voltages required for the electrical stimulation of the sub-thalamus region for the control tremor motion.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ritesh R. Chintakuntla, Ritesh R. Chintakuntla, Jose K. Abraham, Jose K. Abraham, Vijay K. Varadan, Vijay K. Varadan, } "Neuroelectronics and modeling of electrical signals for monitoring and control of Parkinson's disease", Proc. SPIE 7291, Nanosensors, Biosensors, and Info-Tech Sensors and Systems 2009, 72910T (31 March 2009); doi: 10.1117/12.829927; https://doi.org/10.1117/12.829927
PROCEEDINGS
9 PAGES


SHARE
Back to Top