Zehra, Syeda Sabeeka; (2018) Electromyogram Interference Reduction In Neural Signal Recording Using Simple RC Compensation Circuits. Masters thesis (M.Phil), UCL (University College London).

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Abstract

Neuroprosthesis can partially restore lost motor functionalities of individuals such as bladder voiding using functional electrical stimulation (FES) techniques. FES involves applying pattern of electrical current pulses using implanted electrodes to trigger affected nerves that are damaged due to paralysis. A neural signal recorded using tripolar cuff electrodes is significantly contaminated due to the presence of EMG interference from the surrounding muscles. Conventional neural amplifiers are unable to remove such interferences and modifications to the design are required. The modification to the design of the Quasi-tripole (QT) amplifier is considered in this work to minimise the EMG interferences from neural signal recording. The analogy between this modified version of QT known as mQT and Wheatstone bridge claims to neutralise the EMG interference by adding compensation circuit to either end of the outer electrodes of the tripolar cuff and therefore balancing the bridge. In this work, we present simple 3 and 2 stage RC compensation circuits to minimise EMG interference in trying to balance the bridge in the neural frequency band of interest (500-10kHz). It is shown that simple RC compensation circuit in series reduces EMG interference only at the spot frequency rather than linearly in the entire frequency band of interest. However, two and three stages RC ladder compensation circuits mimicking electrode-electrolyte interface, can minimize the EMG interference linearly in the entire frequency band of interest, without requiring any readjustment to their components. The aim is to minimise EMG interference as close to null as possible. Invitro testing of about 20% imbalanced cuff electrode with proposed 3 and 2 stage RC ladder compensation circuits resulted in linear EMG interference reduction atleast by a factor of 6. On an average, this yielded an improvement of above 80% EMG minimisation, in contrast to above 90% observed in the optimisation results, when 1Ω transimpedance (EMG) was introduced into the setup. Further improvements to the setup and design can give more promising results in reliable neural signal recording for FES applications.

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