A Feature Fusion-Based Discriminant Learning Model for Diagnosis of Neuromuscular Disorders Using Single-Channel Needle Electromyogram Signals
A. Hazarika and M. Bhuyan, Department of Electronics and Communication Engineering, Tezpur University, Tezpur, India
Abstract
Large-scale information embedding is the key to develop an efficient and reliable process monitoring and diagnosis model. This chapter addresses a feature fusion-based data-driven model for diagnosis of neuromuscular disorders. The core focus is to develop an information fusion framework that can employ large-scale available data for viable real-time applications. For model validation and performance investigation, a real-time electromyogram dataset that includes various ...
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