Papers
1
Total Citations
30
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About
Dr. Prateek Virdi’s research lies at the intersection of biomedical signal processing and machine learning, with a primary focus on developing intelligent systems for human movement analysis. His most cited work, “Discrete Wavelet Packet based Elbow Movement classification using Fine Gaussian SVM” (2016, 30 citations), introduces a novel framework that leverages Wavelet Packet Transform (WPT) for denoising and feature extraction from surface electromyogram (sEMG) signals. By applying a Fine Gaussian Support Vector Machine, Dr. Virdi achieved robust classification of elbow movements from data collected across nine healthy subjects, with preprocessing conducted using MyoResearch XP software. This contribution is significant for advancing prosthetic control and rehabilitation technologies, offering a computationally efficient approach to decoding neuromuscular activity. The paper’s citation count underscores its influence in the field of human–machine interfaces. Dr. Virdi’s work demonstrates a commitment to translating complex signal processing techniques into practical solutions for assistive devices, making him a notable figure in biomedical engineering research.
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