Monil Chheta
Papers
1
Total Citations
29
H-Index
1
About
Monil Chheta is a researcher focused on biomedical signal processing, with a particular emphasis on electroencephalography (EEG) and the critical challenge of artefact removal. His most cited work, "Classification of Artefacts in EEG Signal Recordings and EOG Artefact Removal using EOG Subtraction" (2016, 29 citations), provides a foundational framework for categorizing physiological and external noise sources that corrupt neural recordings. By systematically classifying artefacts—such as those from eye movements (EOG) or muscle activity—and demonstrating effective subtraction techniques, Chheta has contributed to improving the fidelity of brain-computer interface (BCI) and clinical EEG data. His research addresses a key bottleneck in neuroscience: ensuring that clean signals are available for accurate diagnosis or device control. While his citation count reflects a focused, early-career impact, his work on artefact classification remains a practical reference for students and researchers entering the field of EEG analysis. Chheta’s contributions underscore the importance of signal quality in advancing both fundamental neuroscience and applied neurotechnology.
Research Focus
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Top Papers
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