Papers
2
Total Citations
58
H-Index
2
About
Nandini Jog is a researcher whose work centers on the critical challenge of cleaning electroencephalography (EEG) signals—the electrical recordings of brain activity—by identifying and removing artifacts, or unwanted noise. Her primary contributions lie in the classification and elimination of these contaminating signals, which are essential for accurate brain-computer interface and neurological research. Jog systematically categorized artifacts into physiological sources (like eye blinks and muscle movements) and external ones, providing a foundational framework for the field. Her two most-cited papers, "Classification of Artefacts in EEG Signal Recordings and Overview of Removing Techniques" (2015) and "Classification of Artefacts in EEG Signal Recordings and EOG Artefact Removal using EOG Subtraction" (2016), each have garnered 29 citations, highlighting their practical value to the research community. Notably, her work on EOG subtraction offers a targeted method for removing ocular artifacts, a persistent problem in EEG analysis. Through these contributions, Jog has helped advance the reliability of brain signal processing, making her a key figure for students and researchers seeking to understand or implement artifact removal techniques in neurotechnology.
Research Focus
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Top Papers
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