Papers
5
Total Citations
317
H-Index
5
About
Sachin Taran is a leading researcher in biomedical signal processing and brain-computer interfaces (BCIs), with a focus on decoding neural and muscular activity for assistive technologies. His most cited work, “Motor imagery tasks-based EEG signals classification using tunable-Q wavelet transform” (2018, 97 citations), introduced a novel signal decomposition method that significantly improved the accuracy of classifying imagined motor tasks from EEG data—a critical step for non-invasive BCI systems. Building on this, his 2020 study (97 citations) employed a flexible analytic wavelet transform to further enhance motor-imagery classification, demonstrating robust performance across diverse subjects. Taran has also advanced physical action recognition using surface EMG signals, notably through a 2019 paper (69 citations) that combined deep transfer learning with EMG data to classify movements with high precision. His work on environmental sound classification (38 citations) showcases his versatility in applying signal processing techniques to real-world auditory tasks. With over 300 total citations, Taran’s contributions are foundational for developing intuitive, real-time BCI and prosthetic control systems, bridging the gap between raw biosignals and practical human-machine interfaces.
Research Focus
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