2020 - Fellow, National Academy of Inventors
1996 - Fellow of the Indian National Academy of Engineering (INAE)
His main research concerns Artificial intelligence, Neuroscience, Electroencephalography, Speech recognition and Computer vision. His work carried out in the field of Artificial intelligence brings together such families of science as Decoding methods, Task, Brain–computer interface and Pattern recognition. His study explores the link between Neuroscience and topics such as Biomedical engineering that cross with problems in Speckle pattern.
His Electroencephalography course of study focuses on Asphyxia and Electrophysiology. He works mostly in the field of Speech recognition, limiting it down to concerns involving Algorithm and, occasionally, Wavelet, Ventricular tachycardia and Ventricular fibrillation. His Computer vision study integrates concerns from other disciplines, such as Endoscope and Biomechanics.
Nitish V. Thakor mainly investigates Artificial intelligence, Electroencephalography, Neuroscience, Biomedical engineering and Pattern recognition. Nitish V. Thakor interconnects Machine learning, Decoding methods and Computer vision in the investigation of issues within Artificial intelligence. His biological study spans a wide range of topics, including Anesthesia, Asphyxia and Speech recognition.
Anesthesia is closely attributed to Ischemia in his research. He has included themes like Signal and Signal processing in his Speech recognition study. Neurophysiology, Stimulation, Somatosensory evoked potential, Somatosensory system and Thalamus are among the areas of Neuroscience where the researcher is concentrating his efforts.
His primary areas of investigation include Artificial intelligence, Electroencephalography, Biomedical engineering, Stimulation and Neuroscience. His Artificial intelligence research incorporates themes from Computer vision and Pattern recognition. His work deals with themes such as Cognition, Sensory stimulation therapy, Task analysis and Perception, which intersect with Electroencephalography.
The Biomedical engineering study combines topics in areas such as Photoacoustic imaging in biomedicine, Contrast, Ultrasound, Triboelectric effect and Actuator. His study looks at the intersection of Stimulation and topics like Prosthesis with Electromyography and Pattern recognition. All of his Neuroscience and Sensory system and Inhibitory postsynaptic potential investigations are sub-components of the entire Neuroscience study.
His primary areas of study are Biomedical engineering, Stimulation, Artificial intelligence, Electroencephalography and Photon upconversion. His Biomedical engineering study combines topics from a wide range of disciplines, such as Muscle Stimulation, Triboelectric effect, Electrical muscle stimulation, Magnetic resonance imaging and Actuator. His research integrates issues of Peripheral nerve and Urology in his study of Stimulation.
His studies link Pattern recognition with Artificial intelligence. His Electroencephalography study incorporates themes from Spectral density, Degree, Algorithm, Sample entropy and Discriminative model. His study in Photon upconversion is interdisciplinary in nature, drawing from both Biological neural network and Light attenuation.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Applications of adaptive filtering to ECG analysis: noise cancellation and arrhythmia detection
N.V. Thakor;Y.-S. Zhu.
IEEE Transactions on Biomedical Engineering (1991)
Cellular effects of deep brain stimulation: model-based analysis of activation and inhibition.
Cameron C. McIntyre;Warren M. Grill;David L. Sherman;Nitish V. Thakor.
Journal of Neurophysiology (2004)
Estimation of QRS Complex Power Spectra for Design of a QRS Filter
Nitish V. Thakor;John G. Webster;Willis J. Tompkins.
IEEE Transactions on Biomedical Engineering (1984)
Electric field and stimulating influence generated by deep brain stimulation of the subthalamic nucleus
Cameron C. McIntyre;Susumu Mori;David L. Sherman;Nitish V. Thakor.
Clinical Neurophysiology (2004)
Detecting ventricular tachycardia and fibrillation by complexity measure
Xu-Sheng Zhang;Yi-Sheng Zhu;N.V. Thakor;Zhi-Zhong Wang.
IEEE Transactions on Biomedical Engineering (1999)
Implantable myocardial ischemia detection, indication and action technology
Ananth Natarajan;Nitish V. Thakor.
Power harvesting and telemetry in CMOS for implanted devices
C. Sauer;M. Stanacevic;G. Cauwenberghs;N. Thakor.
ieee international workshop on biomedical circuits and systems (2004)
Decoding of Individuated Finger Movements Using Surface Electromyography
F.V.G. Tenore;A. Ramos;A. Fahmy;S. Acharya.
IEEE Transactions on Biomedical Engineering (2009)
Advances in Quantitative Electroencephalogram Analysis Methods
Nitish V. Thakor;Shanbao Tong.
Annual Review of Biomedical Engineering (2004)
Parkin facilitates the elimination of expanded polyglutamine proteins and leads to preservation of proteasome function.
Yien Che Tsai;Paul S. Fishman;Nitish V. Thakor;George A. Oyler.
Journal of Biological Chemistry (2003)
Medical and Biological Engineering and Computing
(Impact Factor: 3.079)
Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: