Kiret Dhindsa
Affiliations: | McMaster University, Hamilton, ON, Canada |
Area:
machine learning, brain-computer interfacing, neurofeedback, computational neuroscience, signal processing, data science, neuroscienceGoogle:
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Publications
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| Smail LC, Dhindsa K, Braga LH, et al. (2020) Using Deep Learning Algorithms to Grade Hydronephrosis Severity: Toward a Clinical Adjunct. Frontiers in Pediatrics. 8: 1 |
| Shaw SB, Dhindsa K, Reilly JP, et al. (2019) Capturing the Forest But Missing the Trees: Microstates Inadequate for Characterizing Shorter-Scale EEG Dynamics. Neural Computation. 1-35 |
| Dhindsa K, Acai A, Wagner N, et al. (2019) Individualized pattern recognition for detecting mind wandering from EEG during live lectures. Plos One. 14: e0222276 |
| Boshra R, Dhindsa K, Boursalie O, et al. (2019) From Group-Level Statistics to Single-Subject Prediction: Machine Learning Detection of Concussion in Retired Athletes. Ieee Transactions On Neural Systems and Rehabilitation Engineering : a Publication of the Ieee Engineering in Medicine and Biology Society |
| Dhindsa K, Gauder KD, Marszalek KA, et al. (2018) Progressive Thresholding: Shaping and Specificity in Automated Neurofeedback Training. Ieee Transactions On Neural Systems and Rehabilitation Engineering : a Publication of the Ieee Engineering in Medicine and Biology Society |
| Dhindsa K, Carcone D, Becker S. (2017) Toward an Open-Ended BCI: A User-Centered Coadaptive Design. Neural Computation. 1-27 |
| Dhindsa K. (2017) Filter-Bank Artifact Rejection: High performance real-time single-channel artifact detection for EEG Biomedical Signal Processing and Control. 38: 224-235 |
| Dhindsa K, Drobinin V, King J, et al. (2014) Examining the role of the temporo-parietal network in memory, imagery, and viewpoint transformations. Frontiers in Human Neuroscience. 8: 709 |