What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Statistics
- Machine learning
Cuntai Guan mainly investigates Brain–computer interface, Artificial intelligence, Electroencephalography, Pattern recognition and Motor imagery.
His Brain–computer interface research is multidisciplinary, relying on both Speech recognition, Information transfer and Event-related potential.
His research in Artificial intelligence intersects with topics in Algorithm, Machine learning and Computer vision.
His research investigates the connection between Electroencephalography and topics such as Stroke patient that intersect with problems in Eeg data, Finger tapping and Kullback–Leibler divergence.
His Pattern recognition research is multidisciplinary, incorporating elements of Feature, Algorithm design, Selection, Covariance matrix and Signal processing.
His Motor imagery research includes themes of Rehabilitation, Physical medicine and rehabilitation and Motor control.
His most cited work include:
- Regularizing Common Spatial Patterns to Improve BCI Designs: Unified Theory and New Algorithms (609 citations)
- Filter Bank Common Spatial Pattern (FBCSP) in Brain-Computer Interface (573 citations)
- Temporal classification of multichannel near-infrared spectroscopy signals of motor imagery for developing a brain-computer interface. (481 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Artificial intelligence, Brain–computer interface, Electroencephalography, Pattern recognition and Motor imagery.
His Artificial intelligence research incorporates elements of Machine learning, Speech recognition and Computer vision.
He studied Brain–computer interface and Physical medicine and rehabilitation that intersect with Stroke and Transcranial direct-current stimulation.
The Electroencephalography study combines topics in areas such as Neurophysiology and Audiology.
His work carried out in the field of Pattern recognition brings together such families of science as Filter bank and Signal processing.
His Motor imagery research incorporates themes from Deep learning and Convolutional neural network.
He most often published in these fields:
- Artificial intelligence (59.23%)
- Brain–computer interface (47.69%)
- Electroencephalography (39.74%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (59.23%)
- Brain–computer interface (47.69%)
- Electroencephalography (39.74%)
In recent papers he was focusing on the following fields of study:
Cuntai Guan focuses on Artificial intelligence, Brain–computer interface, Electroencephalography, Pattern recognition and Motor imagery.
He combines topics linked to Machine learning with his work on Artificial intelligence.
His biological study spans a wide range of topics, including Rehabilitation, Cognitive psychology, Physical medicine and rehabilitation, Stroke and Brain activity and meditation.
The various areas that Cuntai Guan examines in his Electroencephalography study include Stroop effect, Support vector machine and Audiology.
His work deals with themes such as Decoding methods, Filter bank, Multivariate statistics and Signal processing, which intersect with Pattern recognition.
His study explores the link between Feature extraction and topics such as Pattern recognition that cross with problems in Statistical classification.
Between 2017 and 2021, his most popular works were:
- Learning Temporal Information for Brain-Computer Interface Using Convolutional Neural Networks (140 citations)
- A Survey on Explainable Artificial Intelligence (XAI): Toward Medical XAI. (106 citations)
- A review on EMG-based motor intention prediction of continuous human upper limb motion for human-robot collaboration (64 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- Machine learning
His scientific interests lie mostly in Brain–computer interface, Electroencephalography, Artificial intelligence, Convolutional neural network and Feature extraction.
Cuntai Guan interconnects Affect, Neuroimaging, Physical medicine and rehabilitation and State in the investigation of issues within Brain–computer interface.
His work in the fields of Electroencephalography, such as Motor imagery, intersects with other areas such as Response time.
His Artificial intelligence study incorporates themes from Machine learning and Pattern recognition.
His Convolutional neural network research integrates issues from Feature and Pattern recognition.
His research investigates the link between Feature extraction and topics such as Discriminative model that cross with problems in Movement, Binary classification and Wavelet.
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