What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Neuroscience
- Electroencephalography
Christoph Guger mainly focuses on Brain–computer interface, Electroencephalography, Motor imagery, Speech recognition and Artificial intelligence.
His Brain–computer interface research incorporates elements of Control, Communication and Virtual reality, Human–computer interaction.
He has included themes like Cursor and Audiology in his Electroencephalography study.
His research investigates the connection with Motor imagery and areas like Communications system which intersect with concerns in Brain activity and meditation.
Christoph Guger interconnects Eeg data and Feature extraction in the investigation of issues within Speech recognition.
The Artificial intelligence study combines topics in areas such as Computer vision and Pattern recognition.
His most cited work include:
- How many people are able to control a P300-based brain-computer interface (BCI)? (494 citations)
- Current trends in Graz brain-computer interface (BCI) research (449 citations)
- How many people are able to operate an EEG-based brain-computer interface (BCI)? (411 citations)
What are the main themes of his work throughout his whole career to date?
Christoph Guger focuses on Brain–computer interface, Electroencephalography, Motor imagery, Human–computer interaction and Artificial intelligence.
His research integrates issues of Rehabilitation, Speech recognition, Virtual reality and Physical medicine and rehabilitation in his study of Brain–computer interface.
His work on Event-related potential as part of general Electroencephalography study is frequently connected to Altitude, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
His Neurorehabilitation research extends to Motor imagery, which is thematically connected.
His biological study spans a wide range of topics, including Control, Multimedia, Brain activity and meditation and Simulation.
His Artificial intelligence study integrates concerns from other disciplines, such as Computer vision and Pattern recognition.
He most often published in these fields:
- Brain–computer interface (64.42%)
- Electroencephalography (30.29%)
- Motor imagery (23.56%)
What were the highlights of his more recent work (between 2017-2021)?
- Brain–computer interface (64.42%)
- Physical medicine and rehabilitation (17.79%)
- Motor imagery (23.56%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Brain–computer interface, Physical medicine and rehabilitation, Motor imagery, Electroencephalography and Stroke.
His Brain–computer interface study combines topics in areas such as Audiology, Speech recognition, Sensory stimulation therapy, Cognition and Artificial intelligence.
His research in Speech recognition intersects with topics in Auditory oddball and Sine wave.
His Physical medicine and rehabilitation study combines topics from a wide range of disciplines, such as Rehabilitation, Chronic stroke, Functional electrical stimulation and Avatar.
His study looks at the relationship between Motor imagery and topics such as Neurorehabilitation, which overlap with Feature extraction.
His work on Wakefulness as part of his general Electroencephalography study is frequently connected to State, thereby bridging the divide between different branches of science.
Between 2017 and 2021, his most popular works were:
- A New Method to Generate Artificial Frames Using the Empirical Mode Decomposition for an EEG-Based Motor Imagery BCI. (19 citations)
- Real-time detection and discrimination of visual perception using electrocorticographic signals. (15 citations)
- A quantitative method for evaluating cortical responses to electrical stimulation (14 citations)
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