Sammenlign metoder

	BCI Motorisk Forestilling	Common Spatial Pattern	Muskelsynergieanalyse
Fagområde	Biomekanik	Biomekanik	Biomekanik
Familie	Process / pipeline	Process / pipeline	Process / pipeline
Oprindelsesår	1999	2000	1999
Ophavsperson	Gert Pfurtscheller	Herbert Ramoser	Marc Tresch
Type	Neural signal processing and decoding pipeline	Spatial filtering and feature extraction	Dimensionality reduction and pattern extraction
Oprindelig kilde	Pfurtscheller, G., & Neuper, C. (1999). Motor imagery and direct brain-computer communication. Proceedings of the IEEE, 89(7), 1123-1134.	Ramoser, H., Mueller-Gerking, J., & Pfurtscheller, G. (2000). Optimal spatial filtering of single trial EEG during imagined hand movement. IEEE Transactions on Rehabilitation Engineering, 8(4), 441-446.	Tresch, M. C., Saltiel, P., Bizzi, E., & Bizzi, E. (1999). The construction of movement by the spinal cord. Nature Neuroscience, 2(2), 162-167.
Aliasser	Motor imagery BCI, MI-BCI, EEG motor decoding	CSP, Spatial filtering, CSP decomposition	Motor synergy, Synergy extraction, Motor primitives
Relaterede	3	3	3
Resumé	Brain-computer interface (BCI) using motor imagery decodes the intent to move from brain activity (typically EEG) recorded while subjects imagine movement without actual muscle contraction. Pioneered by Gert Pfurtscheller and colleagues, motor imagery BCIs enable communication and control for paralyzed patients and enhance motor learning in rehabilitation.	Common Spatial Pattern (CSP) is a spatial filtering technique that identifies electrode combinations that maximize the variance difference between two classes of EEG activity, typically used in brain-computer interfaces to enhance motor imagery discrimination. Introduced by Ramoser and colleagues in 2000, CSP has become a standard feature extraction method in BCI research.	Muscle synergy analysis decomposes complex motor behavior into a small set of coactivated muscle groups (synergies or motor primitives). Pioneered by Marc Tresch and colleagues studying frog motor control, this approach reveals how the nervous system simplifies the control of many muscles by organizing them into task-relevant combinations.