Vertaile menetelmiä

	BCI-liikemielikuvitus	Yleinen spatiaalinen kuvio	Lihassynnergia-analyysi
Tieteenala	Biomekaniikka	Biomekaniikka	Biomekaniikka
Menetelmäperhe	Process / pipeline	Process / pipeline	Process / pipeline
Syntyvuosi	1999	2000	1999
Kehittäjä	Gert Pfurtscheller	Herbert Ramoser	Marc Tresch
Tyyppi	Neural signal processing and decoding pipeline	Spatial filtering and feature extraction	Dimensionality reduction and pattern extraction
Alkuperäislähde	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.
Rinnakkaisnimet	Motor imagery BCI, MI-BCI, EEG motor decoding	CSP, Spatial filtering, CSP decomposition	Motor synergy, Synergy extraction, Motor primitives
Liittyvät	3	3	3
Tiivistelmä	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.