Compara mètodes

	Envelopa de l'EMG	Anàlisi de sinergies musculars	Detecció QRS Pan-Tompkins
Camp	Biomecànica	Biomecànica	Biomecànica
Família	Process / pipeline	Process / pipeline	Process / pipeline
Any d'origen	1999	1999	1985
Autor original	Roberto Merletti	Marc Tresch	Jiapu Pan
Tipus	Digital signal processing pipeline	Dimensionality reduction and pattern extraction	Digital signal processing pipeline
Font seminal	Phinyomark, A., Quaine, F., Charbonnier, S., & Serviere, C. (2012). Robust EMG feature extraction in the whitespace. IEEE Transactions on Biomedical Engineering, 59(5), 1505-1517.	Tresch, M. C., Saltiel, P., Bizzi, E., & Bizzi, E. (1999). The construction of movement by the spinal cord. Nature Neuroscience, 2(2), 162-167.	Pan, J., & Tompkins, W. J. (1985). A real-time QRS detection algorithm. IEEE Transactions on Biomedical Engineering, BME-32(3), 230-236.
Àlies	EMG linear envelope, RMS envelope, Activation envelope	Motor synergy, Synergy extraction, Motor primitives	QRS detection, R-peak detection, Heartbeat detection
Relacionats	3	3	3
Resum	Electromyography (EMG) envelope analysis extracts the amplitude modulation of muscle electrical activity to quantify muscle activation over time. By filtering and demodulating the raw EMG signal, practitioners obtain a smoothed activation profile that reflects when and how intensely a muscle is contracting during movement or fatigue.	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.	The Pan-Tompkins algorithm is a real-time QRS detection method for electrocardiograms (ECGs) that identifies the R-peaks (ventricular depolarization) and QRS complexes from continuous cardiac waveforms. Published by Jiapu Pan and Willis Tompkins in 1985, it remains a standard reference for ECG processing and is widely implemented in clinical monitoring systems.