Confronta i metodi

	Analisi del Gesto tramite DTW	Inviluppo EMG	Dinamica Inversa
Campo	Biomeccanica	Biomeccanica	Biomeccanica
Famiglia	Process / pipeline	Process / pipeline	Process / pipeline
Anno di origine	1978	1999	1990
Ideatore	Sakoe and Chiba	Roberto Merletti	David Winter
Tipo	Sequence alignment and pattern matching	Digital signal processing pipeline	Computational analysis pipeline
Fonte seminale	Sakoe, H., & Chiba, S. (1978). Dynamic programming algorithm optimization for spoken word recognition. IEEE Transactions on Acoustics, Speech, and Signal Processing, 26(1), 43-49.	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.	Winter, D. A. (1990). Biomechanics and Motor Control of Human Movement. Wiley-Interscience.
Alias	DTW, Gait pattern matching, Temporal gait comparison	EMG linear envelope, RMS envelope, Activation envelope	Inverse problem, Biomechanical inverse dynamics
Correlati	3	3	3
Sintesi	Dynamic Time Warping (DTW) is a sequence alignment algorithm that measures similarity between time series of different lengths by allowing flexible temporal matching. Applied to gait analysis, DTW enables comparison of walking patterns across subjects and conditions despite variations in cadence or stride length.	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.	Inverse dynamics is a biomechanical analysis technique that estimates the forces and moments acting on joints during movement by working backward from observed motion and ground reaction forces. Introduced by David Winter in the early 1990s, it is fundamental to understanding how muscles and joints generate and control human motion.