방법 비교

	동적 시간 왜곡(DTW) 보행 분석	EMG 엔벨로프	역동학
분야	생체역학	생체역학	생체역학
계열	Process / pipeline	Process / pipeline	Process / pipeline
기원 연도	1978	1999	1990
창시자	Sakoe and Chiba	Roberto Merletti	David Winter
유형	Sequence alignment and pattern matching	Digital signal processing pipeline	Computational analysis pipeline
원전	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.
별칭	DTW, Gait pattern matching, Temporal gait comparison	EMG linear envelope, RMS envelope, Activation envelope	Inverse problem, Biomechanical inverse dynamics
관련	3	3	3
요약	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.