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| 동적 시간 왜곡(DTW) 보행 분석× | EMG 엔벨로프× | |
|---|---|---|
| 분야 | 생체역학 | 생체역학 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1978 | 1999 |
| 창시자≠ | Sakoe and Chiba | Roberto Merletti |
| 유형≠ | Sequence alignment and pattern matching | Digital signal processing 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. DOI ↗ | 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. link ↗ |
| 별칭 | DTW, Gait pattern matching, Temporal gait comparison | EMG linear envelope, RMS envelope, Activation envelope |
| 관련 | 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. |
| ScholarGate데이터셋 ↗ |
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