So sánh phương pháp

	Phân tích kiểu sợi MHC	Ước lượng 1RM
Lĩnh vực	Khoa học thể thao	Khoa học thể thao
Họ	Hypothesis test	Hypothesis test
Năm ra đời	1994	1993
Người khởi xướng	Reggiani & Schiaffino	Matt Brzycki
Loại	muscle biopsy analysis	submaximal prediction
Công trình gốc	Bottinelli, R., & Reggiani, C. (2000). Human skeletal muscle fibres: acting role of fibre type in resistance training. Journal of Sports Medicine and Physical Fitness, 40(2), 166-177.	Brzycki, M. (1993). Strength testing: predicting a one-rep max from reps-to-fatigue. Journal of Physical Education, Recreation and Dance, 64(1), 88-90.
Tên gọi khác	fiber typing, myosin isoforms, muscle fiber classification	one-rep max prediction, estimated 1RM, strength prediction, maximal strength assessment
Liên quan	3	5
Tóm tắt	MHC fiber typing is laboratory analysis of muscle fiber composition, quantifying the percentage of slow-twitch (Type I) and fast-twitch (Type II) fibers in a muscle sample. Based on myosin heavy chain (MHC) isoform expression, fibers are classified into Type I (slow-twitch, oxidative), Type IIa (fast-twitch, oxidative-glycolytic), and Type IIx/IId (fast-twitch, glycolytic). Introduced by Bottinelli and colleagues (1994), MHC typing requires muscle biopsy and biochemical analysis. Fiber type composition is partially genetic but trainable; endurance training promotes Type II-to-IIa conversion, while power training promotes Type I-to-IIa transitions in some contexts. Understanding fiber composition informs training prescription and explains performance predispositions.	One-repetition maximum (1RM) estimation is a method to predict an athlete's maximum strength in a given lift without performing an actual maximal single repetition. Developed systematically by Matt Brzycki (1993) and refined by numerous researchers, 1RM estimation uses submaximal loads and repetition performance to extrapolate a strength ceiling. Rather than exposing untrained individuals, older adults, or post-injury athletes to the stress and injury risk of true 1RM testing, estimation provides a safer, time-efficient alternative. Multiple prediction equations exist, with varying accuracy depending on population and lift type.