ArticleJournal of foot and ankle research2023
A classification of the plantar intrinsic foot muscles based on the physiological cross-sectional area and muscle fiber length in healthy young adult males.
Article in Journal of foot and ankle research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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2 citing papers in PubMed, 2 citations in OpenAlex.
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- Classifying Endurance Runners by Kinematics Strengthens Relationships of Muscle-Tendon Unit Function with Running Economy and Performance.Medicine and science in sports and exercise · 2026Article
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6 authors at 1 institution in 1 country.
Funding
Abstract
backgroundPlantar intrinsic foot muscles (PIFMs) are composed of 10 muscles and play an essential role in achieving functional diversity in the foot. Previous studies have identified that the morphological profiles of PIFMs vary between individuals. The morphological profiles of a muscle theoretically reflect its output potentials: the physiological cross-sectional area (PCSA) of a muscle is proportional to its maximum force generation, and the muscle fiber length (FL) is its shortening velocity. This implies that the PCSA and FL may be useful variables for characterizing the functional diversity of the individual PIFM. The purpose of this study was to examine how individual PIFMs can be classified based on their PCSA and FL.
methodsIn 26 healthy young adult males, the muscle volume and muscle length of seven PIFMs (abductor hallucis, ABDH; abductor digiti minimi, ABDM; adductor hallucis oblique head, ADDH-OH; ADDH transverse head, ADDH-TH; flexor digitorum brevis, FDB; flexor hallucis brevis, FHB; quadratus plantae, QP) were measured using magnetic resonance imaging. The PCSA and FL of each of the seven PIFMs were then estimated by combining the data measured from the participants and those of muscle architectural parameters documented from cadavers in previous studies. A total of 182 data samples (26 participants × 7 muscles) were classified into clusters using k-means cluster analysis. The optimal number of clusters was evaluated using the elbow method.
resultsThe data samples of PIFMs were assigned to four clusters with different morphological profiles: ADDH-OH and FHB, characterised by large PCSA and short FL (high force generation and slow shortening velocity potentials); ABDM and FDB, moderate PCSA and moderate FL (moderate force generation and moderate shortening velocity potentials); QP, moderate PCSA and long FL (moderate force generation and rapid shortening velocity potentials); ADDH-TH, small PCSA and moderate FL (low force generation and moderate shortening velocity potentials). ABDH components were assigned equivalently to the first and second clusters.
conclusionsThe approach adopted in this study may provide a novel perspective for interpreting the PIFMs' function based on their maximal force generation and shortening velocity potentials.
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