ArticlePloS one2016
Biomechanical Constraints Underlying Motor Primitives Derived from the Musculoskeletal Anatomy of the Human Arm.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 19 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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Who cites it
19 citing papers in PubMed.
- Humanoid Robotic Loading Enhances Mechanotransduction in Tendon Tissue Engineering.Cyborg and bionic systems (Washington, D.C.) · 2026Article
- Stroke-Related Changes in Tonic and Phasic Muscle Recruitment During Reaching Reveal Pathway-Specific Motor Deficits.bioRxiv : the preprint server for biology · 2025Article
- Control signal dimensionality depends on limb dynamics.PloS one · 2025Article
- Decoding the brain-machine interaction for upper limb assistive technologies: advances and challenges.Frontiers in human neuroscience · 2025Review
- Stroke-Related Changes in Tonic and Phasic Muscle Recruitment During Reaching Reveal Pathway-Specific Motor Deficits.Journal of central nervous system disease · 2025Article
- Differential Impact of Biomechanical Constraints on Control Signal Dimensionality for Gravity Support Versus Propulsion.bioRxiv : the preprint server for biology · 2024Article
- Human arm redundancy: a new approach for the inverse kinematics problem.Royal Society open science · 2024Article
- Muscle anatomy is reflected in the spatial organization of the spinal motoneuron pools.Communications biology · 2024Article
- Essential Tremor accentuates the pattern of tremor-band coherence between upper-limb muscles.Journal of neurophysiology · 2023Article
- Quantifying Performance in Robotic Surgery Training Using Muscle-Based Activity Metrics.... IEEE International Conference on System Engineering and Technology. IEEE International Conference on System Engineering and Technology · 2021Article
- A segmented forearm model of hand pronation-supination approximates joint moments for real time applications.International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering · 2021Article
- Solving musculoskeletal biomechanics with machine learning.PeerJ. Computer science · 2021Article
- Approximating complex musculoskeletal biomechanics using multidimensional autogenerating polynomials.PLoS computational biology · 2020Article
- The effect of wrist posture on extrinsic finger muscle activity during single joint movements.Scientific reports · 2020Article
- Advanced technologies for intuitive control and sensation of prosthetics.Biomedical engineering letters · 2020Review
- A novel method of identifying motor primitives using wavelet decomposition.... International Conference on Wearable and Implantable Body Sensor Networks. International Conference on Wearable and Implantable Body Sensor Networks · 2018Article
- Analytical CPG model driven by limb velocity input generates accurate temporal locomotor dynamics.PeerJ · 2018Article
- Correction: Biomechanical Constraints Underlying Motor Primitives Derived from the Musculoskeletal Anatomy of the Human Arm.PloS one · 2018Article
- Gravitational and Dynamic Components of Muscle Torque Underlie Tonic and Phasic Muscle Activity during Goal-Directed Reaching.Frontiers in human neuroscience · 2017Article
Corrections and comments
- Erratum issued
Authors and funding
4 authors.
Funding
Abstract
Neural control of movement can only be realized though the interaction between the mechanical properties of the limb and the environment. Thus, a fundamental question is whether anatomy has evolved to simplify neural control by shaping these interactions in a beneficial way. This inductive data-driven study analyzed the patterns of muscle actions across multiple joints using the musculoskeletal model of the human upper limb. This model was used to calculate muscle lengths across the full range of motion of the arm and examined the correlations between these values between all pairs of muscles. Musculoskeletal coupling was quantified using hierarchical clustering analysis. Muscle lengths between multiple pairs of muscles across multiple postures were highly correlated. These correlations broadly formed two proximal and distal groups, where proximal muscles of the arm were correlated with each other and distal muscles of the arm and hand were correlated with each other, but not between groups. Using hierarchical clustering, between 11 and 14 reliable muscle groups were identified. This shows that musculoskeletal anatomy does indeed shape the mechanical interactions by grouping muscles into functional clusters that generally match the functional repertoire of the human arm. Together, these results support the idea that the structure of the musculoskeletal system is tuned to solve movement complexity problem by reducing the dimensionality of available solutions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.