Differentiating variations in thumb position from recordings of the surface electromyogram in adults performing static grips, a proof of concept study

Alejandra Aranceta-Garza, Bernard Arthur Conway

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9 Citations (Scopus)
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Hand gesture and grip formations are produced by the muscle synergies arising between extrinsic and intrinsic hand muscles and many functional hand movements involve repositioning of the thumb relative to other digits. In this study we explored whether changes in thumb posture in able-body volunteers can be identified and classified from the modulation of forearm muscle surface electromyography (sEMG) alone without reference to activity from the intrinsic musculature. In this proof-of-concept study, our goal was to determine if there is scope to develop prosthetic hand control systems that may incorporate myoelectric thumb-position control.

Healthy volunteers performed a controlled-isometric grip task with their thumb held in four different opposing-postures. Grip force during task performance was maintained at 30% maximal-voluntary force and sEMG signals from the forearm were recorded using 2D high-density sEMG (HD-sEMG arrays). Correlations between sEMG amplitude and root-mean squared estimates with variation in thumb-position were investigated using principal-component analysis and self-organizing feature maps.

Results demonstrate that forearm muscle sEMG patterns possess classifiable parameters that correlate with variations in static thumb position (accuracy of 88.25±0.5% anterior; 91.25±2.5% posterior musculature of the forearm sites). Of importance, this suggests that in transradial amputees, despite the loss of access to the intrinsic muscles that control thumb action, an acceptable level of control over a thumb component within myoelectric devices may be achievable. Accordingly, further work exploring the potential to provide myoelectric control over the thumb within a prosthetic hand is warranted.
Original languageEnglish
Article number123
Number of pages11
JournalFrontiers in Bioengineering and Biotechnology
Publication statusPublished - 22 May 2019


  • grip formation
  • high-density surface electromyography
  • machine learning
  • prosthetics
  • self-organizing feature maps
  • featured maps
  • thumb position control
  • myoelectric prosthetics


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