{
  "abstract": "Surface electromyography (sEMG) has emerged as an impactful tool for controlling advanced prosthetic devices by detecting and recording muscle electrical activity during motion. This study presents a unique technique for recognizing nine distinct classes of finger movements by utilizing the Ninapro database. To address an underexplored domain of upper-limb prosthetic control, this research targets fine-resolution individual finger movements rather than the broad range of hand gestures. A custom-made one-dimensional convolutional neural network (1D–CNN) was developed and validated using a within-subject evaluation strategy and signals. The proposed model achieved an overall classification accuracy of 90.1%. An in-depth sensitivity/specificity analysis for each finger movement class was administered to gain key insights into current recognition capabilities. The findings presented in this study demonstrate the viability of fine-resolution finger-movement recognition, offering foundational insights that may inform the future development and refinement of control systems in the prosthetic field.",
  "abstract_shown": true,
  "affiliations": [
    "Biomedical Systems and Informatics Engineering Department, Yarmouk University, Irbid, Jordan.",
    "Hunter Medical Research Institute, Mark Hughes Foundation Centre for Brain Cancer Research, University of Newcastle, Newcastle, NSW, Australia.",
    "The Institute of Biomedical Technology, King Hussein Medical Center, Royal Jordanian Medical Service, Amman, Jordan.",
    "The Department of Biomedical Engineering, Jordan University of Science and Technology, Irbid, Jordan.",
    "Faculty of Electrical Engineering & Technology, University of Malaysia Perlis, UniCITI Alam Campus, Arau, Perlis, Malaysia.",
    "Advanced Computing (AdvCOMP), Centre of Excellence, Universiti Malaysia Perlis (UniMAP), Arau, Perlis, Malaysia.",
    "Department of Diagnostic Radiology, Faculty of Medicine, Jordan University of Science and Technology, Irbid, Jordan."
  ],
  "article_type": "Research Article",
  "arxiv": null,
  "author_total": 6,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Hiam Alquran",
      "orcid": "0000-0002-2966-6442"
    },
    {
      "affs": [
        1
      ],
      "name": "Hassan Alawneh"
    },
    {
      "affs": [
        2,
        3
      ],
      "name": "Mohammed Alsalatie"
    },
    {
      "affs": [
        0
      ],
      "name": "Ateka Khader"
    },
    {
      "affs": [
        4,
        5
      ],
      "name": "Wan Azani Mustafa"
    },
    {
      "affs": [
        6
      ],
      "name": "Khaled Zayed Alawneh"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/97735k2d1tnwn.bib",
  "cited_by": 0,
  "doi": "10.1371/journal.pone.0361050",
  "fulltext_url": "https://europepmc.org/articles/PMC13690248",
  "id": "97735k2d1tnwn",
  "issns": [
    "1932-6203"
  ],
  "landing_url": "https://doi.org/10.1371/journal.pone.0361050",
  "language": "eng",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2204|Muscle activation and electromyography studies"
    ],
    [
      "plos",
      "/Biology and life sciences/Anatomy/Body limbs/Arms/Hands"
    ],
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      "plos",
      "/Biology and life sciences/Anatomy/Body limbs/Arms/Hands/Fingers"
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      "/Biology and life sciences/Bioengineering/Biotechnology/Medical devices and equipment/Assistive technologies/Prosthetics"
    ],
    [
      "plos",
      "/Biology and life sciences/Biomechanics/Musculoskeletal mechanics"
    ],
    [
      "plos",
      "/Biology and life sciences/Physiology/Muscle physiology/Musculoskeletal mechanics"
    ],
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      "plos",
      "/Biology and life sciences/Psychology/Behavior/Nonverbal communication"
    ],
    [
      "plos",
      "/Engineering and technology/Bioengineering/Biotechnology/Medical devices and equipment/Assistive technologies/Prosthetics"
    ],
    [
      "plos",
      "/Engineering and technology/Signal processing/Signal filtering"
    ],
    [
      "plos",
      "/Medicine and health sciences/Anatomy/Body limbs/Arms/Hands"
    ],
    [
      "plos",
      "/Medicine and health sciences/Anatomy/Body limbs/Arms/Hands/Fingers"
    ],
    [
      "plos",
      "/Medicine and health sciences/Anatomy/Body limbs/Arms/Hands/Thumbs"
    ],
    [
      "plos",
      "/Medicine and health sciences/Medical devices and equipment/Assistive technologies/Prosthetics"
    ],
    [
      "plos",
      "/Research and analysis methods/Bioassays and physiological analysis/Electrophysiological techniques/Muscle electrophysiology/Electromyography"
    ],
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      "plos",
      "/Social sciences/Psychology/Behavior/Nonverbal communication"
    ]
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  "pdf_url": "https://europepmc.org/articles/PMC13690248?pdf=render",
  "pmcid": "PMC13690248",
  "pmid": "42911971",
  "published": "2026-10-22",
  "publisher": "Public Library of Science",
  "ris": "https://research.draconitic.com/paper/97735k2d1tnwn.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:23Z",
      "native_id": "10.1371/journal.pone.0361050",
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      "url": "https://doi.org/10.1371/journal.pone.0361050"
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    {
      "first_seen": "2026-10-30T12:20:10Z",
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  "subjects": [
    {
      "field": "medicine",
      "origin": "plos:anatomy",
      "subfield": "physiology"
    }
  ],
  "title": "Deep learning–driven fine-resolution finger movement recognition from surface EMG signals",
  "title_text": "Deep learning–driven fine-resolution finger movement recognition from surface EMG signals",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:20:10Z",
  "url": "https://research.draconitic.com/paper/97735k2d1tnwn",
  "venue": "PLOS One",
  "versions": []
}