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Peer-reviewedCC BY-NC-ND 4.0Scientific Data

Compound muscle action potential scan dataset in adults with spinal cord injury and healthy controls

  • Junjun Chen1
  • Peipei Xu2
  • Maoqi Chen1
  • Zhiyuan Lu1,3
  • Xiaoyan Li4
  • Argyrios Stampas5
  • Ya Zong2
  • Ping Zhou1,3
5 affiliations
  1. 1School of Rehabilitation Sciences and Engineering, University of Health and Rehabilitation Sciences, Qingdao, China
  2. 2Department of Rehabilitation Medicine, Shanghai Jiao Tong University Affiliated Ruijin Hospital, Shanghai, China
  3. 3Department of Rehabilitation Medicine, Qingdao Central Hospital, University of Health and Rehabilitation Sciences, Qingdao, China
  4. 4Fischell Department of Bioengineering, University of Maryland at College Park, College Park, Maryland USA
  5. 5Department of Physical Medicine and Rehabilitation, University of Texas Health Science Center at Houston, Houston, Texas USA
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Abstract

Certain neurological conditions, such as amyotrophic lateral sclerosis (ALS) and spinal cord injury (SCI), result in motor unit loss in muscles. The stimulus-evoked compound muscle action potential (CMAP) scan captures comprehensive information on motor unit recruitment that enables rapid and non-invasive assessment of motor unit status. However, few publicly available CMAP scan datasets exist to support research on motor unit number estimation (MUNE). To address this gap, we collected CMAP scan data from the first dorsal interosseous (FDI) muscle of 13 individuals with SCI and 13 healthy participants, and established a dedicated CMAP scan dataset. The dataset includes CMAP waveforms evoked by each nerve stimulus from which CMAP scan curve and typical parameters were extracted for direct use. All SCI participants underwent multiple clinical assessments and exhibited a spectrum of impairment severity from mild to severe, resulting in diverse CMAP features. We anticipate that this dataset will facilitate the development of advanced CMAP scan-based assessment techniques and aid in the investigation of neuromuscular impairment.

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Cite

BibTeXRIS
BibTeX
@article{chen2026compound,
  title = {{Compound muscle action potential scan dataset in adults with spinal cord injury and healthy controls}},
  author = {Junjun Chen and Peipei Xu and Maoqi Chen and Zhiyuan Lu and Xiaoyan Li and Argyrios Stampas and Ya Zong and Ping Zhou},
  journal = {Scientific Data},
  year = {2026},
  month = jul,
  doi = {10.1038/s41597-026-07864-2},
  url = {https://doi.org/10.1038/s41597-026-07864-2},
  note = {CC BY-NC-ND 4.0},
}
RIS
TY  - JOUR
TI  - Compound muscle action potential scan dataset in adults with spinal cord injury and healthy controls
AU  - Junjun Chen
AU  - Peipei Xu
AU  - Maoqi Chen
AU  - Zhiyuan Lu
AU  - Xiaoyan Li
AU  - Argyrios Stampas
AU  - Ya Zong
AU  - Ping Zhou
PY  - 2026
DA  - 2026/07/11
JO  - Scientific Data
DO  - 10.1038/s41597-026-07864-2
UR  - https://doi.org/10.1038/s41597-026-07864-2
AB  - Certain neurological conditions, such as amyotrophic lateral sclerosis (ALS) and spinal cord injury (SCI), result in motor unit loss in muscles. The stimulus-evoked compound muscle action potential (CMAP) scan captures comprehensive information on motor unit recruitment that enables rapid and non-invasive assessment of motor unit status. However, few publicly available CMAP scan datasets exist to support research on motor unit number estimation (MUNE). To address this gap, we collected CMAP scan data from the first dorsal interosseous (FDI) muscle of 13 individuals with SCI and 13 healthy participants, and established a dedicated CMAP scan dataset. The dataset includes CMAP waveforms evoked by each nerve stimulus from which CMAP scan curve and typical parameters were extracted for direct use. All SCI participants underwent multiple clinical assessments and exhibited a spectrum of impairment severity from mild to severe, resulting in diverse CMAP features. We anticipate that this dataset will facilitate the development of advanced CMAP scan-based assessment techniques and aid in the investigation of neuromuscular impairment.
SN  - 2052-4463
ER  -