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Parkinson’s disease presents significant challenges in diagnosis and monitoring due to its progressive nature and complex symptomatology. This preliminary study introduces a novel approach using surface electromyography (sEMG) to objectively assess PD severity, focusing on the biceps brachii muscle. SEMG data was analyzed from five PD patients (age 72–84) and five healthy controls (age 67–80) using the Myoware Muscle Sensor. Key parameters such as Root Mean Square (RMS), Median Frequency (MDF), Mean Frequency, and Sample Entropy (SampEn) were extracted. Results indicate notable neuromuscular differences, particularly in variance and mean frequency during sustained contractions, with the classification model achieving accuracies up to 83%. Despite the small sample size, findings suggest sEMG’s potential as a non-invasive tool for PD severity assessment. Future research with larger cohorts is essential to validate these findings and enhance the methodology, aiming for integration into clinical protocols to improve PD evaluation and personalized therapy.

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Preliminary Surface EMG Profiling in Parkinson’s Disease: A Foundation for Objective Disease Severity Assessment

  • 会议论文

  • 发表日期：

    2025年

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  • Barbara Szyca,
  • Michalina Razik,
  • Liwia Florkiewicz,
  • Anna Prus,
  • Hubert Lis,
  • Kinga Grzęda,
  • Weronika Bajko,
  • Helena Kamieniecka,
  • Weronika Matwiejuk,
  • Inga Rozumowicz,
  • Wiktoria Ziembakowska,
  • Daniel Cieślak,
  • Mariusz Kaczmarek

摘要

Parkinson’s disease presents significant challenges in diagnosis and monitoring due to its progressive nature and complex symptomatology. This preliminary study introduces a novel approach using surface electromyography (sEMG) to objectively assess PD severity, focusing on the biceps brachii muscle. SEMG data was analyzed from five PD patients (age 72–84) and five healthy controls (age 67–80) using the Myoware Muscle Sensor. Key parameters such as Root Mean Square (RMS), Median Frequency (MDF), Mean Frequency, and Sample Entropy (SampEn) were extracted. Results indicate notable neuromuscular differences, particularly in variance and mean frequency during sustained contractions, with the classification model achieving accuracies up to 83%. Despite the small sample size, findings suggest sEMG’s potential as a non-invasive tool for PD severity assessment. Future research with larger cohorts is essential to validate these findings and enhance the methodology, aiming for integration into clinical protocols to improve PD evaluation and personalized therapy.