Poster Presentation Australian and New Zealand Stroke Organisation Conference 2026

Surface electromyography as an objective biomarker of balance and motor impairment after stroke (#144)

Cassio V. Ruas 1 2 3 4 , Camila D. Lima 1 2 5 6 , Bruna M. Carlos 1 2 , Jayne Silvestre 1 2 , Alexandre F. Brandão 1 7 , Gabriel Trajano 3 , Gabriela Castellano 1 2
  1. Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), Universidade Estadual de Campinas (UNICAMP), Campinas, SP, Brazil
  2. Institute of Physics Gleb Wataghin, Universidade Estadual de Campinas (UNICAMP), Campinas, SP, Brazil
  3. School of Exercise and Nutrition Sciences, Queensland University of Technology (QUT), Brisbane, WA, Australia
  4. School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
  5. Centre for Sensorimotor Performance, School of Human Movement and Nutrition Sciences, The University of Queensland, Brisbane, QLD, Australia
  6. Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
  7. Polytechnic School, Pontifical Catholic University of Campinas (PUC-Campinas), Campinas, SP, Brazil

Background/aims: Abnormal levels of electromyographic activity (EMG) are often observed in muscles affected by stroke, likely reflecting altered motor unit recruitment and discharge patterns (1, 2). However, post-stroke clinical assessments, such as Fugl-Meyer (FM) motor scales and Berg Balance Scale (BBS), may not sensitively detect neuromuscular alterations (3).This study examined the influence of EMG on outcomes assessed by commonly used post-stroke clinical scales.

Methods: Sixteen individuals with chronic stroke (59.0±13.9 years; 28.3±23.1 months post-stroke) were assessed using upper-extremity (UEFM), lower-extremity (LEFM) and total FM (TFM), as well as BBS scores. Surface EMG (root mean square over 250 ms) was recorded from the paretic deltoid and rectus femoris muscles during shoulder abduction and flexion, and hip flexion and knee extension maximal voluntary isometric contractions using a Neuro-EMG-Micro-4 system. Relationships between clinical and EMG variables were examined by correlation and regression analyses.

Results: TFM correlated with shoulder abduction (r=0.76, p<0.001), shoulder flexion (r=0.66, p=0.006), hip flexion (r=0.51, p=0.04), and knee extension EMG (r=0.82, p<0.001). LEFM correlated with knee extension EMG (r=0.74; p<0.001), whereas UEFM correlated with shoulder abduction (r=0.78, p<0.001) and shoulder flexion EMG (r=0.64, p=0.008). BBS correlated with knee extension EMG only (r=0.56, p=0.03).

Conclusion: Shoulder abduction and flexion EMG explained 52% of UEFM, knee extension EMG explained 45% of LEFM and 14% of BBS, and all EMG measures explained 81% of TFM variances. As clinical scales do not directly assess impaired neural drive, EMG may serve as an objective biomarker for quantifying neuromuscular dysfunction and monitoring impairment after stroke.

 

  1. Hu, X., Suresh, A. K., Rymer, W. Z., & Suresh, N. L. (2015). Assessing altered motor unit recruitment patterns in paretic muscles of stroke survivors using surface electromyography. Journal of neural engineering, 12(6), 066001. https://doi.org/10.1088/1741-2560/12/6/066001
  2. Son, J., & Rymer, W. Z. (2020). Effects of Changes in Ankle Joint Angle on the Relation Between Plantarflexion Torque and EMG Magnitude in Major Plantar Flexors of Male Chronic Stroke Survivors. Frontiers in neurology, 11, 224. https://doi.org/10.3389/fneur.2020.00224
  3. Ruas, C. V., Carlos, B. M., Feitosa, S., Silva, M. V., Vazquez, P., Pontes, L. L., Silvestre, J., Almeida, S. R. M., Brandão, A. F., & Castellano, G. (2025). The Effects of Transcranial Direct Current Stimulation During Extended Reality Exercises for Cortical, Neuromuscular, and Clinical Recovery of Stroke Survivors. Neural plasticity, 2025, 5688648. https://doi.org/10.1155/np/5688648