Aim: To investigate the association between subjective spasticity ratings and objective spasticity measurement using a new tool for spasticity assessment, i.e. long-term sEMG (surface electromyography) recordings during daily activities. For monitoring, processing and analysis of this long-term sEMG data, a muscle activity detection algorithm was developed.
Method: sEMG of the Rectus Femoris (RF), Vastus Lateralis (VL), Adductor group (AD), and Semitendinosus (ST) of fourteen complete spinal cord injured patients, in whom voluntary muscle contraction was absent, was recorded continuously during activities of daily living. Synchronously, subjects stored their activities in a diary and scored their experienced level of spasticity on a Visual Analogue Scale (VAS) for that particular activity. sEMG data were analysed using a high quality burst detection algorithm that was developed and validated within this study. Derived sEMG parameters were clustered using Principal Component Analysis (PCA) and used in linear mixed model analysis to study their association with VAS.
Results: VAS scores appeared significantly associated with the PCA components representing the number and the duration of bursts, but not burst amplitude. Furthermore, VAS scores were associated with the activity performed. The percentage explained variance was however low, i.e. 27 - 35%.
Conclusions: Patient ratings of the level of spasticity appear poorly associated with spasticity in terms of involuntary muscle activity assessed with long-term sEMG recordings. It is likely to assume that other factors like pain and cognitions are also incorporated in these patient ratings. Clinicians are therefore strongly advised to perform complementary objective assessments using long-term sEMG recordings.