AIM: To investigate the association between subjective spasticity ratings and objective spasticity measurement using a new tool for spasticity assessment, that is long-term surface electromyography (sEMG) 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, vastus lateralis, adductor group and semitendinosus of 14 complete spinal-cord-injured patients, in whom voluntary muscle contraction was absent, was recorded continuously during daily activities. Synchronously, subjects stored their activities in a diary and scored their experienced level of spasticity on the 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 a 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, that is 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 that other factors such as 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.