Epileptic seizures result from abnormal brain activity and involve both electrical and biomechanical signals. Accurate seizure classification is essential for clinical decision-making, yet conventional diagnostic methods, including self-reports and video monitoring, are limited in detecting seizure types. To overcome these limitations, this study investigates a multimodal approach combining electroencephalography (EEG), surface electromyography (sEMG), and inertial measurement unit (IMU) sensors. A synchronized compact wireless system was developed to capture the modalities, ensuring precise...