Background: Sensorimotor oscillations in the mu (8–12 Hz) and beta (13–30 Hz) bands typically show event-related desynchronization (ERD) during movement execution, whereas action observation usually produces weaker and less consistent suppression. In contrast, the role of slower rhythms (delta–theta) and their interaction with faster sensorimotor activity remains less well characterized, especially in exoskeleton-assisted movement. Methods: We recorded 32-channel EEG in 20 right-handed healthy participants during unimanual and bimanual hand movements under three conditions: active execution, exoskeleton-assisted execution, and observation. Spectral analyses included band-limited power changes, a slow/fast power ratio index (2–7 Hz/8–30 Hz), and hemispheric asymmetry measures. Results: Active execution reproduced the expected mu/beta ERD pattern, with only modest lateralization. By contrast, exoskeleton-assisted execution showed a different spectral profile, characterized by sustained delta–theta enhancement, a significantly increased slow/fast ratio throughout the movement, and a more bilateral recruitment pattern in fast frequencies. Observation produced weaker and delayed modulations, without clear lateralization. Across conditions, the slow/fast ratio separated motor states not only in amplitude but also through different temporal profiles, with earlier increases in ACT/EXO and a later peak during observation. In addition, topographic analysis of slow oscillatory activity during assisted bimanual coordination revealed a stable hemispheric asymmetry rather than a symmetric bilateral pattern, suggesting a functional hemispheric bias during joint action. Conclusions: Beyond conventional mu/beta ERD/PMBR markers, the balance between slow and fast spectral activity provides a compact description of motor state. Exoskeleton assistance was associated with a specific reorganization of cortical dynamics, combining bilateral recruitment with structured hemispheric asymmetry in slow rhythms, a pattern not present during voluntary action or observation. These findings support the use of simple EEG spectral markers for the study of human–machine interaction and may be relevant for robotic rehabilitation and brain–computer interface applications.