Stroke is the leading cause of disability worldwide, and nearly 80% of stroke survivors suffer from upper-limb hemiparesis. Myoelectric exoskeletons can restore dexterity and independence to stroke survivors with upper-limb hemiparesis. However, the ability of patients to dexterously control myoelectric exoskeletons is limited by an incomplete understanding of the electromyographic (EMG) hallmarks of hemiparesis, such as muscle weakness and spasticity. Here we show that stroke survivors with upper-limb hemiparesis suffer from delayed voluntary muscle contraction and delayed muscle relaxation. We quantified the time constants of EMG activity associated with initiating and terminating voluntary hand grasps and extensions for both the paretic and non-paretic hands of stroke survivors. We found that the initiation and termination time constants were greater on the paretic side for both hand grasps and hand extensions. Notably, the initiation time constant during hand extension was approximately three times longer for the paretic hand than for the contralateral non-paretic hand (0.618 vs 0.189 s). We also show a positive correlation between the initiation and termination time constants and clinical scores on the Modified Ashworth Scale. The difficulty stroke survivors have in efficiently modulating their EMG presents a challenge for appropriate control of assistive myoelectric devices, such as exoskeletons. This work constitutes an important step towards understanding EMG differences after stroke and how to accommodate these EMG differences in assistive myoelectric devices. Real-time quantitative biofeedback of EMG time constants may also have broad implications for guiding rehabilitation and monitoring patient recovery.Clinical Relevance- After a stroke, muscle activity changes, and these changes make it difficult to use muscle activity to drive assistive and rehabilitative technologies. We identified slower muscle contraction and muscle relaxation as a key difference in muscle activity after a stroke. This quantifiable difference in muscle activity can be used to develop better assistive technologies, guide rehabilitation, and monitor patient recovery.