Introduction: After a stroke, more than 80% of survivors experience common upper limb motor deficits, particularly in distal extremities. The recovery process often involves restoring motor functions in hand. An innovative approach to this involves EMG-driven robotic assistant rehabilitation. By integrating EMG technology with robotics, this method utilizes muscle signals from the patient to control a robotic device, facilitating targeted exercises and promoting neural plasticity for improved hand mobility post-stroke. Enhance motor skills, improve Functionality, and accelerate the rehabilitation process by tailoring the intervention to the individual needs and progression. Methods: A bibliographic exploration covered electronic databases like Google Scholar, PUBMED, and ResearchGate, adhering to PRISMA guidelines. From 236 articles, 45 studies were scrutinized, with 10 meeting the inclusion criteria. Among these, 5 were (RCTs) (4 EMG-driven robotics with NMES, 1 EMG-driven robotics). There was 1 case report and 4 single-group studies (2 EMG-driven robotics and NMES, 2 EMG-driven robotics). Fugl-Meyer Assessment (FMA) and EMG parameters were outcome measures for hand motor function assessment. The Cochrane risk of bias tool was used to evaluate article bias. Result: Significant improvements in FMA and EMG parameters were observed in EMG-driven robotic-assisted rehabilitation. Similar findings were noted in EMG-driven robotic-assisted NMES-assisted rehabilitation. Conclusion: EMG-driven robotics enhance hand function and reduce spasticity, aiding stroke rehabilitation. Implications: Incorporating these technologies improves stroke rehabilitation, enhancing recovery outcomes for individuals with stroke