Risalatul Latifah
Papers
1
Total Citations
2
H-Index
1
About
Risalatul Latifah’s research lies at the intersection of biomedical engineering and rehabilitation robotics, with a focus on enhancing motor recovery through human-robot interaction. Her most-cited work, “Application of EMG and Force Signals of Elbow Joint on Robot-assisted Arm Training” (2018), demonstrates a pioneering approach to integrating electromyography (EMG) and force sensor signals for real-time control of robotic arm systems. By leveraging these biomechanical signals to detect muscle activity during flexion-extension movements, Latifah’s system offers a non-invasive method to support elbow joint rehabilitation in patients with motor impairments. Though her citation count is modest, her contribution is notable for its practical potential: the fusion of EMG and force data enables more responsive, patient-specific training protocols, bridging the gap between robotic assistance and natural neuromuscular control. This work underscores her commitment to developing accessible, sensor-driven therapies that could improve outcomes for individuals recovering from stroke or injury. Latifah’s research exemplifies how low-cost, signal-based interfaces can advance assistive technology, making her a promising voice in the field of rehabilitation engineering.
Research Focus
Key Achievements
Top Papers
- 1