Narjes Meselmani
Papers
1
Total Citations
7
H-Index
1
About
Narjes Meselmani is a researcher at the forefront of biomedical engineering and human-robot interaction, with a focused expertise in electromyography (EMG) signal processing and adaptive control systems. Her most cited work, "Pattern recognition of EMG signals: Towards adaptive control of robotic arms" (2016, 7 citations), addresses a critical challenge in assistive technology: restoring dexterous limb function for individuals with amputations or paralysis. Meselmani's key contribution lies in developing pattern recognition algorithms that decode muscle electrical activity into precise control commands for robotic prosthetics. By enabling adaptive, real-time manipulation of robotic arms, her research bridges the gap between biological signals and mechanical actuation, offering a pathway to more intuitive and responsive assistive devices. This work not only advances the field of neural-machine interfaces but also holds profound implications for improving quality of life for those with limb loss. Meselmani’s innovative approach to EMG-based control systems underscores her commitment to translating complex signal processing into practical, life-changing technologies. Her contributions continue to inspire further exploration in adaptive prosthetics and human-robot collaboration.
Research Focus
Key Achievements
Top Papers
- 1