Arpa Suwannarat
Papers
1
Total Citations
47
H-Index
1
About
Arpa Suwannarat has made impactful contributions to the field of brain-computer interfaces (BCIs) and neurorehabilitation, with a particular focus on EEG-based motor imagery systems for stroke recovery. Her most cited work, "Comparison of EEG measurement of upper limb movement in motor imagery training system" (2018, 47 citations), provides critical insights into how EEG signals can be effectively harnessed to decode upper limb motor intentions, advancing the design of standalone MI training systems and rehabilitation robotics. This research bridges fundamental neuroscience with practical clinical applications, offering a foundation for more intuitive and accessible stroke therapies. By systematically comparing EEG measurement techniques, Suwannarat’s work helps optimize signal processing and classification, directly improving the reliability of BCI-driven rehabilitation tools. Her studies are widely referenced by engineers and clinicians developing assistive technologies, underscoring her role in translating neural engineering into real-world patient benefits. For students and researchers, her work exemplifies how rigorous experimental design can drive innovation in neurotechnology, making rehabilitation more adaptive and personalized.
Research Focus
Key Achievements
Top Papers
- 1