Hiroki Ora
Papers
2
Total Citations
24
H-Index
2
About
Hiroki Ora is a researcher at the forefront of assistive robotics and brain-computer interfaces (BCIs), with a focus on improving human motor function and neural decoding. His work spans two key areas: wearable robotic systems for gait rehabilitation and advanced machine learning for neural signal classification. In a notable 2020 study, Ora investigated the use of synchronized tactile stimulation via a wearable robot to assist gait in patients with Parkinson’s disease, demonstrating immediate after-effects of intervention in participants with modified Hoehn-Yahr scores of 1–3. This work, which has garnered 12 citations, highlights his commitment to translating robotic assistance into clinical benefits. Concurrently, Ora has advanced BCI technology by improving error-related potential (ErrP) classification—a critical component for detecting user intent in real-time systems. By integrating generative adversarial networks (GANs) with deep convolutional neural networks, he addressed the limitations of existing decoding methods, achieving enhanced classification accuracy. This 2020 paper also holds 12 citations, underscoring its impact on the BCI community. Ora’s dual contributions to wearable robotics and neural signal processing position him as an innovator bridging engineering and neuroscience, with clear implications for rehabilitation and human-machine interaction.
Research Focus
Key Achievements
Top Papers
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