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About

Anna Choo is pioneering the integration of brain-computer interfaces (BCIs) with soft robotics to restore motor function in chronic stroke survivors. Her research centers on multimodal BCIs that fuse electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) signals, leveraging both electrical and hemodynamic brain activity to achieve more robust, personalized control of assistive devices. Choo’s most cited work, “A Personalized Multimodal BCI–Soft Robotics System for Rehabilitating Upper Limb Function in Chronic Stroke Patients” (2025, 9 citations), demonstrates a closed-loop system where EEG-fNIRS decoding drives a soft robotic glove, enabling task-specific hand rehabilitation. A companion paper (2 citations) further refines this approach by integrating data-driven feature selection and incremental transcranial electrical stimulation to enhance neural engagement. Choo’s contributions are notable for their translational focus: by combining real-time neural decoding with adaptive, patient-specific stimulation protocols, she addresses a critical gap in post-stroke motor recovery. Her work has already influenced the design of next-generation neurorehabilitation platforms, and her emphasis on multimodal, personalized BCIs positions her as a rising leader in assistive neurotechnology.