Evaluating the Effectiveness and Safety of the Electroencephalogram-Based Brain-Machine Interface Rehabilitation System for Patients With Severe Hemiparetic Stroke: Protocol for a Randomized Controlled Trial (BEST-BRAIN Trial)

Journals

1. Hijikata N, Kawakami M, Ishii R, Tsuzuki K, Nakamura T, Okuyama K, Liu M. Item Difficulty of Fugl-Meyer Assessment for Upper Extremity in Persons With Chronic Stroke With Moderate-to-Severe Upper Limb Impairment. Frontiers in Neurology 2020;11 View
2. Suda M, Kawakami M, Okuyama K, Ishii R, Oshima O, Hijikata N, Nakamura T, Oka A, Kondo K, Liu M. Validity and Reliability of the Semmes-Weinstein Monofilament Test and the Thumb Localizing Test in Patients With Stroke. Frontiers in Neurology 2021;11 View
3. Sasaki K, Fujishige Y, Kikuchi Y, Odagaki M. A Transcranial Magnetic Stimulation Trigger System for Suppressing Motor-Evoked Potential Fluctuation Using Electroencephalogram Coherence Analysis: Algorithm Development and Validation Study. JMIR Biomedical Engineering 2021;6(2):e28902 View
4. Liu M, Ushiba J. Brain–machine Interface (BMI)-based Neurorehabilitation for Post-stroke Upper Limb Paralysis. The Keio Journal of Medicine 2022;71(4):82 View
5. Chen S, Shu X, Wang H, Ding L, Fu J, Jia J. The Differences Between Motor Attempt and Motor Imagery in Brain-Computer Interface Accuracy and Event-Related Desynchronization of Patients With Hemiplegia. Frontiers in Neurorobotics 2021;15 View
6. Nishida D. Gait Improvement on Brain Plasticity Change. The Japanese Journal of Rehabilitation Medicine 2023;60(9):785 View
7. Höhler C, Trigili E, Astarita D, Hermsdörfer J, Jahn K, Krewer C. The efficacy of hybrid neuroprostheses in the rehabilitation of upper limb impairment after stroke, a narrative and systematic review with a meta‐analysis. Artificial Organs 2023 View

Books/Policy Documents

1. Lim J, Lin D, Sohn W, McCrimmon C, Wang P, Nenadic Z, Do A. Neurorehabilitation Technology. View