Towards neuromorphic compression based neural sensing for next-generation wireless implantable brain machine interface by Vivek Mohan, Wee Peng Tay, Arindam Basu

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Efficacy of brain-computer interface training with motor imagery-contingent feedback in improving upper limb function and neuroplasticity among persons with chronic stroke: a doubl... by Myeong Sun Kim, Hyunju Park, Ilho Kwon, Kwang-Ok An, Hayeon Kim, Gyulee Park, Wooseok Hyung, Chang-Hwan Im, Joon-Ho Shin

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Neuronal Multi Unit Activity Processing with Metal Oxide Memristive Devices by Caterina Sbandati, Xiongfei Jiang, Deepika Yadav, Spyros Stathopoulos, Dana Cohen, Alex Serb, Shiwei Wang, Themis Prodromakis

Subjects: “…brain‐machine interface…”
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EEG Channel Selection Using Particle Swarm Optimization for the Classification of Auditory Event-Related Potentials by Alejandro Gonzalez, Isao Nambu, Haruhide Hokari, Yasuhiro Wada

“…Brain-machine interfaces (BMI) rely on the accurate classification of event-related potentials (ERPs) and their performance greatly depends on the appropriate selection of classifier parameters and features from dense-array electroencephalography (EEG) signals. …”
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Hyperchaos on the dynamics of memristive Tabu learning neuron model under influence of electromagnetic radiation: Application in biomedical data privacy by Bertrand Frederick Boui A Boya, Jacques Kengne, Arnaud Nanfak, Sishu Shankar Muni, Jean de Dieu Nkapkop, Germaine Djuidje Kenmoe, Lyudmila Klimentyevna Babenko

“…The insights gained from neural dynamics could pave the way for applications in neuromorphic computing, engineering, and brain-machine interfaces. Based on the complex dynamics of the model, a data privacy of biomedical data has been build and reveals good results, and enable to resist to robust attacks.…”
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Decoding the brain-machine interaction for upper limb assistive technologies: advances and challenges by Sutirtha Ghosh, Rohit Kumar Yadav, Sunaina Soni, Shivangi Giri, Shivangi Giri, Suriya Prakash Muthukrishnan, Lalan Kumar, Lalan Kumar, Shubhendu Bhasin, Sitikantha Roy

“…Advances in assistive technologies, particularly Brain-machine Interfaces (BMIs), highlight the importance of decoding motor intentions and kinematics for effective control. …”
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Chemically Engineered GaN Thin Films for Light‐Stimulated Artificial Synapses by Xiaoqin Yang, Jiawen Lu, Luyu Zhao, Xiaorui Han, Zhongwei Bai, Peiwen Quan, Liangshuai Xie, Liang Li, Haoxuan Sun, Mark Hermann Rummeli, Bingcheng Luo, Hong Gu

“…In recent years, photoelectric neuromorphic devices have garnered significant attention for their potential applications in brain–machine interfaces, intelligent sensing, and neuromorphic computing. …”
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Editorial: Recent applications of noninvasive physiological signals and artificial intelligence by Irma N. Angulo, Eduardo Iáñez, Andres Ubeda

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Improved motor imagery skills after repetitive passive somatosensory stimulation: a parallel-group, pre-registered study by Kyoko Kusano, Masaaki Hayashi, Masaaki Hayashi, Seitaro Iwama, Junichi Ushiba, Junichi Ushiba

“…IntroductionMotor-imagery-based Brain-Machine Interface (MI-BMI) has been established as an effective treatment for post-stroke hemiplegia. …”
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Change in Reciprocal Inhibition of the Forearm with Motor Imagery among Patients with Chronic Stroke by Michiyuki Kawakami, Kohei Okuyama, Yoko Takahashi, Miho Hiramoto, Atsuko Nishimura, Junichi Ushiba, Toshiyuki Fujiwara, Meigen Liu

“…The goals of this study were (1) to describe RI during MI in patients with chronic stroke and (2) to examine the change in RI after MI-based brain-machine interface (BMI) training. Twenty-four chronic stroke patients participated in study 1. …”
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Examining funders’ roles in responsible research and innovation of medical neurotechnology by Denis Larrivee, Jennifer French, Alberto Antonietti, Zach McKinney, Noeline W. Prins, Joana Soldado-Magraner, Michael J. Young, Laura Y. Cabrera

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Smartphone Household Wireless Electroencephalogram Hat by Harold Szu, Charles Hsu, Gyu Moon, Takeshi Yamakawa, Binh Q. Tran, Tzyy Ping Jung, Joseph Landa

“…Rudimentary brain machine interface has existed for the gaming industry. …”
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