首页|Exploring the trade-off between deep-learning and explainable models for brain-m achine interfaces
Exploring the trade-off between deep-learning and explainable models for brain-m achine interfaces
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – According to news reporting based on a preprint abstract, our journalists obtained the following quote sourced from bi orxiv.org: “People with brain or spinal cord-related paralysis often need to rely on others for basic tasks, limiting their independence. “A potential solution is brain-machine interfaces (BMIs), which could allow them to voluntarily control external devices (e.g., robotic arm) by decoding brain a ctivity to movement commands. In the past decade, deep-learning decoders have ac hieved state-of-the-art results in most BMI applications, ranging from speech pr oduction to finger control.
Brain-Based DevicesBrain-machine Inter faceEmerging TechnologiesMachine LearningNeuroscience
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