TRR combines multi-band Riemannian features with a GRU to decode high-dimensional finger kinematics from EMG, achieving 9.79° intra-subject and 16.71° cross-subject average absolute error while running at ~10 Hz on a Raspberry Pi.
Real-time decomposition of surface electromyography into hand joint angles using a parallel an d efficient transformer network
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Digital Rock Physics is proposed as enabling infrastructure for critical minerals strategies through 3D imaging, AI analysis, modeling, and new data standards to improve viability assessment and circularity.
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Decoding High-Dimensional Finger Motion from EMG Using Riemannian Features and RNNs
TRR combines multi-band Riemannian features with a GRU to decode high-dimensional finger kinematics from EMG, achieving 9.79° intra-subject and 16.71° cross-subject average absolute error while running at ~10 Hz on a Raspberry Pi.
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Beyond Critical Minerals Targets: Digital Rock Physics as Infrastructure for Secure and Circular Supply Chains
Digital Rock Physics is proposed as enabling infrastructure for critical minerals strategies through 3D imaging, AI analysis, modeling, and new data standards to improve viability assessment and circularity.