Hierarchical CNN-LSTM plus vision transformer detects tremor from raw time-domain kinematic data across nine body parts with average F1 of 0.765 and attention-based explanations.
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EEG source imaging shows strong dependence between forward source model choice and inverse method success, with point-like source models matching best to dipole-scanning inverses.
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An explainable hierarchical self attention-based approach for tremor detection in the time domain
Hierarchical CNN-LSTM plus vision transformer detects tremor from raw time-domain kinematic data across nine body parts with average F1 of 0.765 and attention-based explanations.