A Novel and Accurate BiLSTM Configuration Controller for Modular Soft Robots with Module Number Adaptability.

Modular soft robots (MSRs) exhibit greater potential for sophisticated tasks compared with single-module robots. However, the modular structure incurs the complexity of accurate control and necessitates a control strategy specifically for modular robots. In this article, we introduce a data collection strategy tailored for MSR and a bidirectional long short-term memory (biLSTM) configuration controller capable of adapting to varying module numbers.

Interictal EEG source connectivity to localize the epileptogenic zone in patients with drug-resistant epilepsy: A machine learning approach.

Objective: To deconstruct the epileptogenic networks of patients with drug-resistant epilepsy (DRE) using source functional connectivity (FC) analysis; unveil the FC biomarkers of the epileptogenic zone (EZ); and develop machine learning (ML) models to estimate the EZ using brief interictal electroencephalography (EEG) data.

Methods: We analyzed scalp EEG from 50 patients with DRE who had surgery. We reconstructed the activity (electrical source imaging [ESI]) of virtual sensors (VSs) across the whole cortex and computed FC separately for epileptiform and non-epileptiform EEG epochs (with or without spikes).