Wireless Power Transfer and Data Communication for Intracranial Neural Implants Case Study : Epilepsy Monitoring

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This article summarizes the recent advancements in the design, fabrication, and control of microrobotic devices for the diagnosis and treatment of brain disorders. With a focus on diverse actuation methods, we discuss how advancements in materials science ...

The rise of robotic body augmentation brings forth new developments that will transform robotics, human-machine interaction, and wearable electronics. Extra robotic limbs, although building upon restorative technologies, bring their own set of challenges i ...

The auxiliary power supply for medium voltage converters requires high insulation capability between the source and the load. Inductive power transfer technology, with an air gap between the primary and secondary coil, offers such high insulation capabilit ...

Solid-state transformers with input-series outputparallel structures are being considered for a variety of applications requiring MVAC to LVDC conversion. Due to the singlephase AC/DC conversion at the input side, all floating cells of the solid-state tran ...

This thesis investigates the magnetic properties of single atoms and molecules adsorbed on thin magnesium oxide decoupling layers, grown on a silver single crystal. To address these systems experimentally, we use a low temperature scanning tunneling micros ...

The capabilities of deep learning systems have advanced much faster than our ability to understand them. Whilst the gains from deep neural networks (DNNs) are significant, they are accompanied by a growing risk and gravity of a bad outcome. This is troubli ...

Background Neurological disorders, such as stroke and chronic pain syndromes, profoundly impact independence and quality of life, especially when affecting upper extremity (UE) function. While conventional physical therapy has shown effectiveness in provid ...

In humans and animals, surprise is a physiological reaction to an unexpected event, but how surprise can be linked to plausible models of neuronal activity is an open problem. We propose a self-supervised spiking neural network model where a surprise signa ...

Despite the widespread empirical success of ResNet, the generalization properties of deep ResNet are rarely explored beyond the lazy training regime. In this work, we investigate scaled ResNet in the limit of infinitely deep and wide neural networks, of wh ...

Reinforcement feedback can improve motor learning, but the underlying brain mechanisms remain underexplored. In particular, the causal contribution of specific patterns of oscillatory activity within the human striatum is unknown. To address this question, ...

This paper focuses on the operational characteristics of a medium voltage resonant DC transformer based on a split capacitor IGCT 3L-NPC leg. The study delves into both the dynamic and static balancing aspects of the 3L-NPC when operating in a two-level, 5 ...

Here we provide the neural data, activation and predictions for the best models and result dataframes of our article "Task-driven neural network models predict neural dynamics of proprioception". It contains the behavioral and neural experimental data (cu ...

Many feedforward neural networks (NNs) generate continuous and piecewise-linear (CPWL) mappings. Specifically, they partition the input domain into regions on which the mapping is affine. The number of these so-called linear regions offers a natural metric ...

Wireless Power Transfer and Data Communication for Intracranial Neural Implants Case Study : Epilepsy Monitoring

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Small-scale robotic devices for medical interventions in the brain

Investigating neural resource allocation in the sensorimotor control of extra limbs

Modeling and optimization of PCB coils for inductive power transfer systems

Active Power Decoupling for Single-Phase Input-Series-Output-Parallel Solid-State Transformers

Magnetism of Single Surface Adsorbed Atoms Studied with Radio-Frequency STM

Safe Deep Neural Networks

Immersive VR for upper-extremity rehabilitation in patients with neurological disorders: a scoping review

Fast adaptation to rule switching using neuronal surprise

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Non-invasive stimulation of the human striatum disrupts reinforcement learning of motor skills

Static and Dynamic Voltage Balancing for an IGCT-Based Resonant DC Transformer

Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

On the number of regions of piecewise linear neural networks