A 16-channel noninvasive closed-loop beginning-and end-of-seizure detection SoC is
presented. The dual-channel charge recycled (DCCR) analog front end (AFE) achieves …

Biomedical applications often require classifiers that are both accurate and cheap to
implement. Today, deep neural networks achieve the state-of-the-art accuracy in most …

Recent years have seen deployments of increasingly complex artificial intelligent (AI) and
machine learning techniques being implemented on cloud server architectures and …

A non-linear support vector machine (NLSVM) seizure classification SoC with 8-channel
EEG data acquisition and storage for epileptic patients is presented. The proposed SoC is …

Epilepsy treatment in clinical practices with surface electroencephalogram (EEG) often faces
training dataset shortage issue, which is aggravated by seizure pattern variation among …

Closed-loop neuromodulation can alleviate disease symptoms and provide sensory
feedback in various neurological disorders and injuries [1]. Energy-efficient realization of …

An EEG-based noninvasive neuro-feedback SoC for emotion classification of Autistic
children is presented. The AFE comprises two entirely shared EEG-channels using sampling …

Neural interfaces play an important role in vital sign monitoring, clinical practice, and
neuroscience frontier research using animal subjects, such as rodents and nonhuman …

This paper presents the design of an area-and energy-efficient closed-loop machine
learning-based patient-specific seizure onset and termination detection algorithm, and its on …

This paper presents a wearable active concentric electrode for concurrent EEG monitoring
and Body-Coupled Communication (BCC) data transmission. A three-layer concentric …