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An 8-Channel Scalable EEG Acquisition SoC With Patient-Specific Seizure Classification and Recording Processor
An 8-channel scalable EEG acquisition SoC is presented to continuously detect and record patient-specific seizure onset activities from scalp EEG. The SoC integrates 8 high-dynamic range AnalogExpand
A 1.83µJ/classification nonlinear support-vector-machine-based patient-specific seizure classification SoC
A Non-Linear SVM (NLSVM)-based seizure detection SoC which ensures a >95% detection accuracy, <;1% false alarm and <;2s latency is presented. Expand
A 1.83 µJ/Classification, 8-Channel, Patient-Specific Epileptic Seizure Classification SoC Using a Non-Linear Support Vector Machine
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 the first work inExpand
21.8 A 16-ch patient-specific seizure onset and termination detection SoC with machine-learning and voltage-mode transcranial stimulation
This paper presents an ultra-low power 16-ch "non-invasive, patient-specific" seizure onset and termination detection SoC with channels multiplexing AFE and pulsating voltage transcranial electrical stimulation (PVTES). Expand
Design and Implementation of an On-Chip Patient-Specific Closed-Loop Seizure Onset and Termination Detection System
An area- and energy-efficient closed-loop machine learning-based patient-specific seizure onset and termination detection algorithm, and its on-chip hardware implementation, which achieves high sensitivity and specificity for long-term monitoring of patients with limited training seizure patterns is presented. Expand
An 8-channel scalable EEG acquisition SoC with fully integrated patient-specific seizure classification and recording processor
This paper presents an ultra-low power scalable EEG acquisition SoC for continuous seizure detection and recording with fully integrated patient-specific Support Vector Machine (SVM)-based classification processor. Expand
A 1.1-mW Ground Effect-Resilient Body-Coupled Communication Transceiver With Pseudo OFDM for Head and Body Area Network
A body-coupled communication (BCC) transceiver (TRX) that mitigates all the practical impairments of the body channel at once is presented, which has been the two major issues on the BCC. Expand
A10.13uJ/classification 2-channel Deep Neural Network-based SoC for Emotion Detection of Autistic Children
An EEG-based noninvasive neuro-feedback SoC for emotion classification of Autistic children is presented and the 4-layers Deep Neural Network (DNN) classifier is integrated on-sensor to classify (4 emotions) with >85% accuracy. Expand
A high accuracy and low latency patient-specific wearable fall detection system
A patient-specific single sensor fall detection system that utilizes a tri-axial accelerometer data measured from the patient's trouser pocket to distinguish between activities of daily living (ADL) and falls is presented. Expand
An On-Chip Processor for Chronic Neurological Disorders Assistance Using Negative Affectivity Classification
Hardware efficient and dedicated human emotion classification processor for CND's and a look-up-table based logarithmic division unit (LDU) to represent the division features in machine learning (ML) applications. Expand