公开(公告)号：US20180303364A1

公开(公告)日：2018-10-25

申请号：US15955010

申请日：2018-04-17

Applicant: Massachusetts Institute of Technology ,  Masdar Institute of Science and Technology

Inventor： Jerald Yoo ,  Anantha P. Chandrakasan ,  Long Yan ,  Dina Reda El-Damak ,  Ali Hossam Shoeb ,  Muhammad Awais Bin Altaf

IPC: A61B5/04 ,  H03H17/02 ,  A61B5/00 ,  H03F3/387 ,  A61B5/0476

CPC classification number: A61B5/04012 ,  A61B5/0476 ,  A61B5/4094 ,  A61B2562/166 ,  H03F3/387 ,  H03F2200/294 ,  H03F2200/375 ,  H03H17/0226 ,  H03H17/0248

Abstract: An integrated circuit chip and method for EEG monitoring. In one embodiment, the integrated circuit chip includes an Analog Front End cell in communication with an electrode and a Classification Processor wherein a signal received from the electrode is processed by the Classification Engine cell and designated as seizure or non-seizure. In another embodiment, the Analog Front End cell includes an amplifier cell in communication with an electrode; and an ASPU cell in communication with the amplifier cell. In yet another embodiment, the Classification Processor includes a DBE Channel Controller cell; a Feature Extraction Engine Processor cell, and a Classification Engine cell in communication with the Feature Extraction Engine Processor cells and the DBE Channel Controller cell.

公开(公告)号：US09848793B2

公开(公告)日：2017-12-26

申请号：US14182570

申请日：2014-02-18

Applicant: Masdar Institute of Science and Technology

Inventor： Jerald Yoo ,  Muhammad Awais Bin Altaf

IPC: A61B5/04 ,  A61B5/00 ,  A61B5/0478

CPC classification number: A61B5/04017 ,  A61B5/0478 ,  A61B5/4094 ,  A61B5/4836 ,  A61B5/725 ,  A61B2503/04 ,  A61B2503/06

Abstract: This disclosure is directed to a machine-based patient-specific seizure classification system. In general, an example system may comprise a non-linear SVM seizure classification system-on-chip (SoC) with multichannel EEG data acquisition and storage for epileptic patients is presented. The SoC may integrate a hardware-efficient log-linear Gaussian Basis Function engine, floating point piecewise linear natural log, and low-noise, high dynamic range readout circuits. In at least one example implementation, the SoC may consume 1.83 μJ/classification while classifying 8 channel results with an average detection rate, average false alarm rate and latency of 95.1%, 0.94% and

公开(公告)号：US20140235990A1

公开(公告)日：2014-08-21

申请号：US14182570

申请日：2014-02-18

Applicant: Masdar Institute of Science and Technology

Inventor： Jerald Yoo ,  Muhammad Awais Bin Altaf

IPC: A61B5/04 ,  A61B5/00 ,  A61B5/0478

CPC classification number: A61B5/04017 ,  A61B5/0478 ,  A61B5/4094 ,  A61B5/4836 ,  A61B5/725 ,  A61B2503/04 ,  A61B2503/06

Abstract: This disclosure is directed to a machine-based patient-specific seizure classification system. In general, an example system may comprise a non-linear SVM seizure classification system-on-chip (SoC) with multichannel EEG data acquisition and storage for epileptic patients is presented. The SoC may integrate a hardware-efficient log-linear Gaussian Basis Function engine, floating point piecewise linear natural log, and low-noise, high dynamic range readout circuits. In at least one example implementation, the SoC may consume 1.83W/classification while classifying 8 channel results with an average detection rate, average false alarm rate and latency of 95.1%, 0.94% and

Abstract translation: 本公开涉及基于机器的患者特异性发作分类系统。 一般来说，示例系统可以包括用于癫痫患者的具有多通道EEG数据采集和存储的非线性SVM癫痫发作分类系统级芯片（SoC）。 SoC可以集成硬件高效的对数线性高斯基函数引擎，浮点分段线性自然对数和低噪声，高动态范围读出电路。 在至少一个示例实现中，SoC可以消耗1.83W /分类，同时对平均检测率，平均误报率和等待时间分别为95.1％，0.94％和<2s的8个信道结果进行分类。