A low-power epilepsy detection circuit based on master-slave support vector machine

Abstract

The invention discloses a low-power epilepsy detection circuit based on a master-slave support vector machine, which belongs to the field of intelligent medical applications. The circuit includes: a clock module, a feature extraction module, a master-slave support vector machine module and a decision module; the master-slave support vector machine module includes a master support vector machine and a slave support vector machine, the master support vector machine is a linear support vector machine, and the slave The support vector machine is a non-linear support vector machine; the main support vector machine controls the startup and shutdown of the slave support vector machine; during the detection process, the main support vector machine detects the beginning of the seizure, starts the slave support vector machine, and corrects the slave support vector machine The end of the epileptic seizure; the detection result of the master-slave support vector machine module is the logic AND of the detection result of the master-slave support vector machine. This application utilizes the master-slave support vector machine and continuous sequence detection, so that under the premise of ensuring the detection performance, the calculation complexity is greatly reduced, the power consumption is reduced, and the requirements of intelligent medical applications are better adapted.

Description

technical field [0001] The invention relates to a low-power consumption epilepsy detection circuit based on a master-slave support vector machine, which belongs to the field of intelligent medical applications. Background technique [0002] As of 2019, the World Health Organization data shows that there are 60 million epilepsy patients worldwide. As we all know, epilepsy is a chronic neurological disease caused by sudden excessive discharge of neuronal cells and is characterized by recurrent seizures, which can range from short attention shifts or muscle twitches to severe and persistent convulsions. Due to the particularity of epileptic seizures, it brings great difficulties in social life to patients, such as discrimination, isolation, fear, and inability to drive and work. There are many brain diseases, therefore, the correct detection and diagnosis is of great significance. [0003] For the detection of epileptic seizures, early long-term electroencephalogram (EEG) mon...

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Problems solved by technology

[0005] Among the above methods, some of them use complex classification algorithms and feature extraction methods in order to pursue higher detection performance such as sensitivity, resulting in a large power consumption, and the other part uses a single linear SVM detection, although the power consumption is reduced , but also reduces the sensitivity of the detection circuit

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