Research Status of Epileptic Spike Detection Algorithms Based on EEG and MEG
WEI Boxuan1a,2, ZHANG Jicong1a,1b,1c,2
1. a. School of Biological and Medical Engineering; b. Beijing Advanced Innovation Center of Biomedical Engineering; c. Beijing High
Precision Innovation Center of Big Data Precision Medicine, Beihang University, Beijing 100191, China; 2. Hefei Innovation Research
Institute, Beihang University, Hefei Anhui 230012, China
Abstract：Epilepsy is one of the most serious disorders that affect patients’ daily lives. Brain neuron activity can be recorded through
electroencephalogram (EEG) and magnetoencephalogram (MEG). Abnormal waveforms of EEG and MEG, especially spikes, contain
a large number of pathological information related to epilepsy. However, the current clinical extraction of epileptic spikes is still
dependent on labor, resulting in strong subjectivity and a huge burden on doctors. The automatic detection of epileptic spikes is of
great significance. In this paper, the importance and existing problems of spike detection were discussed according to characteristic of
spike at first. Then, research status of spike detection algorithms with feature engineering in recent 10 years were reviewed. Finally,
the challenge and future research directions of this field were summarized.
韦博轩1a,2，张冀聪1a,1b,1c,2. EEG及MEG痫样棘波检测算法研究现状[J]. 中国医疗设备, 2019, 34(11): 30-33.
WEI Boxuan1a,2, ZHANG Jicong1a,1b,1c,2. Research Status of Epileptic Spike Detection Algorithms Based on EEG and MEG. China Medical Devices, 2019, 34(11): 30-33.
