TOPICS
- Award
- Award-Student
- 2023
Zhiqiang Liao (D3 at the time) , Department of Electrical Engineering and Information Systems, received Outstanding Presentation Award
On 21st August 2023, Zhiqiang Liao ( D3, Department of Electrical Engineering and Information Systems at the time, currently a JSPS Postdoctoral Fellowship (PD), Department of Bioengineering) , received Outstanding Presentation Award at 1st Beijing Interdisciplinary Science Conference 2023.
Outstanding Presentation Award
This award is presented at the Beijing Interdisciplinary Science Society and at the Beijing Interdisciplinary Science Conference to recognize individual presenters who have made a wonderful presentation and made innovative contributions in multidiscipline research fields.
About awarded research
Zhiqiang Liao, Zhuozheng Shi, Hitoshi Tabata, “Enhanced Intelligent Diagnosis of Epileptic Electroencephalogram Based on Asymmetric Stochastic Resonance,” 1st Beijing Interdisciplinary Science Conference, Beijing, China, Aug. 2023.
Epilepsy is a chronic neurological disorder that can cause sudden symptoms such as seizures. The development of an automatic and accurate intelligent epilepsy diagnostic system has garnered widespread attention to prevent harm from sudden epileptic seizures. Considering the susceptibility of non-invasive brainwaves to noise interference, conventional intelligent diagnostic systems have required various filters. However, while these filters eliminate noise, they may also cause the loss of some valuable information from the brainwaves. To address these challenges, this study proposes an asymmetric stochastic resonance unit as a preprocessing module for an epilepsy seizure prediction system based on convolutional neural networks. Through nonlinear dynamic analysis, this research demonstrates the asymmetric stochastic resonance unit's capability to adjust gain coefficients of different frequency components of brainwaves, resulting in an effect akin to attention mechanisms in intelligent systems. Testing on scalp electroencephalogram (EEG) databases for adult and pediatric epilepsy revealed the superiority of the asymmetric stochastic resonance unit over other traditional preprocessing methods in this study.
Your impression & future plan
I am deeply grateful for having received such an honorable award, thanks to the collaboration with all of my fellow researchers. I will continue to dedicate myself even further and aim for greater achievements in the future.