A REAL-TIME DATA CLASSIFICATION SYSTEM FOR ACCURATE ANALYSIS OF NEURO-BIOLOGICAL SIGNALS

作者：Ji, Zhanfeng^*; Sugi, Takenao; Goto, Satoru; Wang, Xingyu; Nakamura, Masatoshi

来源：International Journal of Innovative Computing Information and Control, 2011, 7(1): 73-83.

• Real-time data classification
• Accurate analysis
• Artifacts detection
• EEG
• ERG

Neuro-biological signals have much importance in clinical diagnosis. However, those signals are inevitably contaminated by various artifacts. The analysis without considering the artifacts would lead to mis-interpretation results. Therefore, an available signal selection technique is necessary to be developed for obtaining accurate and reliable results. In this paper, a model of real-time data classification system for accurate analysis of neuro-biological signals was proposed. The proposed model can be utilized for various research purposes. As an example, a physical system to analyze the relationship between characteristics of electroencephalogram (EEG) and electrocardiogram (EKG) was developed. The results indicated that the real-time system was effective for available signals selection. With the developed real-time system, the quality of signals can be monitored during the recording process.

• 出版日期2011-1
• 单位华东理工大学