11:15 〜 11:30
▼ [9a-Z12-9] Adaptive Time Domain Average Stochastic Resonance System for Magnetocardiographic Detection at Room Temperature
キーワード：stochastic resonance, MCG detection, heart signal processing
Magnetocardiogram (MCG) is a kind of magnetic field which is generated in the heart by the electrical activity. MCG has great potential to improve the diagnosis of diseases and to clarify the biological functions of heart. At present, the most reliable MCG measuring device is superconducting quantum interference device (SQUID). The SQUID magnetometer has high sensitivity, but it incurs high equipment and operational costs, especially the purchase of liquid helium.
In order to reduce the cost and make the MCG can be measured at room temperature, many different sensors like OPM, TMR sensors, etc. have been researched. But at present, in the signal processing part, the performance of traditional time domain average (TDA) method is still insufficient to meet the clinical needs. In this study, we focused on improving the overall detection performance of the system from the part of signal processing by stochastic resonance (SR) combining with improved traditional TDA method.
SR refers to a situation where the mere addition of random noise to the dynamics improves a system’s sensitivity to discriminate weak information-carrying signals. Because the stochastic resonance system is a nonlinear system, the adjustment of its parameters is complex. Therefore, in this study, ant lion optimization algorithm is used so that the whole device can adaptively complete the parameter matching and get the appropriate results of MCG.
In this research, we will first improve the traditional TDA method and combine SR and ant lion optimization algorithm as an adaptive MCG detection system which can work at room temperature. Finally, we will use the proposed system to detect the MCG of the rats and verify the effectiveness of the proposed system.
In order to reduce the cost and make the MCG can be measured at room temperature, many different sensors like OPM, TMR sensors, etc. have been researched. But at present, in the signal processing part, the performance of traditional time domain average (TDA) method is still insufficient to meet the clinical needs. In this study, we focused on improving the overall detection performance of the system from the part of signal processing by stochastic resonance (SR) combining with improved traditional TDA method.
SR refers to a situation where the mere addition of random noise to the dynamics improves a system’s sensitivity to discriminate weak information-carrying signals. Because the stochastic resonance system is a nonlinear system, the adjustment of its parameters is complex. Therefore, in this study, ant lion optimization algorithm is used so that the whole device can adaptively complete the parameter matching and get the appropriate results of MCG.
In this research, we will first improve the traditional TDA method and combine SR and ant lion optimization algorithm as an adaptive MCG detection system which can work at room temperature. Finally, we will use the proposed system to detect the MCG of the rats and verify the effectiveness of the proposed system.