Optimizing biomagnetic sensor performance through in silico diagnostics: A novel approach with BEST (Biomagnetism Evaluation via Simulated Testing)

Figures

• 

  Figure 1. Model establishment and data acquisition (A) Model of MCG signals and placement of sensors. Green and red arrows represent current dipoles simulating MCG signals. The midpoint of the arrow handle represents the position of the dipole, the direction of the arrow represents the orientation of the dipole, and the length of the arrow represents the strength of the dipole. The largest dipole is fixed in position to simulate the normal MCG signal (above), whereas the other dipoles are randomly generated to simulate lesioned signals (below). The orange dots represent the position of the center of the sensors’ bottoms. The blue plane and the orange plane represent the planes where the largest dipole and the sensors’ bottoms are located, respectively. The distance between the two planes is defined as d. (B) Models of cubic and cuboid sensors. The red dot represents the center position of the sensor’s bottom. The blue dots represent all field points that need to be included in the average calculation when simulating the measurement result of the sensor. The bottom edge length of the sensor is defined as a, and the height of the sensor is defined as h. (The diagram shows the cases where…

• 

  Figure 2. Size and distance effects for cubic sensor arrays (A) Linear interpolated result of accuracy on a-d parameter space; a represents the bottom edge length, d represents the distance from the main dipole plane, and the color represents the accuracy of classification on the validation set. (B) Scatterplot of accuracy variation with the change of d under the condition of fixing different values of a. (C) Scatterplot of accuracy variation with the change of a under the condition of fixing different values of d.

• 

  Figure 3. Size and distance effects for cuboid sensor arrays with h=0.5cm (A) Linear interpolated result of accuracy on a-d parameter space; a represents the bottom edge length, d represents the distance from the main dipole plane, and the color represents the accuracy of classification on the validation set. (B) Scatterplot of accuracy variation with the change of d under the condition of fixing different values of a. (C) Scatterplot of accuracy variation with the change of a under the condition of fixing different values of d.

• 

  Figure 4. Size effects from height and bottom edge length for cuboid sensor arrays with d=4cm (A) Linear interpolated result of accuracy on h-a parameter space; h represents the height of the sensors, a represents the bottom edge length, and the color represents the accuracy of classification on the validation set. (B) Scatterplot of accuracy variation with the change of a under the condition of fixing different values of h. (C) Scatterplot of accuracy variation with the change of h under the condition of fixing different values of a.