Measuring Electrolyte Impedance and Noise Simultaneously by Triangular Waveform Voltage and Principal Component Analysis

Tissue Recognition Based on Electrical Impedance Classified by Support Vector Machine in Spinal Operation Area

OBJECTIVE

One of the major difficulties in spinal surgery is the injury of important tissues caused by tissue misclassification, which is the source of surgical complications. Accurate recognization of the tissues is the key to increase safety and effect as well as to reduce the complications of spinal surgery. The study aimed at tissue recognition in the spinal operation area based on electrical impedance and the boundaries of electrical impedance between cortical bone, cancellous bone, spinal cord, muscle, and nucleus pulposus.

METHODS

Two female white swines with body weight of 40 kg were used to expose cortical bone, cancellous bone, spinal cord, muscle, and nucleus pulposus under general anesthesia and aseptic conditions. The electrical impedance of these tissues at 12 frequencies (in the range of 10-100 kHz) was measured by electrochemical analyzer with a specially designed probe, at 22.0-25.0°C and 50%-60% humidity. Two types of tissue recognition models - one combines principal component analysis (PCA) and support vector machine (SVM) and the other combines combines SVM and ensemble learning - were constructed, and the boundaries of electrical impedance of the five tissues at 12 frequencies of current were figured out. Linear correlation, two-way ANOVA, and paired T-test were conducted to analyze the relationship between the electrical impedance of different tissues at different frequencies.

RESULTS

The results suggest that the differences of electrical impedance mainly came from tissue type (p < 0.0001), the electrical impedance of five kinds of tissue was statistically different from each other (p < 0.0001). The tissue recognition accuracy of the algorithm based on principal component analysis and support vector machine ranged from 83%-100%, and the overall accuracy was 95.83%. The classification accuracy of the algorithm based on support vector machine and ensemble learning was 100%, and the boundaries of electrical impedance of five tissues at various frequencies were calculated.

CONCLUSION

The electrical impedance of cortical bone, cancellous bone, spinal cord, muscle, and nucleus pulposus had significant differences in 10-100 kHz frequency. The application of support vector machine realized the accurate tissue recognition in the spinal operation area based on electrical impedance, which is expected to be translated and applied to tissue recognition during spinal surgery.

Generation of an optical triangular-shaped pulse train with variable symmetry by using an I/Q modulator

A setup for an optical triangular-shaped pulse train with variable symmetry is proposed. The key component is an I/Q (I: in-phase, Q: quadrature phase) modulator. By properly setting the three variables, the optical intensity can be expressed by the sum of infinite sinusoidal harmonics, which indicates the possibility to approximate the asymmetrical waveform. It is found that the scheme is capable for generating an optical triangular-shaped pulse train with a tunable symmetrical coefficient (${20}\% \le \delta \le {80}\% $20%≤δ≤80%) and low fitting error ($\eta \le {6}\% $η≤6%).

A 3D Faraday Shield for Interdigitated Dielectrometry Sensors and Its Effect on Capacitance

Interdigitated dielectrometry sensors (IDS) are capacitive sensors investigated to precisely measure the relative permittivity (ϵr) of insulating liquids. Such liquids used in the power industry exhibit a change in ϵr as they degrade. The IDS ability to measure ϵr in-situ can potentially reduce maintenance, increase grid stability and improve safety. Noise from external electric field sources is a prominent issue with IDS. This paper investigates the novelty of applying a Faraday cage onto an IDS as a 3D shield to reduce this noise. This alters the spatially distributed electric field of an IDS affecting its sensing properties. Therefore, dependency of the sensor’s signal with the distance to a shield above the IDS electrodes has been investigated experimentally and theoretically via a Green’s function calculation and FEM. A criteria of the shield’s distance s = s0 has been defined as the distance which gives a capacitance for the IDS equal to 1 − e−2=86.5% of its unshielded value. Theoretical calculations using a simplified geometry gave a constant value for s0/λ = 1.65, where λ is the IDS wavelength. In the experiment, values for s0 were found to be lower than predicted as from theory and the ratio s0/λ variable. This was analyzed in detail and it was found to be resulting from the specific spatial structure of the IDS. A subsequent measurement of a common insulating liquid with a nearby noise source demonstrates a considerable reduction in the standard deviation of the relative permittivity from σunshielded=±9.5% to σshielded=±0.6%. The presented findings enhance our understanding of IDS in respect to the influence of a Faraday shield on the capacitance, parasitic capacitances of the IDS and external noise impact on the measurement of ϵr.