Magnetic nanoparticles (MNPs) are commonly used in biomedical detection due to their capability to bind with some specific antibodies. Quantification of biological entities could be realized by measuring the magnetic response of MNPs after the binding process. This paper presents a contactless scanning prototype based on tunneling magnetoresistance (TMR) sensors for quantification of MNPs present in lateral flow strips (LFSs). The sensing unit of the prototype composes of two active TMR elements, which are parallel and closely arranged to form a differential sensing configuration in a perpendicular magnetic field. Geometrical parameters of the configuration are optimized according to theoretical analysis of the stray magnetic field produced by the test line (T-line) while strips being scanned. A brief description of our prototype and the sample preparation is presented. Experimental results show that the prototype exhibits the performance of high sensitivity and strong anti-interference ability. Meanwhile, the detection speed has been improved compared with existing similar techniques. The proposed prototype demonstrates a good sensitivity for detecting samples containing human chorionic gonadotropin (hCG) at a concentration of 25 mIU/mL. The T-line produced by the sample with low concentration is almost beyond the visual limit and produces a maximum stray magnetic field some 0.247 mOe at the sensor in the x direction.

Various types of interference signals are available in the working environment of passive wireless surface acoustic wave (SAW) sensors. Among these kinds of interference, co-channel interference is difficult to suppress. To solve this problem, a SAW sensor anti-interference technology was proposed to improve the reliability of the SAW sensor. Wavelet denoising method was used to denoise SAW resonator (SAWR) response, which can maintain the envelope characteristics of the SAW response. The entropy energy model of the SAW response signal was established, and the signal envelope was extracted from the proposed entropy energy function. The waveform envelope and the entropy energy curve were adopted as the signal characteristics to form two-dimensional points. The K-Means algorithm was used to classify the two-dimensional points to distinguish the SAW response from sinusoidal interference. Simulation results showed that the SAW response can be detected with a rate of more than 85% when the signal-to-noise ratio was greater than 4 dB, whereas the false detection rate of the sinusoidal interference signal was less than 8%. Finally, the proposed algorithm was used to detect the actual SAW response and sinusoidal interference signal. The experimental results showed that the proposed method can clearly distinguish the SAW response from the co-channel interference signal. Moreover, the proposed method can be used as the anti-interference technology to improve the stability of the SAW sensor.

Passive wireless surface acoustic wave (SAW) resonant sensors are suitable for applications in harsh environments. The traditional SAW resonant sensor system requires, however, Fourier transformation (FT) which has a resolution restriction and decreases the accuracy. In order to improve the accuracy and resolution of the measurement, the singular value decomposition (SVD)-based frequency estimation algorithm is applied for wireless SAW resonant sensor responses, which is a combination of a single tone undamped and damped sinusoid signal with the same frequency. Compared with the FT algorithm, the accuracy and the resolution of the method used in the self-developed wireless SAW resonant sensor system are validated.

Compared with apodization, the piston-mode technique is a preferable solution to suppress the spurious transverse modes in surface acoustic wave (SAW) devices. This paper extends the technique to the SAW resonator (SAWR) strain sensors to achieve a high performance, that is, conquer some negative influence in the wireless strain sensing system caused by the spurious modes, such as low signal to noise ratio (SNR), high misreading rate and demodulation difficulty. The principle of piston-mode operation was presented and a modified expression was given for primary design of the piston-mode waveguide, which takes into account the anisotropy difference in different electrode regions. SAWRs based on the Al/ST-quartz with the conventional and two common piston-mode configurations were designed, simulated, fabricated and measured. The experiments to evaluate the wireless performance and strain sensitivity of the SAWR strain sensors with different electrode configurations were performed.

Since surface acoustic waves (SAWs) are composed of multiple displacement components, their slowness curves sometimes exhibit a more complex shape rather than elliptical or hyperbolic. As a result, the parabolic approximation of 2-D coupling-of-modes (2-D COM) equations is invalid for analysis of waveguiding in such SAW devices. Thence, this paper develops a new general form of 2-D COM equations based on the basic 2-D wave equations of SAWs which contain two displacement components. The fundamentals of the equations were established and the procedures for determining 2-D COM parameters were presented in detail. The new equations were embedded in the partial differential equation (PDE) mode of COMSOL for the simulation of different types of SAWs, including Rayleigh and shear-horizontal (SH) SAWs on ST-quartz and 42°YX-LiTaO3 (42-LT) substrates, respectively. By comparing the calculated results with 1-D COM, parabolic 2-D COM, extended thin plate model, 3-D finite-element method (FEM) calculated results, and the measured result, the applicability of these equations was verified.