A Microflow Cytometer Enabled by Monolithic Integration of a Microreflector with an Acoustic Resonator.

Current microflow cytometers suffer from complicated fluidic integration and low fluorescence collection efficiency, resulting in reduced portability and sensitivity. Herein, we demonstrated a new flow cell design based on an on-chip monolithically integrated microreflector with a bulk acoustic wave resonator (MBAW). It enables simultaneous 3D particle focusing and fluorescence enhancement without using shear flow. Benefited by the on-chip microreflector, the captured fluorescence intensity was 1.8-fold greater than that of the Si substrate and 8.3-fold greater than that of the SiO2 substrate, greatly improving the detection sensitivity. Combined with the contactless acoustic streaming-based focusing, particle sensing with a coefficient of variation as low as 6.1% was achieved. We also demonstrated the difference between live and dead cells and performed a cell cycle assay using the as-developed microflow cytometry. This monolithic integrated MBAW provides a new type of opto-acoustofluidic system and has the potential to be a highly integrated, highly sensitive flow cytometer for applications such as in vitro diagnostics and point of care.

Comparison and Noise Suppression of the Transmitted and Reflected Photoplethysmography Signals.

The photoplethysmography (PPG) is inevitably corrupted by many kinds of noise no matter whether its acquisition mode is transmittance or reflectance. To enhance the quality of PPG signals, many studies have made great progress in PPG denoising by adding extra sensors and developing complex algorithms. Considering the reasonable cost, compact size, and real-time and easy implementation, this study proposed a simple real-time denoising method based on double median filters which can be integrated in microcontroller of commercial or portable pulse oximeters without adding extra hardware. First, we used the boundary extension to preserve the signal boundary distortion and designed a first median filter with the time window at approximately 78 ms to eliminate the high-frequency components of the signal. Then, through the second median filter with a time window which was about 780 ms, we estimated the low-frequency components. Finally, we removed the estimated low-frequency components from the signal to obtain the denoised signal. Through comparing the multiple sets of signals under calmly sitting and slightly moving postures, the PPG signals contained noises no matter whether collected by the transmittance-mode or the reflectance-mode. To evaluate the proposed method, we conducted measured, simulated experiments and a strong noisy environment experiment. Through comparing the morphology distortions, frequency spectra, and the signal-to-noise ratios (SNRs), the results showed that the proposed method can suppress noise effectively and preserve the essential morphological features from PPG signals. As a result, the proposed method can enhance the quality of PPG signals and, thus, can contribute to the improvement of the calculation accuracy of the subsequent physiological parameters. In addition, the proposed method could be a good choice to address the real-time noise reduction of portable PPG measuring instruments.