A microfluidic chip for detecting tumor markers integrated functions including blood plasma separation, microvalve operation, and antibody immobilization.

No abstract

Objective. Impedance cardiography (ICG) is a noninvasive and continuous method for evaluating stroke volume and cardiac output. However, the ICG measurement is easily interfered due to respiration and body movements. Taking into consideration about the spectral correlations between the simultaneously collected ICG, electrocardiogram (ECG), and acceleration signals, this paper introduces a two-step spectrum denoising method to remove motion artifacts of ICG measurements in both resting and exercising scenarios. Approach. First, the major motion artifacts of ECG and ICG are separately suppressed by the spectral subtraction with respect to acceleration signals. The obtained ECG and ICG are further decomposed into two sets of intrinsic mode functions (IMFs) through the ensemble empirical mode decomposition. We then extract the shared spectral information between the two sets of IMFs using the canonical correlation analysis in a spectral domain. Finally, the ICG signal is reconstructed using those canonical variates with largest spectral correlations with ECG IMFs. Main results. The denoising method was evaluated for 30 subjects under both resting and cycling scenarios. Experimental results show that the beat contribution factor of ICG signals increases from its original 80.1%–97.4% after removing the motion artifacts. Significance. The proposed denoising scheme effectively improves the reliability of diagnosis and analysis on cardiovascular diseases relying on ICG signals.