Flexible pressure sensors with high sensitivity and good linearity are in high demand to meet the long-term and accurate detection requirements for pulse detection. In this study, we propose a composite membrane pressure sensor using polydimethylsiloxane (PDMS) and multiwalled carbon nanotubes (MWNTS) reinforced with isopropanol prepared by solution blending and a self-made 3D-printed mold. The device doped with isopropanol had a higher sensitivity and linearity owning to the construction of additional conductive paths. The optimal conditions for realizing a high-performance pressure sensor are a multiwalled carbon nanotube mass ratio of 7% and a composite membrane thickness of 490 μm. The membrane achieves a high linear sensitivity of −57.07 kΩ∙kPa−1 and a linear fitting correlation coefficient of 98.78% in the 0.13~5.2 kPa pressure range corresponding to pulse detection. Clearly, this device has great potential for application in pulse detection.

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BACKGROUND: Wearable devices that monitor heart health of cardiac disease patients in real time are in great demand. OBJECTIVE: We propose an algorithm of improved segment periodical matrix construction for irregular electrocardiogram (ECG) signal denoising. METHOD: While splitting the heartbeat based on each RR interval for periodical segments matrix construction, the as-filtered ECG signal is reconstructed by the maximum singular value after a singular value decomposition. RESULTS: The results demonstrate a higher noise reduction effect with lower signal distortions of our methods compared to several singular value decomposition counterpart approaches. CONCLUSION: Our method has great potential to enhance wearable devices diagnosis accuracy by denoising the complex noises such as electromyography artifacts in real-time ECG sensing.