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      Intra-beat biomarker for accurate continuous non-invasive blood pressure monitoring

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          Abstract

          Accurate continuous non-invasive blood pressure (CNIBP) monitoring is the holy grail of digital medicine but remains elusive largely due to significant drifts in signal and motion artifacts that necessitate frequent device recalibration. To address these challenges, we developed a unique approach by creating a novel intra-beat biomarker (Diastolic Transit Time, DTT) to achieve highly accurate blood pressure (BP) estimations. We demonstrated our approach’s superior performance, compared to other common signal processing techniques, in eliminating stochastic baseline wander, while maintaining signal integrity and measurement accuracy, even during significant hemodynamic changes. We applied this new algorithm to BP data collected using non-invasive sensors from a diverse cohort of high acuity patients and demonstrated that we could achieve close agreement with the gold standard invasive arterial line BP measurements, for up to 20 min without recalibration. We established our approach's generalizability by successfully applying it to pulse waveforms obtained from various sensors, including photoplethysmography and capacitive-based pressure sensors. Our algorithm also maintained signal integrity, enabling reliable assessments of BP variability. Moreover, our algorithm demonstrated tolerance to both low- and high-frequency motion artifacts during abrupt hand movements and prolonged periods of walking. Thus, our approach shows promise in constituting a necessary advance and can be applied to a wide range of wearable sensors for CNIBP monitoring in the ambulatory and inpatient settings.

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          Highly sensitive flexible pressure sensors with microstructured rubber dielectric layers.

          The development of an electronic skin is critical to the realization of artificial intelligence that comes into direct contact with humans, and to biomedical applications such as prosthetic skin. To mimic the tactile sensing properties of natural skin, large arrays of pixel pressure sensors on a flexible and stretchable substrate are required. We demonstrate flexible, capacitive pressure sensors with unprecedented sensitivity and very short response times that can be inexpensively fabricated over large areas by microstructuring of thin films of the biocompatible elastomer polydimethylsiloxane. The pressure sensitivity of the microstructured films far surpassed that exhibited by unstructured elastomeric films of similar thickness, and is tunable by using different microstructures. The microstructured films were integrated into organic field-effect transistors as the dielectric layer, forming a new type of active sensor device with similarly excellent sensitivity and response times.
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            25th anniversary article: The evolution of electronic skin (e-skin): a brief history, design considerations, and recent progress.

            Human skin is a remarkable organ. It consists of an integrated, stretchable network of sensors that relay information about tactile and thermal stimuli to the brain, allowing us to maneuver within our environment safely and effectively. Interest in large-area networks of electronic devices inspired by human skin is motivated by the promise of creating autonomous intelligent robots and biomimetic prosthetics, among other applications. The development of electronic networks comprised of flexible, stretchable, and robust devices that are compatible with large-area implementation and integrated with multiple functionalities is a testament to the progress in developing an electronic skin (e-skin) akin to human skin. E-skins are already capable of providing augmented performance over their organic counterpart, both in superior spatial resolution and thermal sensitivity. They could be further improved through the incorporation of additional functionalities (e.g., chemical and biological sensing) and desired properties (e.g., biodegradability and self-powering). Continued rapid progress in this area is promising for the development of a fully integrated e-skin in the near future. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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              On the Analysis of Fingertip Photoplethysmogram Signals

              Photoplethysmography (PPG) is used to estimate the skin blood flow using infrared light. Researchers from different domains of science have become increasingly interested in PPG because of its advantages as non-invasive, inexpensive, and convenient diagnostic tool. Traditionally, it measures the oxygen saturation, blood pressure, cardiac output, and for assessing autonomic functions. Moreover, PPG is a promising technique for early screening of various atherosclerotic pathologies and could be helpful for regular GP-assessment but a full understanding of the diagnostic value of the different features is still lacking. Recent studies emphasise the potential information embedded in the PPG waveform signal and it deserves further attention for its possible applications beyond pulse oximetry and heart-rate calculation. Therefore, this overview discusses different types of artifact added to PPG signal, characteristic features of PPG waveform, and existing indexes to evaluate for diagnoses.
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                Author and article information

                Contributors
                mkhine@uci.edu
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                6 October 2022
                6 October 2022
                2022
                : 12
                : 16772
                Affiliations
                [1 ]GRID grid.266093.8, ISNI 0000 0001 0668 7243, Department of Biomedical Engineering, , University of California Irvine, ; Irvine, CA 92697 USA
                [2 ]GRID grid.417319.9, ISNI 0000 0004 0434 883X, Department of Anesthesiology & Perioperative Care, , University of California, Irvine Medical Center, ; Orange, CA USA
                Article
                19096
                10.1038/s41598-022-19096-6
                9537243
                36202815
                f4577f50-16db-46d9-952a-203a31f0b7d6
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 1 June 2022
                : 24 August 2022
                Funding
                Funded by: National Institutes of Health,United States
                Award ID: T32GM008620
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000957, Alzheimer's Association;
                Award ID: 2019-AARGD-NTF-644466
                Award ID: 2019-AARGD-NTF-644466
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2022

                Uncategorized
                physiology,cardiology,health care,nanoscience and technology
                Uncategorized
                physiology, cardiology, health care, nanoscience and technology

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