Leadless pacemaker implementation at the right atrial appendage apex: An initial preclinical assessment.

OBJECTIVE: This study evaluates the feasibility and efficacy of implanting a leadless pacemaker at the right atrial appendage (RAA) in a preclinical minipig model, aiming to address the limitations of atrial pacing with current leadless devices like the Medtronic Micra, which is typically used for right ventricular implantation. METHODS: Four minipigs, each with a median body weight of 45.8 ± 10.0 kg, underwent placement of the Micra transcatheter pacing system (TPS) via the right femoral vein into the RAA apex. The pacing performance was assessed over 1-week (short-term) and 3-month (long-term) periods. OUTCOMES: The initial findings indicated successful implantation, with satisfactory intrinsic R-wave amplitudes and pacing threshold. In the following period, the sensitivity, threshold, and impedance were stable with time. Notably, upon explanation at 3 months, a deep myocardial penetration by the device was observed, necessitating a redesign for safe long-term use in a growing subject's heart. CONCLUSION: While initial results suggest that RAA apex placement of the Micra TPS is promising for potential inclusion in a dual-chamber pacing system, the issue of myocardial penetration highlights the need for device redesign to ensure safety and effectiveness in long-term applications.

Bi2O2Se-based CBRAM integrated artificial synapse.

Integrating two-dimensional (2D) semiconducting materials into memristor structures has paved the way for emerging 2D materials to be employed in a vast field of memory applications. Bismuth oxyselenide (Bi2O2Se), a 2D material with high electron mobility, has attracted significant research interest owing to its great potential in various fields of advanced applications. Here, we explore the out-of-plane intrinsic switching behavior of few-layered Bi2O2Se via a cross point device for application in conductive bridge random access memory (CBRAM) and artificial synapses for neuromorphic computing. Via state-of-the-art methods, CVD-grown Bi2O2Se nanoplate is applied as a switching material (SM) in an Al/Cu/Bi2O2Se/Pd CBRAM structure. The device exhibits ∼90 consecutive DC cycles with a tight distribution of the SET/RESET voltages under a compliance current (CC) of 1 mA, a retention of over 10 ks, and multilevel switching characteristics showing four distinct states at Vread values of 0.1, 0.2, 0.25, and 0.3 V. Moreover, an artificial synapse is realized with potentiation and depression by modulating the conductance. The switching mechanism is explained via Cu migration through Bi2O2Se based on HRTEM analysis. The present structure shows potential for future integrated memory applications.

Bi2O2Se-Based Bimode Noise Generator for the Application of Generative Adversarial Networks.

In the emerging technology, the generative aversive networks (GANs), randomness, and unpredictability of inputting noises are the keys to the uniqueness, diversity, robustness, and security of the generated images. Compared with deterministic software-based noise generation, hardware-based noise generation introduces physical entropy sources, such as electronic and photonic noises, to add unpredictability. In this study, bimode Bi2O2Se-based noise generators have been demonstrated for the application of GANs. Harnessing its ultrahigh carrier mobility, excellent air stability, marvelous optoelectronic performance, as well as the unique surface resistive switching effect and defect locations in the energy diagram, Bi2O2Se provides a good material platform to easily integrate with multiple device architectures for generating noises in different physical sources. The noise of the black current mode in a photodetector architecture and the random telegraph noise in a memristor mode were measured, characterized, compared, and analyzed. A method of Markov chain equipped with K-means clustering was carried out to calculate the discrete noise states and the transition probability matrix between them. To evaluate the generated properties of the GANs based on the hardware noise source, the inception score and Fréchet inception distance were evaluated.

Oriented lateral growth of two-dimensional materials on c-plane sapphire.

Two-dimensional (2D) semiconducting transition metal dichalcogenides (TMDs) represent the ultimate thickness for scaling down channel materials. They provide a tantalizing solution to push the limit of semiconductor technology nodes in the sub-1 nm range. One key challenge with 2D semiconducting TMD channel materials is to achieve large-scale batch growth on insulating substrates of single crystals with spatial homogeneity and compelling electrical properties. Recent studies have claimed the epitaxy growth of wafer-scale, single-crystal 2D TMDs on a c-plane sapphire substrate with deliberately engineered off-cut angles. It has been postulated that exposed step edges break the energy degeneracy of nucleation and thus drive the seamless stitching of mono-oriented flakes. Here we show that a more dominant factor should be considered: in particular, the interaction of 2D TMD grains with the exposed oxygen-aluminium atomic plane establishes an energy-minimized 2D TMD-sapphire configuration. Reconstructing the surfaces of c-plane sapphire substrates to only a single type of atomic plane (plane symmetry) already guarantees the single-crystal epitaxy of monolayer TMDs without the aid of step edges. Electrical results evidence the structural uniformity of the monolayers. Our findings elucidate a long-standing question that curbs the wafer-scale batch epitaxy of 2D TMD single crystals-an important step towards using 2D materials for future electronics. Experiments extended to perovskite materials also support the argument that the interaction with sapphire atomic surfaces is more dominant than step-edge docking.

Fabry-Perot Oscillation and Resonance Energy Transfer: Mechanism for Ultralow-Threshold Optically and Electrically Driven Random Laser in Quasi-2D Ruddlesden-Popper Perovskites.

The recently emerged metal-halide hybrid perovskite (MHP) possesses superb optoelectronic features, which have obtained great attention in solid-state lighting, photodetection, and photovoltaic applications. Because of its excellent external quantum efficiency, MHP has promising potential for the manifestation of ultralow threshold optically pumped laser. However, the demonstration of an electrically driven laser remains a challenge because of the vulnerable degradation of perovskite, limited exciton binding energy (Eb), intensity quenching, and efficiency drop by nonradiative recombinations. In this work, based on the paradigm of integration of Fabry-Perot (F-P) oscillation and resonance energy transfer, we observed an ultralow-threshold (∼250 µWcm-2) optically pumped random laser from moisture-insensitive mixed dimensional quasi-2D Ruddlesden-Popper phase perovskite microplates. Particularly, we demonstrated an electrically driven multimode laser with a threshold of ∼60 mAcm-2 from quasi-2D RPP by judicious combination of a perovskite/hole transport layer (HTL) and an electron transport layer (ETL) having suitable band alignment and thickness. Additionally, we showed the tunability of lasing modes and color by driving an external electric potential. Performing finite difference time domain (FDTD) simulations, we confirmed the presence of F-P feedback resonance, the light trapping effect at perovskite/ETL, and resonance energy transfer contributing to laser action. Our discovery of an electrically driven laser from MHP opens a useful avenue for developing future optoelectronics.

Bi2O2Se-based integrated multifunctional optoelectronics.

The prominent light-matter interaction in 2D materials has become a pivotal research area that involves either an archetypal study of inherent mechanisms to explore such interactions or specific applications to assess the efficacy of such novel phenomena. With scientifically controlled light-matter interactions, various applications have been developed. Here, we report four diverse applications on a single structure utilizing the efficient photoresponse of Bi2O2Se with precisely tuned multiple optical wavelengths. First, the Bi2O2Se-based device performs the function of optoelectronic memory using UV (λ = 365 nm, 1.1 mW cm-2) for the write-in process with SiO2 as the charge trapping medium followed by a +1 V bias for read-out. Second, associative learning is mimicked with wavelengths of 525 nm and 635 nm. Third, using similar optical inputs, functions of logic gates "AND", "OR", "NAND", and "NOR" are realized with response current and resistance as outputs. Fourth is the demonstration of a 4 bit binary to the decimal converter using wavelengths of 740 nm (LSB), 595 nm, 490 nm, and 385 nm (MSB) as binary inputs and output response current regarded as equivalent decimal output. Our demonstration is a paradigm for Bi2O2Se-based devices to be an integral part of future advanced multifunctional electronic systems.

Easy and Rapid Approach to Obtaining the Binding Affinity of Biomolecular Interactions Based on the Deep Learning Boost.

Recently, the deep learning (DL) dimension of artificial intelligence has received much attention from biochemical researchers and thus has gradually become the key approach adopted in the area of biosensing applications. Studies have shown that the use of DL techniques for sensing can not only shorten the time of data analysis but also significantly increase the accuracy of data analysis and prediction, resulting in the performance improvement of biosensing systems in comparison to conventional methods. However, obtaining reliable equilibrium and rate constants of biomolecular interactions during the detection process remains difficult and time-consuming to date. In this study, we propose a transformed model based on the deep transfer learning and sequence-to-sequence autoencoder that can successfully transfer the SPR sensorgram to the protein-binding constants, that is, the association rate constant (ka) and dissociation rate constant (kd), which provide crucial information to understand the mechanisms of drug action and the functional structures of biomolecules. Experimentally, we first trained and tested the pre-trained model using the Langmuir model which generated ideal SPR sensorgrams and then we fine-tuned the pre-trained model through the augmented SPR sensorgrams which were synthesized by using the synthesized minority oversampling technique (SMOTE) through the moderate-scale experiment. Next, the fine-tuned model was inputted with a short experimental SPR sensorgram that only needs 110 s, and the sensorgram was directly transformed into a reconstructed ideal sensorgram. Finally, the binding kinetic constants, that is, ka and kd, as outputs, were obtained through fitting the reconstructed ideal sensorgram. The results showed that the prediction errors of ka and kd obtained by our model were less than 12 and 24%, respectively. Based on the convenience, accuracy, and reliability of the proposed DL approach, we believe our strategy significantly boosts the feasibility to monitor the binding affinity of antibodies online during production.

Polarity-Differentiated Dielectric Materials in Monolayer Graphene Charge-Regulated Field-Effect Transistors for an Artificial Reflex Arc and Pain-Modulation System of the Spinal Cord.

The nervous system is a vital part of organisms to survive and it endows them with remarkable abilities, such as perception, recognition, regulation, learning, and decision-making, by intertwining myriad neurons. To realize such outstanding efficacies and functions, many artificial devices and systems have been investigated to emulate the operating principles of the nervous system. Here, an artificial reflex arc (ARA) and artificial pain modulation system (APMS) are proposed to imitate the unconscious behaviors of the spinal cord. Gdx Oy - and Alx Oy -based charge-regulated field-effect transistors (CRFETs) with a monolayer graphene channel are fabricated and adopted as inhibitory and excitatory synapses, respectively, under the same pulse signals to mimic the biological reflex arc through a connection with a poly(vinylidene fluoride-co-trifluoroethylene)-based actuator. Additionally, a memristor is integrated with a CRFET as the interneuron to regulate the Dirac point by controlling the voltage drop on the graphene channel, analogous to the descending pain-inhibition system in the spinal cord, to prevent excessive pain perception. The proposed ARA and APMS provide a significant step forward to realizing the functions of the nervous system, giving promising potential for developing future intelligent alarm systems, neuroprosthetics, and neurorobotics.

α-Fe2O3 Nanoparticles Aided-Dual Conversion for Self-Powered Bio-Based Photodetector.

Eco-friendly energy harvesting from the surrounding environment has been triggered extensive researching enthusiasm due to the threat of global energy crisis and environmental pollutions. By the conversion of mechanical energy that is omnipresent in our environment into electrical energy, triboelectric nanogenerator (TENG) can potentially power up small electronic devices, serves as a self-powered detectors and predominantly, it can minimize the energy crisis by credibly saving the traditional non-renewable energy. In this study, we present a novel bio-based TENG comprising PDMS/α-Fe2O3 nanocomposite film and a processed human hair-based film, that harvests the vibrating energy and solar energy simultaneously by the integration of triboelectric technology and photoelectric conversion techniques. Upon illumination, the output voltage and current signals rapidly increased by 1.4 times approximately, compared to the dark state. Experimental results reveal that the photo-induced enhancement appears due to the effective charge separation depending on the photosensitivity of the hematite nanoparticles (α-Fe2O3 nanoparticles) over the near ultraviolet (UV), visible and near infrared (IR) regions. Our work provides a new approach towards the self-powered photo-detection, while developing a propitious green energy resource for the circular bio-economy.

Bi2O2Se-Based True Random Number Generator for Security Applications.

The fast development of the Internet of things (IoT) promises to deliver convenience to human life. However, a huge amount of the data is constantly generated, transmitted, processed, and stored, posing significant security challenges. The currently available security protocols and encryption techniques are mostly based on software algorithms and pseudorandom number generators that are vulnerable to attacks. A true random number generator (TRNG) based on devices using stochastically physical phenomena has been proposed for auditory data encryption and trusted communication. In the current study, a Bi2O2Se-based memristive TRNG is demonstrated for security applications. Compared with traditional metal-insulator-metal based memristors, or other two-dimensional material-based memristors, the Bi2O2Se layer as electrode with non-van der Waals interface, high carrier mobility, air stability, extreme low thermal conductivity, as well as vertical surface resistive switching shows intrinsic stochasticity and complexity in a memristive true analogue/digital random number generation. Moreover, those analogue/digital random number generation processes are proved to be resilient for machine learning prediction.

Assessing Plasma Levels of α-Synuclein and Neurofilament Light Chain by Different Blood Preparation Methods.

The potential biomarkers of Parkinson's disease are α-synuclein and neurofilament light chain (NFL). However, inconsistent preanalytical preparation of plasma could lead to variations in levels of these biomarkers. Different types of potassium salts of EDTA and different centrifugation temperatures during plasma preparation may affect the results of α-synuclein and NFL measurements. In this study, we prepared plasma from eight patients with Parkinson's disease (PD) and seven healthy controls (HCs) by using di- and tri-potassium (K2- and K3-) EDTA tubes and recruited a separated cohort with 42 PD patients and 40 HCs for plasma samples prepared from whole blood by centrifugation at room temperature and 4°C, respectively, in K2-EDTA tubes. The plasma levels of α-synuclein and NFL in K2- and K3-EDTA were similar. However, the levels of α-synuclein in the plasma prepared at 4°C (101.57 ± 43.43 fg/ml) were significantly lower compared with those at room temperature (181.23 ± 196.31 fg/ml, P < 0.001). Room temperature preparation demonstrated elevated plasma levels of α-synuclein in PD patients (256.6 ± 50.2 fg/ml) compared with the HCs (102.1 ± 0.66 fg/ml, P < 0.001), whereas this increase in PD was not present by preparation at 4°C. Both plasma preparations at room temperature and 4°C demonstrated consistent results of NFL, which are increased in PD patients compared with HCs. Our findings confirmed that K2- and K3-EDTA tubes were interchangeable for analyzing plasma levels of α-synuclein and NFL. Centrifugation at 4°C during plasma preparation generates considerable reduction and variation of α-synuclein level that might hinder the detection of α-synuclein level changes in PD.

Enhanced Plasmonic Biosensor Utilizing Paired Antibody and Label-Free Fe3O4 Nanoparticles for Highly Sensitive and Selective Detection of Parkinson's α-Synuclein in Serum.

Parkinson's disease (PD) is an acute and progressive neurodegenerative disorder, and diagnosis of the disease at its earliest stage is of paramount importance to improve the life expectancy of patients. α-Synuclein (α-syn) is a potential biomarker for the early diagnosis of PD, and there is a great need to develop a biosensing platform that precisely detects α-syn in human body fluids. Herein, we developed a surface plasmon resonance (SPR) biosensor based on the label-free iron oxide nanoparticles (Fe3O4 NPs) and paired antibody for the highly sensitive and selective detection of α-syn in serum samples. The sensitivity of the SPR platform is enhanced significantly by directly depositing Fe3O4 NPs on the Au surface at a high density to increase the decay length of the evanescent field on the Au film. Moreover, the utilization of rabbit-type monoclonal antibody (α-syn-RmAb) immobilized on Au films allows the SPR platform to have a high affinity-selectivity binding performance compared to mouse-type monoclonal antibodies as a common bioreceptor for capturing α-syn molecules. As a result, the current platform has a detection limit of 5.6 fg/mL, which is 20,000-fold lower than that of commercial ELISA. The improved sensor chip can also be easily regenerated to repeat the α-syn measurement with the same sensitivity. Furthermore, the SPR sensor was applied to the direct analysis of α-syn in serum samples. By using a format of paired α-syn-RmAb, the SPR sensor provides a recovery rate in the range from 94.5% to 104.3% to detect the α-syn in diluted serum samples precisely. This work demonstrates a highly sensitive and selective quantification approach to detect α-syn in human biofluids and paves the way for the future development in the early diagnosis of PD.

Charge trapping with α-Fe2O3 nanoparticles accompanied by human hair towards an enriched triboelectric series and a sustainable circular bioeconomy.

This work reports a new approach to amending polydimethylsiloxane (PDMS) by supporting α-Fe2O3 nanoparticles (NPs), thereby generating a material suitable for use as a negative triboelectric material. Additionally, human hair exhibits a profound triboelectrification effect and is a natural regenerative substance, and it was processed into a film to be used as a positive triboelectric material. Spatial distribution of α-Fe2O3 NPs, the special surface morphologies of a negative tribological layer containing nano-clefts with controlled sizes and a valley featuring a positive tribolayer based on human hair made it possible to demonstrate facile and scalable fabrication of a triboelectric nanogenerator (TENG) presenting enhanced performance; this nanogenerator produced a mean peak-to-peak voltage of 370.8 V and a mean output power density of 247.2 µW cm-2 in the vertical contact-separation mode. This study elucidates the fundamental charge transfer mechanism governing the triboelectrification efficiency and its use in harvesting electricity for the further development of powerful TENGs suitable for integration into wearable electronics and self-charging power cells, and the work also illustrates a recycling bioeconomy featuring systematic utilization of human hair waste as a regenerative resource for nature and society.

Flexible Layered-Graphene Charge Modulation for Highly Stable Triboelectric Nanogenerator.

The continuous quest to enhance the output performance of triboelectric nanogenerators (TENGs) based on the surface charge density of the tribolayer has motivated researchers to harvest mechanical energy efficiently. Most of the previous work focused on the enhancement of negative triboelectric charges. The enhancement of charge density over positive tribolayer has been less investigated. In this work, we developed a layer-by-layer assembled multilayer graphene-based TENG to enhance the charge density by creatively introducing a charge trapping layer (CTL) Al2O3 in between the positive triboelectric layer and conducting electrode to construct an attractive flexible TENG. Based on the experimental results, the optimized three layers of graphene TENG (3L-Gr-TENG) with CTL showed a 30-fold enhancement in output power compared to its counterpart, 3L-Gr-TENG without CTL. This remarkably enhanced performance can be ascribed to the synergistic effect between the optimized graphene layers with high dielectric CTL. Moreover, the device exhibited outstanding stability after continuous operation of >2000 cycles. Additionally, the device was capable of powering 20 green LEDs and sufficient to power an electronic timer with rectifying circuits. This research provides a new insight to improve the charge density of Gr-TENGs as energy harvesters for next-generation flexible electronics.

Bi2O2Se-Based Memristor-Aided Logic.

The implementation of two-dimensional materials into memristor architectures has recently been a new research focus by taking advantage of their atomic thickness, unique lattice, and physical and electronic properties. Among the van der Waals family, Bi2O2Se is an emerging ternary two-dimensional layered material with ambient stability, suitable band structure, and high conductivity that exhibits high potential for use in electronic applications. In this work, we propose and experimentally demonstrate a Bi2O2Se-based memristor-aided logic. By carefully tuning the electric field polarity of Bi2O2Se through a Pd contact, a reconfigurable NAND gate with zero static power consumption is realized. To provide more knowledge on NAND operation, a kinetic Monte Carlo simulation is carried out. Because the NAND gate is a universal logic gate, cascading additional NAND gates can exhibit versatile logic functions. Therefore, the proposed Bi2O2Se-based MAGIC can be a promising building block for developing next-generation in-memory logic computers with multiple functions.

Surface Acoustic Wave Sensor for C-Reactive Protein Detection.

A surface acoustic wave (SAW) sensor was investigated for its application in C-reactive protein (CRP) detection. Piezoelectric lithium niobate (LiNbO3) substrates were used to study their frequency response characteristics in a SAW sensor with a CRP sensing area. After the fabrication of the SAW sensor, the immobilization process was performed for CRP/anti-CRP interaction. The CRP/anti-CRP interaction can be detected as mass variations in the sensing area. These mass variations may produce changes in the amplitude of sensor response. It was clearly observed that a CRP concentration of 0.1 µg/mL can be detected in the proposed SAW sensor. A good fitting linear relationship between the detected insertion loss (amplitude) and the concentrations of CRP from 0.1 µg/mL to 1 mg/mL was obtained. The detected shifts in the amplitude of insertion loss in SAW sensors for different CRP concentrations may be useful in the diagnosis of risk of cardiovascular diseases.

Breath Ammonia Is a Useful Biomarker Predicting Kidney Function in Chronic Kidney Disease Patients.

Chronic kidney disease (CKD) is a public health problem and its prevalence has increased worldwide; patients are commonly unaware of the condition. The present study aimed to investigate whether exhaled breath ammonia via vertical-channel organic semiconductor (V-OSC) sensor measurement could be used for rapid CKD screening. We enrolled 121 CKD stage 1-5 patients, including 19 stage 1 patients, 26 stage 2 patients, 38 stage 3 patients, 21 stage 4 patients, and 17 stage 5 patients, from July 2019 to January 2020. Demographic and laboratory data were recorded. The exhaled ammonia was collected and rapidly measured by the V-OSC sensor to correlate with kidney function. Results showed no significant difference in age, sex, body weight, hemoglobin, albumin level, and comorbidities in different CKD stage patients. Correlation analysis demonstrated a good correlation between breath ammonia and blood urea nitrogen levels, serum creatinine levels, and estimated glomerular filtration rate (eGFR). Breath ammonia concentration was significantly elevated with increased CKD stage compared with the previous stage (CKD stage 1/2/3/4/5: 636 ± 94; 1020 ± 120; 1943 ± 326; 4421 ± 1042; 12781 ± 1807 ppb, p < 0.05). The receiver operating characteristic curve analysis showed an area under the curve (AUC) of 0.835 (p < 0.0001) for distinguishing CKD stage 1 from other CKD stages at 974 ppb (sensitivity, 69%; specificity, 95%). The AUC was 0.831 (p < 0.0001) for distinguishing between patients with/without eGFR < 60 mL/min/1.73 m2 (cutoff 1187 ppb: sensitivity, 71%; specificity, 78%). At 886 ppb, the sensitivity increased to 80% but the specificity decreased to 69%. This value is suitable for kidney function screening. Breath ammonia detection with V-OSC is a real time, inexpensive, and easy to administer measurement device for screening CKD with reliable diagnostic accuracy.

Element Code from Pseudopotential as Efficient Descriptors for a Machine Learning Model to Explore Potential Lead-Free Halide Perovskites.

The rapid development of machine learning has proven its potential in material science. To acquire an accurate and promising result, the choice of descriptor plays an essential role in dictating the model performance. In this work, we introduce a set of novel descriptors, Element Code, which is generated from pseudopotential. Using a variational autoencoder to perform unsupervised learning, the produced Element Code is verified to contain representative information on elements. Attributed to the successful extraction of information from pseudopotential, Element Code can serve as the primary descriptor for the machine learning model. We construct a model using Element Code as the sole descriptor to predict the bandgap of a lead-free double halide perovskite, and an accuracy of 0.951 and mean absolute error of 0.266 eV are achieved. We believe our work can offer insights into selecting lead-free halide perovskites and establish a paradigm of exploring new materials.

Achieving High-Performance Perovskite Photovoltaic by Morphology Engineering of Low-Temperature Processed Zn-Doped TiO2 Electron Transport Layer.

Perovskite solar cells (PSCs) have become one of the most promising renewable energy converting devices. However, in order to reach a sufficiently high power conversion efficiency (PCE), the PSCs typically require a high-temperature sintering process to prepare mesostructured TiO2 as an efficient electron transport layer (ETL), which prohibits the PSCs from commercialization in the future. This work investigates a low-temperature synthesis of TiO2 nanocrystals and introduces a two-fluid spray coating process to produce a nanostructured ETL for the following deposition of perovskite layer. The temperature during the whole deposition process can be maintained under 150 °C. Compared to the typical planar TiO2 layer, the perovskite layer fabricated on a nanostructured TiO2 layer shows uniform compactness, preferred orientation, and high crystallinity, leading to reproducible and promising device performance. The detail mechanisms are revealed by the contact angle test, morphology characterization, grazing incident wide angle X-Ray scattering measurement, and space charge limited currents analysis. Finally, optimized device performance can be achieved through adequate Zn doping in the TiO2 layer, demonstrating an average PCE of 19.87% with champion PCE of 21.36%. The efficiency can maintain over 80% of its original value after 3000 h storage in ambient atmosphere. This study suggests a promising approach to offer high-efficiency PSCs using the low-temperature process.

Flexible Textile-Based Pressure Sensing System Applied in the Operating Room for Pressure Injury Monitoring of Cardiac Operation Patients.

Pressure injury is the most important issue facing paralysis patients and the elderly, especially in long-term care or nursing. A new interfacial pressure sensing system combined with a flexible textile-based pressure sensor array and a real-time readout system improved by the Kalman filter is proposed to monitor interfacial pressure progress in the cardiac operation. With the design of the Kalman filter and parameter optimization, noise immunity can be improved by approximately 72%. Additionally, cardiac operation patients were selected to test this developed system for the direct correlation between pressure injury and interfacial pressure for the first time. The pressure progress of the operation time was recorded and presented with the visible data by time- and 2-dimension-dependent characteristics. In the data for 47 cardiac operation patients, an extreme body mass index (BMI) and significantly increased pressure after 2 h are the top 2 factors associated with the occurrence of pressure injury. This methodology can be used to prevent high interfacial pressure in high-risk patients before and during operation. It can be suggested that this system, integrated with air mattresses, can improve the quality of care and reduce the burden of the workforce and medical cost, especially for pressure injury.