Medical Instruments Research Articles

Concepts of reproductive behaviour and motherhood in Soviet cinema of the 1920–1930s

The article examines representations of motherhood and reproductive behaviour in Soviet cinema from Revolution 1917 to the mid-1930s (films “Children are the Flowers of Life”, “The Road to Happiness”, “Katka's Reinette Apples”, “Bed and Sofa”, etc.) through the study of the reproductive choice mechanism, demonstration of pregnancy, childbirth and child care. Conclusions are drawn about the presence of several main conceptual frameworks, such as happy Soviet motherhood as opposed to pre-revolutionary motherhood; the unreliability of the parental function of the biological father, but the support of the collective and the acquisition of a new partner, which means the creation of a two-parents family; transition from the demonstration of medical instruments and the process of childbirth to the withdrawal of this segment; etc.

Telehealth Challenges, Opportunities, and Policy Recommendations for Rural Older Adults Living with HIV in the United States

ABSTRACT Over one million people in the United States (U.S.) are living with HIV. People living with HIV in the rural South experience delayed HIV treatment and increased mortality risks. Access challenges and HIV stigma exacerbate care disengagement for rural people living with HIV (PLH). This study examines the applicability and feasibility of telehealth to provide HIV care for older adults in the rural U.S. South. Semi-structured interviews were conducted with 27 key informants with expertise in HIV care and community engagement in high rural HIV burden states. Results indicate that telehealth challenges exist for older rural PLH to receive HIV care, such as lack of internet access and low technology literacy. Phone calls can be a simple and effective telehealth option for older rural PLH, as they align with their care preferences, mitigate care barriers, and show promise increasing care engagement. When warranted, complex telehealth options for older rural PLH require tailored approaches, such as portable medical instruments allowing real-time data sharing during home visits or tablet distribution from the clinic. Findings suggest that policy makers and providers support the reimbursement and use of audio-only telehealth services, expand broadband infrastructure and affordability in rural areas, and implement tailored telehealth interventions.

Enhanced antimicrobial efficacy of hydroxyapatite-based composites for healthcare applications

Hydroxyapatite (HAp) and hydroxyapatite-based materials show promising potential in the healthcare sector due to their distinctive properties such as biocompatibility, antimicrobial efficacy, non-toxicity, and robust mechanical characteristics. This makes HAp materials play an important role in hindering infection spreading in healthcare provider institutions. This study assesses the antimicrobial efficacy of the developed hydroxyapatite-based composites incorporating copper, zinc, and silver nanoparticles. The synthesized HAp and its modified composite variants (Cu/HAp, Zn/HAp, and Ag/HAp) with varying ratios ranging from 0 to 15% (wt) were characterized using XRD, XPS, SEM, and TEM analyses. Furthermore, the antibacterial and antifungal properties of the synthesized HAp and HAp-based composites were evaluated. The antibacterial effectiveness of the HAp and its composites was evaluated using a modified disc diffusion test, where the resulting inhibition zones on the agar surface were observed. All the HAp and HAp-based composites (HAp, Cu/HAp, Zn/HAp, and Ag/HAp materials) elicited in the formation of inhibitory zones. The most substantial inhibition values were observed for the 5% Ag/HAp formulation, with values of 19.7 and 13.8, against E. coli and S. aureus, respectively. The 5% Ag/HAp concentration may strike an ideal balance, providing high antimicrobial activity without adverse effects on biocompatibility or material stability. These findings underscore the recommendation of the proposed HAp-based composites for infection control measures through their application on medical instruments, textiles, healthcare personnel attire, and patient garments.

Influence of Exposure Distance on Light Irradiance of Dental Curing Lamps in Various Operating Modes

The efficiency of photopolymerisation significantly impacts achieving a high degree of conversion and, consequently, determines the success and strength of resin-based composite (RBC) restorations. The study aimed to measure the light irradiance of selected LED curing lamps, taking into account various exposure modes and the increased distance of the light source from the radiometer surface. The study material consisted of 21 LED polymerisation lamps of a single type (Woodpecker Medical Instrument Co., Guilin, China) with three exposure modes: standard, soft start, and pulse. During the measurement, the distance was increased from 0 mm to 8 mm, every 2 mm. Light irradiance measurements were made with a Bluephase Meter II photometer (Ivoclar Vivadent, Opfikon, Switzerland). Increasing the distance affected the soft mode the most, causing a significant drop in light irradiance on the photometer. Standard mode coped best with distance. Even at a distance of 0 mm, the soft start mode does not reach the power of the standard and pulse modes. The standard mode seems to be the most clinically effective, especially if it is planned to polymerise a material in a deep cavity. The soft start mode, as the least resistant to increasing distance, is recommended for use in front teeth or the cervical area.

Personalized blood pressure estimation using multiview fusion information of wearable physiological signals and transfer learning

Continuous blood pressure (BP) monitoring is crucial for individual health management, yet the significant inter-individual variations among patients pose challenges to achieving precision medicine. In response to this issue, we propose a parallel cross-hybrid architecture that integrates a convolutional neural network backbone and a Mix-Transformer backbone. This model, grounded in multi-view physiological signals and personalized fine-tuning strategies, aims to estimate BP, facilitating the capture of physiological information across diverse receptive fields and enhancing network expressive capabilities. Our proposed architecture exhibits superior performance in estimating systolic blood pressure and diastolic blood pressure, with average absolute errors of 3.94 mmHg and 2.24 mmHg, respectively. These results surpass existing baseline models and align with the standards set by the British Hypertension Society, the Association for the Advancement of Medical Instrumentation, and the Institute of Electrical and Electronics Engineers for BP measurement. Additionally, this study explores a personalized model fine-tuning strategy by adjusting specific layers and incorporating individual information, presenting an optimal solution. The model's generalization ability is validated through transfer learning across databases (public and self-made). To enhance the proposed architecture's usability in wearable devices, this study employs a knowledge distillation strategy for model lightweighting, with preliminary application in our designed real-time BP estimation system. This study provides an efficient and accurate solution for personalized BP estimation, exhibiting broad potential applications.

Long‐Term Monitoring of ApoE4 within Aqueous Humor Using Intraocular Lenses Containing Target‐Responsive Inverse Opal Hydrogel

Neurodegenerative diseases, including Alzheimer's disease (AD), pose significant challenges to global healthcare because of their irreversible postsymptomatic progression. Conventional radiographic techniques have limitations in early detection, owing to the time lapse between symptom recognition by individuals and precise inspection using medical instruments. Current research explores ophthalmic approaches to address this gap, investigating the physiological link between ocular health and brain diseases. Intraocular lenses (IOLs), widely used in cataract and refractive surgeries, provide a safe and minimally invasive platform for the continuous monitoring of neurodegenerative disease biomarkers, including those associated with AD. By integrating biomolecule‐responsive sensors with IOLs, it becomes feasible to achieve early diagnosis and long‐term, noninvasive monitoring postimplantation. Herein, a fluorescently labeled inverse opal hydrogel (FIOH) is merged with IOLs for ApoE4 detection, a key risk factor for AD. The permeability and inherent photonic properties of FIOH facilitate the cumulative enhancement of the fluorescence signal. In a simulation of the aqueous humor circulation, the detection limit for ApoE4 is determined to be 0.1 nM. Therefore, FIOH‐integrated IOLs hold promise not only for early detection but also for providing a reliable platform for the continuous, noninvasive monitoring of neurodegenerative diseases after the initial, minimally invasive implantation.

A multi-adaptive neuro-fuzzy inference system with variable thresholds for heartbeat classification

Various heart disorders are non-invasively diagnosed using electrocardiograms (ECGs). An ECG records a variety of waveforms, including P, QRS, and T waves, which represent the electrical activity of the human heart. Cardiovascular diseases are diagnosed by examining the length, form, and spacing of these waveforms. This research develops a multi-adaptive, neuro-fuzzy inference system (MANFIS), enhanced by a variable threshold approach, to enhance heartbeat classification accuracy. The MIT-BIH arrhythmia database was utilized, and seven features were extracted from each record. A subtractive clustering method was employed to prepare the inputs for the MANFIS, enabling heartbeat classification. By applying a variable threshold to the MANFIS outputs, classification accuracy was further enhanced. The proposed method, termed variable-threshold MANFIS, can separately detect normal sinus rhythm, left bundle branch block, right bundle branch block, premature ventricular contraction, atrial premature condition, and paced beat. This is achieved using six different ANFIS classifiers, each with its own threshold. The system was evaluated, achieving an accuracy of 98.33%, a sensitivity of 93.12%, a specificity of 99.66%, a precision of 98.33, and an F1-score of 95.44. A distinct feature of this machine-learning-based model is its controllable threshold, which delivers promising results across all training, testing, and validation datasets. The proposed diagnostic system is applicable in new automated medical instrumentation and serves as a valuable tool in cardiology.

Bactericidal effect of direct and indirect plasma for medical instruments: Comparative experimental study

Bactericidal effect of direct and indirect plasma for medical instruments: Comparative experimental study

Training and education of operating room nurses in robot-assisted surgery: a systematic review.

With the introduction of robot-assisted surgery, the role and responsibility of the operating room nurses have been expanded. The surgical team for robotic-assisted surgery depends on the ability of the operating room nurses to operate and handle the robotic system before, during, and after procedures. However, operating room nurses must acquire the necessary competencies for robotic-assisted surgery. We performed a systematic review using the databases MEDLINE and EMBASE to review the evidence on educating and training operating room nurses in robot-assisted surgery. Studies describing operating room nurses' training and team-training with operating room nurses for robot-assisted surgery were included. The Medical Education Research Study Quality Instrument (MERSQI) and the Newcastle-Ottawa Scale-Education (NOS-E) were used to evaluate the quality of the included studies. We identified 3351 potential studies and included 16 in the final synthesis. Nine studies focused on team-training in robot-assisted surgery: four focused solely on training for operating room nurses, and only three on operating room nurses as first assistants in robot-assisted surgery. Most studies examined team-training in RAS, including OR nurses, focused on emergency situations and conversion to an open procedure. Only a few studies addressed other competencies relevant to OR nurses in RAS. No randomized controlled trials were identified. Only a few studies used pre- and post-testing, and only one examined clinical outcomes. The quality assessment of the included studies was moderate to low, with a median MERSQI score of 10.3 and a median NOS-E score of 2. There is sparse research on the education of operating room nurses in robot-assisted surgery, and the literature emphasizes the training of surgeons. More research is needed to develop evidence-based training for operating room nurses in robot-assisted surgery.

Impact of Skin Pigmentation on Pulse Oximetry Blood Oxygenation and Wearable Pulse Rate Accuracy: Systematic Review and Meta-Analysis.

Photoplethysmography (PPG) is a technology routinely used in clinical practice to assess blood oxygenation (SpO2) and pulse rate (PR). Skin pigmentation may influence accuracy, leading to health outcomes disparities. This systematic review and meta-analysis primarily aimed to evaluate the accuracy of PPG-derived SpO2 and PR by skin pigmentation. Secondarily, we aimed to evaluate statistical biases and the clinical relevance of PPG-derived SpO2 and PR according to skin pigmentation. We identified 23 pulse oximetry studies (n=59,684; 197,353 paired SpO2-arterial blood observations) and 4 wearable PR studies (n=176; 140,771 paired PPG-electrocardiography observations). We evaluated accuracy according to skin pigmentation group by comparing SpO2 accuracy root-mean-square values to the regulatory threshold of 3% and PR 95% limits of agreement values to +5 or -5 beats per minute (bpm), according to the standards of the American National Standards Institute, Association for the Advancement of Medical Instrumentation, and the International Electrotechnical Commission. We evaluated biases and clinical relevance using mean bias and 95% CI. For SpO2, accuracy root-mean-square values were 3.96%, 4.71%, and 4.15%, and pooled mean biases were 0.70% (95% CI 0.17%-1.22%), 0.27% (95% CI -0.64% to 1.19%), and 1.27% (95% CI 0.58%-1.95%) for light, medium, and dark pigmentation, respectively. For PR, 95% limits of agreement values were from -16.02 to 13.54, from -18.62 to 16.84, and from -33.69 to 32.54, and pooled mean biases were -1.24 (95% CI -5.31 to 2.83) bpm, -0.89 (95% CI -3.70 to 1.93) bpm, and -0.57 (95% CI -9.44 to 8.29) bpm for light, medium, and dark pigmentation, respectively. SpO2 and PR measurements may be inaccurate across all skin pigmentation groups, breaching U.S. Food and Drug Administration guidance and industry standard thresholds. Pulse oximeters significantly overestimate SpO2 for both light and dark skin pigmentation, but this overestimation may not be clinically relevant. PRs obtained from wearables exhibit no statistically or clinically significant bias based on skin pigmentation.

Materials for semiconductor nanowires in nanoscale photonic and electronic devices

Abstract Many aspects of civilization are impacted by electronic and optoelectronic equipment, including medical instruments, communications, computing, multimedia systems, and basic home appliances. the development of nanoscale devices has garnered significant attention due to the increasing demand for smaller, more powerful, and efficient systems across various industries. Nanoscale devices operate at the nanometer scale, typically involving structures and components with dimensions on the order of 1 to 100 nanometers. As a potent class of materials, semiconductor nanowires are creating a lot of new possibilities for innovative nanoscale photonic and electrical devices through carefully regulated development and organization. the exploration of electronic and optoelectronic nanodevices, along with integrated arrays, opens up a rich landscape of possibilities across various technological domains. This research not only pushes the boundaries of miniaturization but also paves the way for innovative applications in electronics, photonics, sensing, and emerging fields like quantum and neuromorphic computing that hold the potential for numerous applications in the future.

Corrosion resistance and long-term antibacterial performance of ZnO-Al2O3 nanocomposite coatings on aluminum alloy

Anodic aluminum oxide-zinc (AAO-Zn) coatings were prepared on aluminum (Al) alloy substrates through anodization and nZnO deposition. Further heat treatment at various temperature is applied to the composite coatings. Among the samples, AZ-250 sample showed lower corrosion current density (1.127 × 10−8 A/cm2) and higher charge-transfer resistance (4.65 × 105 Ω cm2) compared to the AZ-150 and AZ-350 samples. At 250 °C, a greater incorporation of nZnO into the AAO layer facilitated the fusion of ZnO with aluminum oxide, resulting in a denser and more protective coating. The antibacterial research revealed AZ-250 sample achieved a 100 % reduction of S. aureus and 97.9 % of E. coli within 2 h. Even after 40 days of air exposure, the AZ-250 sample maintained high antibacterial effectiveness due to ZnO attachment and sustained Zn2⁺ release from the nanoporous AAO structure. This nanocomposite is suitable for applications in heat exchangers, medical instrument casings, and transport structure.

Are previously validated blood pressure self-measurement devices accepted under the Universal Standard? A systematic review.

This study aimed to analyze whether oscillometric blood pressure devices validated for the general population may be considered approved under Universal Standard criteria. A systematic review was conducted, with searches in nine databases, up to September 2023, including 32 validation studies of noninvasive arm cuff devices for self-measurement. The British Hypertension Society protocol was most common (68%), followed by the Association for the Advancement of Medical Instrumentation (40%). Most devices met Universal Standard criterion 1, but only 17 (53%) met criterion 2. Few studies contained details about the choice of cuffs, the number of participants by arm circumference, or the differences between methods by cuff subgroup. Due to the considerable differences between validation protocols, 53% of the devices analyzed were approved under the Universal Standard. The study contributes to expanding the validated pool of self-measurement devices under the Universal Standard.

Radiation Detectors and Sensors in Medical Imaging.

Medical imaging instrumentation design and construction is based on radiation sources and radiation detectors/sensors. This review focuses on the detectors and sensors of medical imaging systems. These systems are subdivided into various categories depending on their structure, the type of radiation they capture, how the radiation is measured, how the images are formed, and the medical goals they serve. Related to medical goals, detectors fall into two major areas: (i) anatomical imaging, which mainly concerns the techniques of diagnostic radiology, and (ii) functional-molecular imaging, which mainly concerns nuclear medicine. An important parameter in the evaluation of the detectors is the combination of the quality of the diagnostic result they offer and the burden of the patient with radiation dose. The latter has to be minimized; thus, the input signal (radiation photon flux) must be kept at low levels. For this reason, the detective quantum efficiency (DQE), expressing signal-to-noise ratio transfer through an imaging system, is of primary importance. In diagnostic radiology, image quality is better than in nuclear medicine; however, in most cases, the dose is higher. On the other hand, nuclear medicine focuses on the detection of functional findings and not on the accurate spatial determination of anatomical data. Detectors are integrated into projection or tomographic imaging systems and are based on the use of scintillators with optical sensors, photoconductors, or semiconductors. Analysis and modeling of such systems can be performed employing theoretical models developed in the framework of cascaded linear systems analysis (LCSA), as well as within the signal detection theory (SDT) and information theory.

Fiber Bragg Grating Pulse and Systolic Blood Pressure Measurement System Based on Mach-Zehnder Interferometer.

A fiber Bragg grating (FBG) pulse and systolic blood pressure (SBP) measurement system based on the edge-filtering method is proposed. The edge filter is the Mach-Zehnder interferometer (MZI) fabricated by two fiber couplers with a linear slope of 52.45 dBm/nm. The developed system consists of a broadband light source, an edge filter, fiber Bragg gratings (FBGs), a coarse wavelength-division multiplexer (CWDM), and signal-processing circuits based on a field-programmable gate array (FPGA). It can simultaneously measure pulse pulsations of the radial artery in the wrist at three positions: Cun, Guan and Chi. The SBP can be calculated based on the pulse transit time (PTT) principle. The measurement results compared to a standard blood pressure monitor showed the mean absolute error (MAE) and standard deviation (STD) of the SBP were 0.93 ± 3.13 mmHg. The system meets the requirements of the Association for the Advancement of Medical Instrumentation (AAMI) equipment standards. The proposed system can achieve continuous real-time measurement of pulse and SBP and has the advantages of fast detection speed, stable performance, and no compression sensation for subjects. The system has important application value in the fields of human health monitoring and medical device development.

BP-Diff: a conditional diffusion model for cuffless continuous BP waveform estimation using U-Net.

Continuous monitoring of blood pressure (BP) is crucial for daily healthcare. Although invasive methods provide accurate continuous BP measurements, they are not suitable for routine use. Photoplethysmography (PPG), a non-invasive technique that detects changes in blood volume within the microcirculation using light, shows promise for BP measurement. The primary goal of this study is to develop a novel cuffless method based on PPG for accurately estimating continuous BP.
Approach. We introduce BP-Diff, an end-to-end method for cuffless continuous BP waveform estimation utilizing a conditional diffusion probability model combined with a U-Net architecture. This approach takes advantage of the stochastic properties of diffusion models and the strong feature representation capabilities of U-Net. It integrates the continuous BP waveform as the initial status and uses the PPG signal and its derivatives as conditions to guide the training and sampling process.
Main results. BP-Diff was evaluated using both uncalibrated and calibrated schemes. The results indicate that, when uncalibrated, BP-Diff can accurately track BP dynamics, including peak and valley positions, as well as timing. After calibration, BP-Diff achieved highly accurate BP estimations. The mean absolute error (MAE) of the estimated BP waveforms, along with the systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean arterial pressure (MAP) from the calibrated BP-Diff model, were 2.99 mmHg, 2.6 mmHg, 1.4 mmHg, and 1.44 mmHg, respectively. Consistency tests, including Bland-Altman analysis and Pearson correlation, confirmed its high reliability compared to reference BP. BP-Diff meets the American Association for Medical Instrumentation (AAMI) standards and has achieved a Grade A from the British Hypertension Society (BHS).
Significance. This study utilizes PPG signals to develop a novel cuffless continuous BP measurement method, demonstrating superiority over existing approaches. The method is suitable for integration into wearable devices, providing a practical solution for continuous BP monitoring in everyday healthcare.

Comparison of the ClearSight™ finger cuff monitor versus invasive arterial blood pressure measurement in elective cardiac surgery patients: a prospective observational study.

To determine the acceptability of the ClearSight™ system (Edwards Lifesciences Corp., Irvine, CA, USA) for continuous blood pressure monitoring during elective cardiac surgery compared with arterial catheterization. We enrolled 30 patients undergoing elective cardiac surgery in a prospective observational study. Blood pressure measurements were recorded every 10 sec intraoperatively. We determined agreement based on the Association for the Advancement of Medical Instrumentation (AAMI) recommendations. Statistical analysis included fixed bias (difference of measurements between methods), percentage error (accuracy between ClearSight measurement and expected measurement from arterial line), and interchangeability (ability to substitute ClearSight monitor without effecting overall outcome of analysis). We used a paired samples t test to compare the time required for placing each monitor. We found fixed bias in the differences between the ClearSight monitor and invasive arterial blood pressure measurement in systolic blood pressure (SBP; mean difference, 8.7; P < 0.001) and diastolic blood pressure (DBP; mean difference, -2.2; P < 0.001), but not in mean arterial pressure (MAP; mean difference, -0.5; P < 0.001). Bland-Altman plots showed that the means of the limits of agreement were greater than 5mm Hg for SBP, DBP, and MAP. The percentage errors for SBP, DBP, and MAP were lower than the cutoff we calculated from the invasive arterial blood pressure measurements. Average interchangeability rates were 38% for SBP, 50% for DBP, and 50% for MAP. Placement of the ClearSight finger cuff was significantly faster compared with arterial catheterization (mean [standard deviation], 1.7 [0.6] min vs 5.6 [4.1] min; P < 0.001). In this prospective observational study, we did not find the ClearSight system to be an acceptable substitute for invasive arterial blood pressure measurement in elective cardiac surgery patients according to AAMI guidelines. Nevertheless, based on statistical standards, there is evidence to suggest otherwise. ClinicalTrials.gov ( NCT05825937 ); first submitted 11 April 2023.

Design and validation of a method for evaluating medical device cleanliness by recovering and quantifying residual proteins on stainless plates

We recently reported a method for recovering and quantifying residual proteins bound to surfaces of various medical instruments via thermal coagulation under neutral pH and room temperature. The method effectively recovered and solubilised coagulated proteins at high temperatures in dry and humid conditions, with a protein recovery rate of > 90%. This study validated the previous method by comparing residual protein recovery from test samples using a conventional extraction solution (1% SDS, [pH 11.0]) and proposed solution (1% SDS, 10 mM TCEP, and 10 mM HEPES [pH 7.0]). To mimic soiled medical equipment, pseudo-blood-contaminated stainless steel plates were prepared. Residual protein was recovered using conventional and proposed solutions under varying temperature and humidity conditions. Quantitative protein recovery limits were determined at nine facilities. Compared with the conventional solution, the proposed solution recovered proteins more effectively from samples processed at temperatures > 60 °C. However, low recovery rates were observed for samples processed at 95 °C, possibly owing to differences in protein adhesion due to sample and plate-surface properties. Our findings present a method for quantifying residual proteins on medical instruments exposed to high temperatures during use or disinfection. Further studies should standardise test soiling conditions, materials, and solutions to evaluate cleaning methods.

A paralleled CNN and Transformer network for PPG-based cuff-less blood pressure estimation

Cuff-less blood pressure measurement plays a pivotal part in hypertension diagnosis and prevention. By employing deep learning algorithms, blood pressure estimation applying photoplethysmography (PPG) signals has achieved remarkable improvements and attracted growing attention. However, most existing methods utilize the PPG signal emphasized on localized feature learning, often neglecting the global features in the temporal data. To tackle the issue, we propose a novel architecture. It leverages a parallel processing approach by using Convolutional Neural Network for extracting local features and simultaneously employing Transformer to capture global features. The feature fusion block integrates the features using spatial and channel attention. The blood pressure values are regressed by two fully connected layers. To verify the performance of our method, we conduct evaluations on the Medical Information Mart for Intensive Care (MIMIC) database. On the MIMIC database, our algorithm demonstrates exceptional performance. For Diastolic Pressure, Mean Arterial Pressure, and Systolic Pressure, the mean absolute errors are 2.36 mmHg, 2.03 mmHg, and 4.44 mmHg, respectively. This performance aligns with the rigorous criteria required by an Association for the Advancement of Medical Instrumentation (AAMI) and receives a Grade A rating in accordance with the British Hypertension Society (BHS) standard.

Continuous blood pressure monitoring based on transformer encoders and stacked attention gated recurrent units

Continuous blood pressure monitoring (CBPM) is critical to support the accurate prevention and reliable treatment of cardiovascular diseases. To achieve efficient multi-information interaction and further improve the monitoring performance, this research proposes an intelligent model based on transformer encoders and stacked attention gated recurrent units (TE-SAGRU) for CBPM. Long-term multi-source feature sequences with rich information are initially extracted from photoplethysmography (PPG) and electrocardiography (ECG) signals. The paralleled transformer encoders are constructed for different source feature sequences to obtain high-level feature representations and preserve respective long-term independence. The multiple stacked attention gated recurrent units are cross-connected for multi-interactive feature fusion and promoting complementarity effects of multi-source features on CBPM. Comprehensive comparison experiments are carried out to validate the effectiveness of the TE-SAGRU model, using the dataset with 1000 subjects derived from the MIMIC-III database. The continuous monitoring errors of the TE-SAGRU model for systolic blood pressure (SBP) and diastolic blood pressure (DBP) are 3.91 ± 5.65 mmHg and 2.29 ± 3.01 mmHg. The monitored results pass the requirement of the Association for the Advancement of Medical Instrumentation (AAMI) standard and achieve Grade A of the British Hypertension Society (BHS) protocol.