Sphygmomanometer for Invasive Blood Pressure Monitoring in a Medical Mission

Tao, Kun‐Ming; Sokha, Sann; Yuan, Hongbin

doi:10.1097/aln.0000000000002469

Cited by 12 publications

(4 citation statements)

References 3 publications

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“…In the nursing process, catheter may be bent, resulting in thrombosis and, in severe cases, even extubation and reinsertion ( 16 – 18 ). In this study, the difference of nursing efficiency between the two groups was not significant ( P = 0.69).…”

Section: Discussionmentioning

confidence: 99%

Application Analysis of Positive-Pressure Connector in Invasive Blood Pressure Monitoring in Coronary Interventional Therapy

et al. 2021

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Background: In order to reduce the risk of invasive blood pressure monitoring and improve the safety and efficiency, this article mainly analyzes the effectiveness and safety of using positive-pressure connector for invasive blood pressure monitoring in patients with coronary artery interventional therapy, so as to improve the invasive blood pressure monitoring method.Aim: To study and analyze the application of positive-pressure connector in invasive blood pressure monitoring in coronary interventional therapy.Methods: From October 2017 to October 2019, a total of 120 patients admitted to Cangzhou Central Hospital, Cangzhou, Hebei, China, for coronary interventional therapy with invasive blood pressure monitoring were selected and divided into a control group and an experimental group by drawing lots with 60 patients in each group. Positive-pressure connector was used for invasive blood pressure detection in the experimental group, and heparin cap connector was used for invasive blood pressure detection in the control group. The effectiveness and safety of blood pressure monitoring in the two groups were compared, and the influence of different joints on invasive blood pressure monitoring was analyzed.Results: The influencing factors of puncture efficiency in the experimental group (6.67%) were significantly lower than those in the control group (30.00%) (P < 0.05). There was no significant difference in catheter bending between the experimental group and the control group (P > 0.05). The experimental group exhibited a remarkably higher puncture safety rate (93%) compared to the control group (67%) (P < 0.05). There was no significant difference in arterial blood pressure between the two groups with different indwelling time (P > 0.05). The frequency of extubation and reinsertion in the experimental group was significantly lower than that in the control group (P < 0.05). Factors influencing puncture safety in the experimental group were significantly lower than those in the control group (P < 0.05).Conclusion: The use of positive-pressure connector for invasive blood pressure monitoring in patients with coronary artery interventional therapy can greatly improve the safety of blood pressure monitoring and reduce the suffering of patients. Therefore, the application of positive-pressure connector in invasive blood pressure monitoring is worthy of promotion and application in clinical practice.

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Section: Discussionmentioning

confidence: 99%

Application Analysis of Positive-Pressure Connector in Invasive Blood Pressure Monitoring in Coronary Interventional Therapy

et al. 2021

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“…Continuous BP measurement and monitoring the variations in BP are essential for regulating high BP and early intervention in hypertension and other cardiovascular disorders [3]. Sphygmomanometery and oscillometry are frequently used for monitoring BP at domicile and mobile [4,5]. Inflatable cuffs are used to measure non-invasive BP, which can be uncomfortable, especially for hypertensive patients who need regular readings.…”

Section: Introductionmentioning

confidence: 99%

A Novel Technique for Continuous Blood Pressure Estimation from Optimal Feature Set of PPG Signal Using Deep Learning Approach

Raju

Dipto

Hossain

et al. 2023

Preprint

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Continuous Blood Pressure (BP) provides essential information for monitoring one's health condition. However, BP is currently monitoring using uncomfortable cuff-based devices, which does not support continuous BP monitoring. This paper aims to introduce a blood pressure monitoring algorithm based on only photoplethysmography (PPG) signals using the deep neural network (DNN). The PPG signals are obtained from 219 subjects with 657 records and filtered using signal processing algorithms to reduce the effects of noise, such as baseline wandering, and motion artifacts. The proposed algorithm is based on pulse wave analysis of PPG signals, extracted various domain features from PPG signals, and mapped them to BP values. Four feature selection methods are applied and yielded four feature subsets. Therefore, an ensemble feature selection technique is proposed to obtain the optimal feature set based on major voting scores from four feature subsets. DNN models, along with the ensemble feature selection technique, outperformed in estimating the systolic blood pressure (SBP) and diastolic blood pressure (DBP) compared to previously reported approaches that rely only on the PPG signal. The coefficient of determination (R2) and mean absolute error (MAE) of the proposed algorithm are 0.962 and 2.480 mmHg respectively for SBP, 0.955 and 1.499 mmHg respectively for DBP. The proposed approach meets the Advancement of Medical Instrumentation standard for SBP and DBP estimations. Additionally, according to the British Hypertension Society standard, the results attained Grade A for both SBP and DBP estimations. It concludes that BP can be estimated more accurately using the optimal feature set and DNN models. The proposed algorithm has the potential ability to facilitate mobile healthcare devices to monitor continuous BP.

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“…Both mercury and electronic sphygmomanometers are discontinuous, cuffbased methods for measuring BP. Electrocardiography requires a number of electrodes to be attached to the body, which is an inconvenience when it comes to measuring BP continuously [3][4][5]. Photoplethysmography (PPG), which absorbs light energy through a photodetector, can be used to monitor a patient's pulse rate.…”

Section: Introductionmentioning

confidence: 99%

Blood Pressure and Heart Rate Measurements Using Photoplethysmography with Modified LRCN

Mostafa¹,

Idris²,

Kaur³

2022

Computers, Materials &Amp; Continua

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In this study, single-channel photoplethysmography (PPG) signals were used to estimate the heart rate (HR), diastolic blood pressure (DBP), and systolic blood pressure (SBP). A deep learning model was proposed using a long-term recurrent convolutional network (LRCN) modified from a deep learning algorithm, the convolutional neural network model of the modified inception deep learning module, and a long short-term memory network (LSTM) to improve the model's accuracy of BP and HR measurements. The PPG data of 1,551 patients were obtained from the University of California Irvine Machine Learning Repository. How to design a filter of PPG signals and how to choose the loss functions for deep learning model were also discussed in the study. Finally, the stability of the proposed model was tested using a 10-fold cross-validation, with an MAE ± SD of 2.942 ± 5.076 mmHg for SBP, 1.747 ± 3.042 mmHg for DBP, and 1.137 ± 2.463 bpm for the HR. Compared with its existing counterparts, the model entailed less computational load and was more accurate in estimating SBP, DBP, and HR. These results established the validity of the model.

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Sphygmomanometer for Invasive Blood Pressure Monitoring in a Medical Mission

Cited by 12 publications

References 3 publications

Application Analysis of Positive-Pressure Connector in Invasive Blood Pressure Monitoring in Coronary Interventional Therapy

Application Analysis of Positive-Pressure Connector in Invasive Blood Pressure Monitoring in Coronary Interventional Therapy

A Novel Technique for Continuous Blood Pressure Estimation from Optimal Feature Set of PPG Signal Using Deep Learning Approach

Blood Pressure and Heart Rate Measurements Using Photoplethysmography with Modified LRCN

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