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Search Results (13)
  • Open Access

    ARTICLE

    Acute Effects of Virtual Reality Exercise on Young Adults’ Blood Pressure and Feelings

    Pablo Saiz-Gonzalez1,2, Daniel J. McDonough3, Wenxi Liu4, Zan Gao1,*

    International Journal of Mental Health Promotion, Vol.25, No.5, pp. 711-719, 2023, DOI:10.32604/ijmhp.2023.027530

    Abstract Virtual reality (VR) seems to have the potential to provide opportunities to promote physical activity (PA) in a fun way. This paper aimed to examine the acute effects of three different virtual reality-based exercise bikes on young adults’ blood pressure (BP) and feelings compared to a traditional exercise cycling session. Four exercise sessions (immersive VR cycling, two non-immersive VR cycling, and traditional cycling) were completed by 36 young adults (22 females; Mage = 23.6 years). BP was measured immediately before and after each session using a BP cuff and exercise-induced feelings were assessed via an established survey immediately after each… More >

  • Open Access

    ARTICLE

    Non-Contact Physiological Measurement System for Wearing Masks During the Epidemic

    Shu-Yin Chiang*, Dong-Ye Wu

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2509-2526, 2023, DOI:10.32604/cmc.2023.036466

    Abstract Physiological signals indicate a person’s physical and mental state at any given time. Accordingly, many studies extract physiological signals from the human body with non-contact methods, and most of them require facial feature points. However, under COVID-19, wearing a mask has become a must in many places, so how non-contact physiological information measurements can still be performed correctly even when a mask covers the facial information has become a focus of research. In this study, RGB and thermal infrared cameras were used to execute non-contact physiological information measurement systems for heart rate, blood pressure, respiratory rate, and forehead temperature for… More >

  • Open Access

    ARTICLE

    Machine Learning for Detecting Blood Transfusion Needs Using Biosignals

    Hoon Ko1, Chul Park2, Wu Seong Kang3, Yunyoung Nam4, Dukyong Yoon5, Jinseok Lee1,*

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 2369-2381, 2023, DOI:10.32604/csse.2023.035641

    Abstract Adequate oxygen in red blood cells carrying through the body to the heart and brain is important to maintain life. For those patients requiring blood, blood transfusion is a common procedure in which donated blood or blood components are given through an intravenous line. However, detecting the need for blood transfusion is time-consuming and sometimes not easily diagnosed, such as internal bleeding. This study considered physiological signals such as electrocardiogram (ECG), photoplethysmogram (PPG), blood pressure, oxygen saturation (SpO2), and respiration, and proposed the machine learning model to detect the need for blood transfusion accurately. For the model, this study extracted… More >

  • Open Access

    ARTICLE

    Design of Online Vitals Monitor by Integrating Big Data and IoT

    E. Afreen Banu1,*, V. Rajamani2

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2469-2487, 2023, DOI:10.32604/csse.2023.021332

    Abstract In this work, we design a multisensory IoT-based online vitals monitor (hereinafter referred to as the VITALS) to sense four bedside physiological parameters including pulse (heart) rate, body temperature, blood pressure, and peripheral oxygen saturation. Then, the proposed system constantly transfers these signals to the analytics system which aids in enhancing diagnostics at an earlier stage as well as monitoring after recovery. The core hardware of the VITALS includes commercial off-the-shelf sensing devices/medical equipment, a powerful microcontroller, a reliable wireless communication module, and a big data analytics system. It extracts human vital signs in a pre-programmed interval of 30 min… More >

  • Open Access

    ARTICLE

    False Alarm Reduction in ICU Using Ensemble Classifier Approach

    V. Ravindra Krishna Chandar1,*, M. Thangamani2

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 165-181, 2022, DOI:10.32604/iasc.2022.022339

    Abstract

    During patient monitoring, false alert in the Intensive Care Unit (ICU) becomes a major problem. In the category of alarms, pseudo alarms are regarded as having no clinical or therapeutic significance, and thus they result in fatigue alarms. Artifacts are misrepresentations of tissue structures produced by imaging techniques. These Artifacts can invalidate the Arterial Blood Pressure (ABP) signal. Therefore, it is very important to develop algorithms that can detect artifacts. However, ABP has algorithmic shortcomings and limitations of design. This study is aimed at developing a real-time enhancement of independent component analysis (EICA) and time-domain detection of QRS that can… More >

  • Open Access

    ARTICLE

    Blood Pressure and Heart Rate Measurements Using Photoplethysmography with Modified LRCN

    Chih-Ta Yen1,*, Cheng-Hong Liao2

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1973-1986, 2022, DOI:10.32604/cmc.2022.022679

    Abstract 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… More >

  • Open Access

    ARTICLE

    A Deep Learning-Based Continuous Blood Pressure Measurement by Dual Photoplethysmography Signals

    Chih-Ta Yen1,*, Sheng-Nan Chang2, Liao Jia-Xian3, Yi-Kai Huang3

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2937-2952, 2022, DOI:10.32604/cmc.2022.020493

    Abstract This study proposed a measurement platform for continuous blood pressure estimation based on dual photoplethysmography (PPG) sensors and a deep learning (DL) that can be used for continuous and rapid measurement of blood pressure and analysis of cardiovascular-related indicators. The proposed platform measured the signal changes in PPG and converted them into physiological indicators, such as pulse transit time (PTT), pulse wave velocity (PWV), perfusion index (PI) and heart rate (HR); these indicators were then fed into the DL to calculate blood pressure. The hardware of the experiment comprised 2 PPG components (i.e., Raspberry Pi 3 Model B and analog-to-digital… More >

  • Open Access

    CASE REPORT

    When the Blood Pressure Misleads You: A Diagnostic Conundrum in an Unusual Case of Coarctation

    Eva Kapravelou1, Hugo Issa2, Gordon Culham3, Martin Hosking1, Sanjiv K. Gandhi2, Shubhayan Sanatani1,*

    Congenital Heart Disease, Vol.16, No.6, pp. 675-680, 2021, DOI:10.32604/CHD.2021.016548

    Abstract A 4-month-old previously healthy baby was found to be in congestive heart failure with LV dysfunction and a right aortic arch with severe coarctation, undetectable by blood pressure measurements. A cardiac CT and central blood pressure led to the diagnosis of a unique anatomic variant of aortic coarctation. Once diagnosed the patient underwent surgery with an uncomplicated recovery. More >

  • Open Access

    ARTICLE

    Effect of Cluster Nursing Mode Combined with Blood Pressure Regulation on Surgical Tolerance of Patients with Esophageal Cancer and Hypertension

    Hongyan Ai1,*, Yan Wang2, Hongmei Gu2

    Oncologie, Vol.23, No.2, pp. 185-193, 2021, DOI:10.32604/Oncologie.2021.016420

    Abstract Objective: To explore the effect of the cluster nursing mode combined with blood pressure regulation on the surgical tolerance of patients with esophageal cancer and hypertension. Methods: The clinical data of 86 patients with esophageal cancer and hypertension treated in our hospital (February 2016–February 2017) were retrospectively analyzed. The patients were randomly split into research group and reference group, with 43 cases in each group. The reference group received routine nursing, while the research group received cluster nursing combined with blood pressure regulation. The SBP, DBP and heart rates at D1 (at admission), D2 (2 h before surgery) and D3… More >

  • Open Access

    ARTICLE

    Non-Contact Blood Pressure Measurement Based on IPPG

    Jiancheng Zou1, Shouyu Zhou1,*, Bailin Ge1, Xin Yang2

    Journal of New Media, Vol.3, No.2, pp. 41-51, 2021, DOI:10.32604/jnm.2021.017764

    Abstract Blood pressure is an important physiological parameter to reflect human vital signs. In order to achieve the non-contact dynamic blood pressure acquisition based on ordinary optical camera, a theoretical understanding of the functional relationship between blood pressure and pulse wave signal conduction time. And through imaging photoelectric plethysmography (IPPG), pulse wave signal conduction time of forehead and hand was obtained with ordinary optical camera. First, the pulse wave conduction time was obtained by recording the video with an ordinary optical camera. Second, real-time blood pressure values were collected. Finally, based on the relationship between blood pressure and pulse wave conduction… More >

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