scholarly journals Assessment of Manual Blood Pressure and Heart Rate Measurement Skills of Pharmacy Students: A Follow-Up Investigation

2008 ◽  
Vol 72 (3) ◽  
pp. 60 ◽  
Author(s):  
Katherine E. Elliott ◽  
Kenneth L. McCall ◽  
David S. Fike ◽  
Jill Polk ◽  
Cynthia Raehl
Keyword(s):  
Blood Pressure ◽  
Heart Rate ◽  
Pharmacy Students ◽  
Rate Measurement ◽  
Heart Rate Measurement ◽  
Manual Blood Pressure

scholarly journals The usage of a hydraulic model of the vascular system in the development of verification units for blood pressure measuring devices

2012 ◽  
Vol 93 (2) ◽  
pp. 380-382
Author(s):  
A I Soyko ◽  
R N Karataev ◽  
I V Klyushkin ◽  
V A Gogin
Keyword(s):  
Blood Pressure ◽  
Heart Rate ◽  
Blood Vessels ◽  
Vascular System ◽  
Circulatory System ◽  
Hydraulic Model ◽  
Rate Measurement ◽  
Measuring Devices ◽  
Heart Rate Measurement ◽  
Human Circulatory System

The hydraulic model of the human circulatory system was discussed, presented from the position of classification and systematization of the major blood vessels, identified were the main consumers of the circulatory system, considered in detail was the area of regulation associated with the processes of blood pressure and heart rate measurement.

scholarly journals Changes in Blood Pressure and Heart Rate Measurement Undergraduate Students During Exam Period

2017 ◽  
Vol 08 (02) ◽  
Author(s):  
Senol Dogan ◽  
Nilay Nalcaci ◽  
Serkan Dogan ◽  
Almir Badnjevic ◽  
Amina Kurtovic ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Heart Rate ◽  
Undergraduate Students ◽  
Rate Measurement ◽  
Heart Rate Measurement

Feasibility of hybrid telerehabilitation as component of a novel comprehensive care program after acute myocardial infarction in a one-year follow-up preliminary experience of a single center

2021 ◽  
Vol 28 (Supplement_1) ◽  
Author(s):  
E Piotrowicz ◽  
P Orzechowski ◽  
I Kowalik ◽  
R Piotrowicz
Keyword(s):  
Myocardial Infarction ◽  
Blood Pressure ◽  
Acute Myocardial Infarction ◽  
Heart Rate ◽  
Functional Capacity ◽  
Care Program ◽  
Comprehensive Care ◽  
Monitoring Center ◽  
One Year

Abstract Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): National Health Fund Background. A novel comprehensive care program after acute myocardial infarction (AMI) „KOS-zawał" was implemented in Poland. It includes acute intervention, complex revascularization, implantation of cardiovascular electronic devices (in case of indications), rehabilitation or hybrid telerehabilitation (HTR) and scheduled outpatient follow-up. HTR is a unique component of this program. The purpose of the pilot study was to evaluate a feasibility, safety and patients’ acceptance of HTR as component of a novel care program after AMI and to assess mortality in a one-year follow-up. Methods The study included 55 patients (LVEF 55.6 ± 6.8%; aged 57.5 ± 10.5 years). Patients underwent a 5-week HTR based on Nordic walking, consisting of an initial stage (1 week) conducted within an outpatient center and a basic stage (4-week) home-based telerehabilitation five times weekly. HTR was telemonitored with a device adjusted to register electrocardiogram (ECG) recording and to transmit data via mobile phone network to the monitoring center. The moments of automatic ECG registration were pre-set and coordinated with exercise training. The influence on physical capacity was assessed by comparing changes in functional capacity (METs) from the beginning and the end of HTR. Patients filled in a questionnaire in order to assess their acceptance of HTR at the end of telerehabilitation. Results HTR resulted in a significant improvement in functional capacity and workload duration in exercise test (Table). Safety: there were neither deaths nor adverse events during HTR. Patients accepted HTR, including the need for interactive everyday collaboration with the monitoring center. Prognosis all patients survived in a one-year follow-up. Conclusions Hybrid telerehabilitation is a feasible, safe form of rehabilitation, well accepted by patients. There were no deaths in a one-year follow-up. Outcomes before and after HTR Before telerehabilitation After telerehabilitation P Exercise time [s] 381.5 ± 92.0 513.7 ± 120.2 <0.001 Maximal workload [MET] 7.9 ± 1.8 10.1 ± 2.3 <0.001 Heart rate rest [bpm] 68.6 ± 12.0 66.6 ± 10.9 0.123 Heart rate max effort [bpm] 119.7 ± 15.9 131.0 ± 20.1 <0.001 SBP rest [mmHg] 115.6 ± 14.8 117.7 ± 13.8 0.295 DBP rest [mmHg] 74.3 ± 9.2 76.2 ± 7.3 0.079 SBP max effort [mm Hg] 159.5 ± 25.7 170.7 ± 25.5 0.003 DBP max effort [mm Hg] 84.5 ± 9.2 87.2 ± 9.3 0.043 SBP systolic blood pressure, DBP diastolic blood pressure.

scholarly journals A Review of Deep Learning-Based Contactless Heart Rate Measurement Methods

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3719
Author(s):  
Aoxin Ni ◽  
Arian Azarang ◽  
Nasser Kehtarnavaz
Keyword(s):  
Heart Rate ◽  
Deep Learning ◽  
Mean Absolute Error ◽  
Absolute Error ◽  
Video Camera ◽  
Measurement Methods ◽  
Rate Measurement ◽  
Learning Methods ◽  
The Public ◽  
Heart Rate Measurement

The interest in contactless or remote heart rate measurement has been steadily growing in healthcare and sports applications. Contactless methods involve the utilization of a video camera and image processing algorithms. Recently, deep learning methods have been used to improve the performance of conventional contactless methods for heart rate measurement. After providing a review of the related literature, a comparison of the deep learning methods whose codes are publicly available is conducted in this paper. The public domain UBFC dataset is used to compare the performance of these deep learning methods for heart rate measurement. The results obtained show that the deep learning method PhysNet generates the best heart rate measurement outcome among these methods, with a mean absolute error value of 2.57 beats per minute and a mean square error value of 7.56 beats per minute.

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