scholarly journals Non-Invasive PPG-Based System for Continuous Heart Rate Monitoring of Incubated Avian Embryo

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4560
Author(s):  
Ali Youssef ◽  
Daniel Berckmans ◽  
Tomas Norton
Keyword(s):  
Heart Rate ◽  
Real Time ◽  
Experimental Studies ◽  
Detection Algorithm ◽  
Embryonic Heart ◽  
Avian Embryo ◽  
Cardiovascular Research ◽  
Natural Activity ◽  
Non Invasive ◽  
Promising Solution

The chicken embryo is a widely used experimental animal model in many studies, including in the field of developmental biology, of the physiological responses and adaptation to altered environments, and for cancer and neurobiology research. The embryonic heart rate is an important physiological variable used as an index reflecting the embryo’s natural activity and is considered one of the most difficult parameters to measure. An acceptable measurement technique of embryonic heart rate should provide a reliable cardiac signal quality while maintaining adequate gas exchange through the eggshell during the incubation and embryonic developmental period. In this paper, we present a detailed design and methodology for a non-invasive photoplethysmography (PPG)-based prototype (Egg-PPG) for real-time and continuous monitoring of embryonic heart rate during incubation. An automatic embryonic cardiac wave detection algorithm, based on normalised spectral entropy, is described. The developed algorithm successfully estimated the embryonic heart rate with 98.7% accuracy. We believe that the system presented in this paper is a promising solution for non-invasive, real-time monitoring of the embryonic cardiac signal. The proposed system can be used in both experimental studies (e.g., developmental embryology and cardiovascular research) and in industrial incubation applications.

scholarly journals Non-Invasive PPG-Based System for Continuous Heart Rate Monitoring of Incubated Avian Embryo

2020 ◽  
Author(s):  
Ali Youssef ◽  
Daniel Berckmans ◽  
Tomas Norton
Keyword(s):  
Heart Rate ◽  
Real Time ◽  
Experimental Studies ◽  
Detection Algorithm ◽  
Embryonic Heart ◽  
Avian Embryo ◽  
Cardiovascular Research ◽  
Natural Activity ◽  
Non Invasive ◽  
Promising Solution

The chicken embryo is a widely used experimental animal-model in many studies such as developmental biology and to study the physiological responses and adaptation to altered environments as well as for cancer and neurobiology research. Embryonic heart rate is an important physiological variable useful as an index reflecting the embryo's natural activity and is considered one of the most difficult parameters to measure. An acceptable measurement technique of embryonic heart rate should provide a reliable cardiac signal quality while maintaining adequate gas exchange through the eggshell along the incubation and embryonic developmental period. In this paper, we presented a detailed design and methodology for a non-invasive PPG-based prototype (Egg-PPG) for real-time and continuous monitoring of embryonic heart rate during incubation. An automatic embryonic cardiac wave detection algorithm, based on normalised spectral entropy, is described. The developed algorithm successfully estimated the embryonic heart rate with 98.7% accuracy. We believe that the developed overall system presented in this paper is showing a promising solution for non-invasion, real-time monitoring of embryonic cardiac signal, which can be used in both experimental studies (e.g., developmental embryology and cardiovascular research) and in industrial incubation applications.

scholarly journals Identification of thresholds for accuracy comparisons of heart rate and respiratory rate in neonates

2021 ◽  
Vol 5 ◽  
pp. 93
Author(s):  
Jesse Coleman ◽  
Amy Sarah Ginsburg ◽  
William M. Macharia ◽  
Roseline Ochieng ◽  
Guohai Zhou ◽  
...  
Keyword(s):  
Heart Rate ◽  
Respiratory Rate ◽  
A Priori ◽  
Detection Algorithm ◽  
University Hospital ◽  
Non Invasive ◽  
Accuracy Comparison ◽  
Study Team ◽  
Neonatal Care Unit ◽  
Clinical Measurements

Background: Heart rate (HR) and respiratory rate (RR) can be challenging to measure accurately and reliably in neonates. The introduction of innovative, non-invasive measurement technologies suitable for resource-constrained settings is limited by the lack of appropriate clinical thresholds for accuracy comparison studies. Methods: We collected measurements of photoplethysmography-recorded HR and capnography-recorded exhaled carbon dioxide across multiple 60-second epochs (observations) in enrolled neonates admitted to the neonatal care unit at Aga Khan University Hospital in Nairobi, Kenya. Trained study nurses manually recorded HR, and the study team manually counted individual breaths from capnograms. For comparison, HR and RR also were measured using an automated signal detection algorithm. Clinical measurements were analyzed for repeatability. Results: A total of 297 epochs across 35 neonates were recorded. Manual HR showed a bias of -2.4 (-1.8%) and a spread between the 95% limits of agreement (LOA) of 40.3 (29.6%) compared to the algorithm-derived median HR. Manual RR showed a bias of -3.2 (-6.6%) and a spread between the 95% LOA of 17.9 (37.3%) compared to the algorithm-derived median RR, and a bias of -0.5 (1.1%) and a spread between the 95% LOA of 4.4 (9.1%) compared to the algorithm-derived RR count. Manual HR and RR showed repeatability of 0.6 (interquartile range (IQR) 0.5-0.7), and 0.7 (IQR 0.5-0.8), respectively. Conclusions: Appropriate clinical thresholds should be selected a priori when performing accuracy comparisons for HR and RR. Automated measurement technologies typically use median values rather than counts, which significantly impacts accuracy. A wider spread between the LOA, as much as 30%, should be considered to account for the observed physiological nuances and within- and between-neonate variability and different averaging methods. Wider adoption of thresholds by data standards organizations and technology developers and manufacturers will increase the robustness of clinical comparison studies.

scholarly journals Vital Block and Vital Sign Server for ECG and Vital Sign Monitoring in a Portable u-Vital System

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1089
Author(s):  
Tae Wuk Bae ◽  
Kee Koo Kwon ◽  
Kyu Hyung Kim
Keyword(s):  
Real Time ◽  
Vital Sign ◽  
Vital Signs ◽  
Detection Algorithm ◽  
Smart Device ◽  
Blood Oxygen Saturation ◽  
Real Time Processing ◽  
Non Invasive ◽  
Wireless Protocols ◽  
Point Detection

An important function in the future healthcare system involves measuring a patient’s vital signs, transmitting the measured vital signs to a smart device or a management server, analyzing it in real-time, and informing the patient or medical staff. Internet of Medical Things (IoMT) incorporates information technology (IT) into patient monitoring device (PMD) and is developing traditional measurement devices into healthcare information systems. In the study, a portable ubiquitous-Vital (u-Vital) system is developed and consists of a Vital Block (VB), a small PMD, and Vital Sign Server (VSS), which stores and manages measured vital signs. Specifically, VBs collect a patient’s electrocardiogram (ECG), blood oxygen saturation (SpO2), non-invasive blood pressure (NiBP), body temperature (BT) in real-time, and the collected vital signs are transmitted to a VSS via wireless protocols such as WiFi and Bluetooth. Additionally, an efficient R-point detection algorithm was also proposed for real-time processing and long-term ECG analysis. Experiments demonstrated the effectiveness of measurement, transmission, and analysis of vital signs in the proposed portable u-Vital system.

scholarly journals Acquisition and Analysis System of the Ballistocardiogram Signal Based on Virtual Instruments

2011 ◽  
Vol 2-3 ◽  
pp. 595-598
Author(s):  
Fang Fang Jiang ◽  
Xu Wang ◽  
Dan Yang ◽  
Yu Hao
Keyword(s):  
Heart Rate ◽  
Cardiac Function ◽  
Real Time ◽  
High Efficiency ◽  
Virtual Instruments ◽  
Invasive Technique ◽  
Operational Environment ◽  
Respiration Frequency ◽  
Non Invasive ◽  
Analysis System

Ballistocardiogram signal (BCG) is a non-invasive technique for the assessment of the cardiac function. It consists mainly of heart movement and the movement of blood in aorta, arteries, and periphery, which can be used to real-time monitor the heart rate and respiration frequency at home. In our laboratory, a sitting BCG detection chair has been designed successfully, and the acquisition and analysis system based on virtual instruments is proposed in this paper. MATLAB7.0 and LabVIEW8.5 were used to simulate the operational environment, and the results show high efficiency and accuracy in displaying waveform and spectrum, extracting main characteristics of heart rate and respiratory frequency, and alerting when abnormal heart-rate occurs.

scholarly journals Non-invasive monitoring of avian embryo heart rate

2019 ◽  
Vol 7 (3) ◽  
pp. 119-122 ◽  
Author(s):  
Andrianov Evgenii Aleksandrovich ◽  
◽  
Sudakov Alexander Nikolaevich ◽  
Andrianov Aleksei Aleksandrovich ◽  
Skolznev Nikolay Yakovlevich ◽  
...  
Keyword(s):  
Heart Rate ◽  
Avian Embryo ◽  
Invasive Monitoring ◽  
Non Invasive ◽  
Embryo Heart

scholarly journals Real-Time Cardiac Beat Detection and Heart Rate Monitoring from Combined Seismocardiography and Gyrocardiography

Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3472 ◽  
Author(s):  
D’Mello ◽  
Skoric ◽  
Xu ◽  
Roche ◽  
Lortie ◽  
...  
Keyword(s):  
Heart Rate ◽  
Real Time ◽  
Time Algorithm ◽  
Cardiac Monitoring ◽  
Computational Time ◽  
Heart Rate Monitoring ◽  
Heart Rates ◽  
Non Invasive ◽  
Beat Detection ◽  
Speed Accuracy

Cardiography is an indispensable element of health care. However, the accessibility of at-home cardiac monitoring is limited by device complexity, accuracy, and cost. We have developed a real-time algorithm for heart rate monitoring and beat detection implemented in a custom-built, affordable system. These measurements were processed from seismocardiography (SCG) and gyrocardiography (GCG) signals recorded at the sternum, with concurrent electrocardiography (ECG) used as a reference. Our system demonstrated the feasibility of non-invasive electro-mechanical cardiac monitoring on supine, stationary subjects at a cost of $100, and with the SCG–GCG and ECG algorithms decoupled as standalone measurements. Testing was performed on 25 subjects in the supine position when relaxed, and when recovering from physical exercise, to record 23,984 cardiac cycles at heart rates in the range of 36–140 bpm. The correlation between the two measurements had r2 coefficients of 0.9783 and 0.9982 for normal (averaged) and instantaneous (beat identification) heart rates, respectively. At a sampling frequency of 250 Hz, the average computational time required was 0.088 s per measurement cycle, indicating the maximum refresh rate. A combined SCG and GCG measurement was found to improve accuracy due to fundamentally different noise rejection criteria in the mutually orthogonal signals. The speed, accuracy, and simplicity of our system validated its potential as a real-time, non-invasive, and affordable solution for outpatient cardiac monitoring in situations with negligible motion artifact.

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