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Zoo Biology Sep 2021Magnesium is involved in a variety of physiological processes in marine animals and is known to be deleterious in both excess and deficiency. The effects of magnesium...
Magnesium is involved in a variety of physiological processes in marine animals and is known to be deleterious in both excess and deficiency. The effects of magnesium concentration ranging from 700 mg/L (low), 1344 mg/L (control), and 2000 mg/L (high) on size and pulse rate in upside-down jellyfish (Cassiopea andromeda) medusae were examined in two separate 28-day trials. Exposure to low magnesium resulted in significantly (p < .05) higher pulse rates and decreased bell diameter and also produced oral arm degradation. Exposure to high magnesium resulted in significantly (p < .05) lower pulse rates and decreased bell diameter as well as oral arm cupping. In both low and high magnesium, almost all specimens changed color from pale blue on Day 1, to brown by Day 28, suggesting a loss of zooxanthellae. The decrease in bell diameter and color change was more pronounced and occurred more rapidly in low magnesium. The results of both trials demonstrate the deleterious effects of high and low magnesium on C. andromeda and emphasize the importance of monitoring magnesium concentration to maintain healthy display animals in public aquaria.
Topics: Animals; Animals, Zoo; Heart Rate; Magnesium; Scyphozoa
PubMed: 34124804
DOI: 10.1002/zoo.21631 -
ISA Transactions 1983Modern biomedical instrumentation uses the technology that resulted from advances in electronics. Integrated circuit (IC) chips have replaced large systems of hard-wired...
Modern biomedical instrumentation uses the technology that resulted from advances in electronics. Integrated circuit (IC) chips have replaced large systems of hard-wired electronic logic circuits and made them obsolete. Probably the most significant development in electronics is the IC chip called a microprocessor. Its capabilities make possible sophisticated instruments that can measure, compute, and display data for recurring physiological changes such as pulse rate. Because such instruments can function faster than the changes occur, information about the rate can be determined quickly, and remedial or corrective action can be implemented quickly in response to the data. This paper describes a pulse rate monitor that uses a microprocessor. It measures the occurrence rate of signals such as heart rate and respiration rate. It detects the signal rate, compares it with preset limits, and activates alarms as the limits are exceeded. The rate is measured and displayed at all times, until alarm conditions are detected. Then the display indicates the rate that caused the alarm condition. Upper and lower rate limits can be adjusted by the operator to suit the application.
Topics: Computers; Electrocardiography; Heart Rate; Humans; Microcomputers; Monitoring, Physiologic; Pulse; Software
PubMed: 6688244
DOI: No ID Found -
Medical Engineering & Physics Mar 2011We investigate whether pulse rate variability (PRV) extracted from finger photo-plethysmography (Pleth) waveforms can be the substitute of heart rate variability (HRV)... (Comparative Study)
Comparative Study
We investigate whether pulse rate variability (PRV) extracted from finger photo-plethysmography (Pleth) waveforms can be the substitute of heart rate variability (HRV) from RR intervals of ECG signals during obstructive sleep apnea (OSA). Simultaneous measurements (ECG and Pleth) were taken from 29 healthy subjects during normal (undisturbed sleep) breathing and 22 patients with OSA during OSA events. Highly significant (p<0.01) correlations (1.0>r>0.95) were found between heart rate (HR) and pulse rate (PR). Bland-Altman plot of HR and PR shows good agreement (<5% difference). Comparison of 2 min recording epochs demonstrated significant differences (p<0.01) in time, frequency domains and complexity analysis, between normal and OSA events using PRV as well as HRV measures. Results suggest that both HRV and PRV indices could be used to distinguish OSA events from normal breathing during sleep. However, several variability measures (SDNN, RMSSD, HF power, LF/HF and sample entropy) of PR and HR were found to be significantly (p<0.01) different during OSA events. Therefore, we conclude that PRV provides accurate inter-pulse variability to measure heart rate variability under normal breathing in sleep but does not precisely reflect HRV in sleep disordered breathing.
Topics: Adult; Aged; Algorithms; Cardiovascular Physiological Phenomena; Electrocardiography; Entropy; Heart Rate; Humans; Middle Aged; Photoplethysmography; Pulse; Respiration; Sleep; Sleep Apnea Syndromes; Sleep Apnea, Obstructive
PubMed: 20980188
DOI: 10.1016/j.medengphy.2010.09.020 -
Annual International Conference of the... 2012We propose in this paper an effective method to obtain the pulse rate from a hydraulic sensor that is placed under the mattress. The sensor captures the superposition of...
We propose in this paper an effective method to obtain the pulse rate from a hydraulic sensor that is placed under the mattress. The sensor captures the superposition of the ballistocardiogram (BCG) and the respiration signals. The BCG is modeled as the j-peak with a frequency modulation component. The proposed method utilizes the Hilbert transform to effectively capture the j-peak, which allows the pulse rate information to come out distinctively in the frequency domain. Among the five subjects tested, the error in pulse rate estimation is less than 1%.
Topics: Adult; Ballistocardiography; Biosensing Techniques; Female; Heart Rate; Humans; Male; Respiration
PubMed: 23366454
DOI: 10.1109/EMBC.2012.6346493 -
Biomedizinische Technik. Biomedical... Feb 2019In this paper, common time- and frequency-domain variability indexes obtained by pulse rate variability (PRV) series extracted from video-photoplethysmographic signal...
In this paper, common time- and frequency-domain variability indexes obtained by pulse rate variability (PRV) series extracted from video-photoplethysmographic signal (vPPG) were compared with heart rate variability (HRV) parameters calculated from synchronized ECG signals. The dual focus of this study was to analyze the effect of different video acquisition frame-rates starting from 60 frames-per-second (fps) down to 7.5 fps and different video compression techniques using both lossless and lossy codecs on PRV parameters estimation. Video recordings were acquired through an off-the-shelf GigE Sony XCG-C30C camera on 60 young, healthy subjects (age 23±4 years) in the supine position. A fully automated, signal extraction method based on the Kanade-Lucas-Tomasi (KLT) algorithm for regions of interest (ROI) detection and tracking, in combination with a zero-phase principal component analysis (ZCA) signal separation technique was employed to convert the video frames sequence to a pulsatile signal. The frame-rate degradation was simulated on video recordings by directly sub-sampling the ROI tracking and signal extraction modules, to correctly mimic videos recorded at a lower speed. The compression of the videos was configured to avoid any frame rejection caused by codec quality leveling, FFV1 codec was used for lossless compression and H.264 with variable quality parameter as lossy codec. The results showed that a reduced frame-rate leads to inaccurate tracking of ROIs, increased time-jitter in the signals dynamics and local peak displacements, which degrades the performances in all the PRV parameters. The root mean square of successive differences (RMSSD) and the proportion of successive differences greater than 50 ms (PNN50) indexes in time-domain and the low frequency (LF) and high frequency (HF) power in frequency domain were the parameters which highly degraded with frame-rate reduction. Such a degradation can be partially mitigated by up-sampling the measured signal at a higher frequency (namely 60 Hz). Concerning the video compression, the results showed that compression techniques are suitable for the storage of vPPG recordings, although lossless or intra-frame compression are to be preferred over inter-frame compression methods. FFV1 performances are very close to the uncompressed (UNC) version with less than 45% disk size. H.264 showed a degradation of the PRV estimation directly correlated with the increase of the compression ratio.
Topics: Algorithms; Heart Rate; Humans; Pressure; Signal Processing, Computer-Assisted; Video Recording
PubMed: 29135450
DOI: 10.1515/bmt-2016-0234 -
International Journal of... Sep 2013Heart rate variability (HRV) is widely used to assess autonomic nervous system (ANS) function. It is traditionally collected from a dedicated laboratory...
Heart rate variability (HRV) is widely used to assess autonomic nervous system (ANS) function. It is traditionally collected from a dedicated laboratory electrocardiograph (ECG). This presents a barrier to collecting the large samples necessary to maintain the statistical power of between-subject psychophysiological comparisons. An alternative to ECG involves an optical pulse sensor or photoplethysmograph run from a smartphone or similar portable device: smartphone pulse rate variability (SPRV). Experiment 1 determined the simultaneous accuracy between ECG and SPRV systems in n = 10 participants at rest. Raw SPRV values showed a consistent positive bias, which was successfully attenuated with correction. Experiment 2 tested an additional n = 10 participants at rest, during attentional load, and during mild stress (exercise). Accuracy was maintained, but slightly attenuated during exercise. The best correction method maintained an accuracy of +/-2% for low-frequency spectral power, and +/-5% for high-frequency spectral power over all points. Thus, the SPRV system records a pulse-to-pulse approximation of an ECG-derived heart rate series that is sufficiently accurate to perform time- and frequency-domain analysis of its variability, as well as accurately reflecting change in autonomic output provided by typical psychophysiological stimuli. This represents a novel method by which an accurate approximation of HRV may be collected for large-sample or naturalistic cardiac psychophysiological research.
Topics: Adolescent; Adult; Electrocardiography; Exercise; Female; Heart Rate; Humans; Inhibition, Psychological; Internet; Male; Neuropsychological Tests; Psychophysiology; Reaction Time; Rest; Spectrum Analysis; Young Adult
PubMed: 23751411
DOI: 10.1016/j.ijpsycho.2013.05.017 -
American Journal of Respiratory and... Jul 2021
Topics: Biomarkers; Cardiovascular Diseases; Heart Rate; Humans; Polysomnography; Sleep Apnea Syndromes
PubMed: 33915067
DOI: 10.1164/rccm.202102-0512LE -
Annual International Conference of the... Jul 2018Estimation of pulse rate from a wrist-type PPG during motion is a notoriously difficult problem because of the presence of motion artifact (MA) which corrupts the signal...
Estimation of pulse rate from a wrist-type PPG during motion is a notoriously difficult problem because of the presence of motion artifact (MA) which corrupts the signal in both the time and frequency domains. In this paper, we propose a new method for deriving pulse rate under intense exercise conditions which employs Ensemble Empirical Mode Decomposition and power spectral analysis to extract the pulsatile component of the signal. The method was validated on an openly available database containing PPG and ground-truth ECG-derived pulse rate measurements from 12 subjects during a running experiment. Our proposed technique showed a high estimation accuracy with a mean absolute error of 2.14 bpm over the entire database and a correlation coefficient between the estimates and the ground truth of 0.98. Our approach matched the performance of the state-of-the-art TROIKA framework without utilizing simultaneously recorded accelerometry data to remove the MA component. With over 97.5% of estimates within a 10% margin from the ground truth, our technique shows a lot of potential for inclusion in next generation wrist-worn wearable monitors in both sports and clinical settings.
Topics: Algorithms; Heart Rate; Humans; Photoplethysmography; Signal Processing, Computer-Assisted; Wrist
PubMed: 30441586
DOI: 10.1109/EMBC.2018.8513584 -
Annual International Conference of the... Nov 2021Photoplethysmography (PPG) is a completely noninvasive, optical method of assessing blood flow dynamics in peripheral vasculature. Wearable devices for PPG recording are...
Photoplethysmography (PPG) is a completely noninvasive, optical method of assessing blood flow dynamics in peripheral vasculature. Wearable devices for PPG recording are becoming increasingly popular, due to their cost-effectiveness and ease of use. For these reasons, many recent scientific studies have proposed the use of pulse rate variability (PRV) extracted from PPG as a surrogate for heart rate variability (HRV), in monitoring autonomic activity and cardiovascular health.In this work, we used a cross-mapping approach, a methodology based on chaos theory, to compare PRV and HRV dynamics, and investigate their agreement according to age and gender of healthy subjects. We used ECG and PPG data acquired from 57 subjects (41 young and 16 elderly) during resting state in the supine position. Signals were gathered from the publicly available VORTAL dataset. Our results showed a statistically significant decrease of PRV reliability as an HRV surrogate in old participants, which was confirmed as significant when only men subjects were analyzed (p-value<0.01).Our findings, although preliminary, suggest greater caution in the use of PPG devices for monitoring cardiovascular health, especially in elderly men.
Topics: Aged; Autonomic Nervous System; Electrocardiography; Female; Heart Rate; Humans; Male; Photoplethysmography; Reproducibility of Results
PubMed: 34891340
DOI: 10.1109/EMBC46164.2021.9630550 -
Physiological Measurement Feb 2021Precise beat-to-beat fiducial point detection in the photoplethysmogram signal is essential for reliable pulse rate variability (PRV) analysis, which is considered an...
Precise beat-to-beat fiducial point detection in the photoplethysmogram signal is essential for reliable pulse rate variability (PRV) analysis, which is considered an integral part of health monitoring devices in the evolving era of mobile health. Several studies have aimed to compare PRV to the well-investigated, gold standard heart rate variability (HRV) analysis, to see if they are interchangeable. The agreement between PRV and HRV is not unequivocal, as we learn from the commented metaanalysis. Technical factors like low sampling rate of photoplethysmography (PPG) or imprecise fiducial point detection are more important in this difference than physiological factors corresponding to pulse arrival time. Standardization of the PPG acquisition and reference point detection is necessary for comparable studies and correct measurement.
Topics: Electrocardiography; Heart Rate; Photoplethysmography; Reference Standards; Telemedicine
PubMed: 33554875
DOI: 10.1088/1361-6579/abd332