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Biosensors Aug 2022Cardiovascular disease is one of the leading causes of death worldwide. Long-term and real-time monitoring of cardiovascular indicators is required to detect... (Review)
Review
Cardiovascular disease is one of the leading causes of death worldwide. Long-term and real-time monitoring of cardiovascular indicators is required to detect abnormalities and conduct early intervention in time. To this end, the development of flexible wearable/implantable sensors for real-time monitoring of various vital signs has aroused extensive interest among researchers. Among the different kinds of sensors, mechanical sensors can reflect the direct information of pressure fluctuations in the cardiovascular system with the advantages of high sensitivity and suitable flexibility. Herein, we first introduce the recent advances of four kinds of mechanical sensors for cardiovascular system monitoring, based on capacitive, piezoresistive, piezoelectric, and triboelectric principles. Then, the physio-mechanical mechanisms in the cardiovascular system and their monitoring are described, including pulse wave, blood pressure, heart rhythm, endocardial pressure, etc. Finally, we emphasize the importance of real-time physiological monitoring in the treatment of cardiovascular disease and discuss its challenges in clinical translation.
Topics: Cardiovascular Diseases; Electric Power Supplies; Heart Rate; Humans; Monitoring, Physiologic; Wearable Electronic Devices
PubMed: 36005046
DOI: 10.3390/bios12080651 -
Sensors (Basel, Switzerland) Sep 2022Heart rate (HR) and respiratory rate (RR) are two vital parameters of the body medically used for diagnosing short/long-term illness. Out-of-the-body, non-skin-contact...
Heart rate (HR) and respiratory rate (RR) are two vital parameters of the body medically used for diagnosing short/long-term illness. Out-of-the-body, non-skin-contact HR/RR measurement remains a challenge due to imprecise readings. "Invisible" wearables integrated into day-to-day garments have the potential to produce precise readings with a comfortable user experience. Sleep studies and patient monitoring benefit from "Invisibles" due to longer wearability without significant discomfort. This paper suggests a novel method to reduce the footprint of sleep monitoring devices. We use a single silver-coated nylon fabric band integrated into a substrate of a standard cotton/nylon garment as a resistive elastomer sensor to measure air and blood volume change across the chest. We introduce a novel event-based architecture to process data at the edge device and describe two algorithms to calculate real-time HR/RR on ARM Cortex-M3 and Cortex-M4F microcontrollers. RR estimations show a sensitivity of 99.03% and a precision of 99.03% for identifying individual respiratory peaks. The two algorithms used for HR calculation show a mean absolute error of 0.81 ± 0.97 and 0.86±0.61 beats/min compared with a gold standard ECG-based HR. The event-based algorithm converts the respiratory/pulse waveform into instantaneous events, therefore reducing the data size by 40-140 times and requiring 33% less power to process and transfer data. Furthermore, we show that events hold enough information to reconstruct the original waveform, retaining pulse and respiratory activity. We suggest fabric sensors and event-based algorithms would drastically reduce the device footprint and increase the performance for HR/RR estimations during sleep studies, providing a better user experience.
Topics: Heart Rate; Humans; Nylons; Polysomnography; Respiratory Rate; Sleep
PubMed: 36081149
DOI: 10.3390/s22176689 -
Scientific Reports Mar 2022Fetal behavioural states (fBS) describe periods of fetal wakefulness and sleep and are commonly defined by features such as body and eye movements and heart rate....
Fetal behavioural states (fBS) describe periods of fetal wakefulness and sleep and are commonly defined by features such as body and eye movements and heart rate. Automatic state detection through algorithms relies on different parameters and thresholds derived from both the heart rate variability (HRV) and the actogram, which are highly dependent on the specific datasets and are prone to artefacts. Furthermore, the development of the fetal states is dynamic over the gestational period and the evaluation usually only separated into early and late gestation (before and after 32 weeks). In the current work, fBS detection was consistent between the classification algorithm and visual inspection in 87 fetal magnetocardiographic data segments between 27 and 39 weeks of gestational age. To identify how automated fBS detection could be improved, we first identified commonly used parameters for fBS classification in both the HRV and the actogram, and investigated their distribution across the different fBS. Then, we calculated a receiver operating characteristics (ROC) curve to determine the performance of each parameter in the fBS classification. Finally, we investigated the development of parameters over gestation through linear regression. As a result, the parameters derived from the HRV have a higher classification accuracy compared to those derived from the body movement as defined by the actogram. However, the overlapping distributions of several parameters across states limit a clear separation of states based on these parameters. The changes over gestation of the HRV parameters reflect the maturation of the fetal autonomic nervous system. Given the higher classification accuracy of the HRV in comparison to the actogram, we suggest to focus further research on the HRV. Furthermore, we propose to develop probabilistic fBS classification approaches to improve classification in less prototypical datasets.
Topics: Autonomic Nervous System; Female; Fetus; Gestational Age; Heart Rate; Heart Rate, Fetal; Humans; Pregnancy; Wakefulness
PubMed: 35233073
DOI: 10.1038/s41598-022-07476-x -
Comparative Medicine Feb 2022Acute spinal cord injury (ASCI) is a devastating event that can have severe hemodynamic consequences, depending on location and severity of the lesion. Knowledge of...
Acute spinal cord injury (ASCI) is a devastating event that can have severe hemodynamic consequences, depending on location and severity of the lesion. Knowledge of hyperacute hemodynamic changes is important for researchers using porcine models of thoracic ASCI. The goal of this study was to determine the hyperacute hemodynamic changes observed after ASCI when using pigs as their own controls. Five Yucatan gilts were anesthetized, and a dorsal laminectomy performed at T10-T12. Standardized blunt trauma was applied for 5 consecutive min, and hemodynamic variables were collected 5 min before ASCI, and at 2, 4, 6, 8, 10, 20, 30, 60, 80 and 120 min after ASCI. Arterial blood gas samples were collected at 60 min and 10 min before, and at 30 min and between 120 and 240 min after ASCI. Parametric data were analyzed using a mixed effects model with time point as the fixed factor and subject as the random factor. We found no effect on heart rate, pulse pressure, SpO₂, EtCO₂, and respiratory rate between baseline and timepoints after ASCI. Diastolic arterial pressure, mean arterial pressure, and systolic arterial pressure fell significantly by 18%, 16%, and 15%, respectively, at 2 min after ASCI. However, none of the decrements in arterial pressures resulted in hypotension at any time point. Heart rate did not change significantly after ASCI. Blood glucose progressively increased to 50% above baseline between 120 and 240 minutes after ASCI. Low thoracic ASCI caused a consistent and statistically significant but clinically minor hyperacute decrease in arterial pressures (-15%) that did not produce hypotension or metabolic changes suggestive of tissue hypoperfusion. Our findings using this model suggest that mean arterial pressures should be maintained above 85 mm Hg prior to spinal trauma in order to avoid hypotensive states after ASCI.
Topics: Animals; Blood Pressure; Female; Heart Rate; Hemodynamics; Hypotension; Spinal Cord Injuries; Swine
PubMed: 34814974
DOI: 10.30802/AALAS-CM-21-000067 -
Sensors (Basel, Switzerland) Jul 2023Not long ago, hearables paved the way for biosensing, fitness, and healthcare monitoring. Smart earbuds today are not only producing sound but also monitoring vital... (Review)
Review
Not long ago, hearables paved the way for biosensing, fitness, and healthcare monitoring. Smart earbuds today are not only producing sound but also monitoring vital signs. Reliable determination of cardiovascular and pulmonary system information can explore the use of hearables for physiological monitoring. Recent research shows that photoplethysmography (PPG) signals not only contain details on oxygen saturation level (SPO2) but also carry more physiological information including pulse rate, respiration rate, blood pressure, and arterial-related information. The analysis of the PPG signal from the ear has proven to be reliable and accurate in the research setting. (1) Background: The present integrative review explores the existing literature on an in-ear PPG signal and its application. This review aims to identify the current technology and usage of in-ear PPG and existing evidence on in-ear PPG in physiological monitoring. This review also analyzes in-ear (PPG) measurement configuration and principle, waveform characteristics, processing technology, and feature extraction characteristics. (2) Methods: We performed a comprehensive search to discover relevant in-ear PPG articles published until December 2022. The following electronic databases: Institute of Electrical and Electronics Engineers (IEEE), ScienceDirect, Scopus, Web of Science, and PubMed were utilized to conduct the studies addressing the evidence of in-ear PPG in physiological monitoring. (3) Results: Fourteen studies were identified but nine studies were finalized. Eight studies were on different principles and configurations of hearable PPG, and eight studies were on processing technology and feature extraction and its evidence in in-ear physiological monitoring. We also highlighted the limitations and challenges of using in-ear PPG in physiological monitoring. (4) Conclusions: The available evidence has revealed the future of in-ear PPG in physiological monitoring. We have also analyzed the potential limitation and challenges that in-ear PPG will face in processing the signal.
Topics: Photoplethysmography; Monitoring, Physiologic; Blood Pressure; Arteries; Respiratory Rate; Heart Rate; Signal Processing, Computer-Assisted
PubMed: 37514778
DOI: 10.3390/s23146484 -
Epileptic Disorders : International... Oct 2022We explored changes in heart rate during the peri-ictal period in patients with focal epilepsy, and differences in heart rate changes according to epileptic site and...
OBJECTIVE
We explored changes in heart rate during the peri-ictal period in patients with focal epilepsy, and differences in heart rate changes according to epileptic site and side were assessed.
METHODS
A total of 198 epileptic seizures in 102 patients with focal epilepsy, who had a definite epileptogenic focus and had undergone surgical treatment, were assessed from 2014 to 2019. Heart rate was measured manually during the peri-ictal period. Change in heart rate and the time it occurred were assessed and compared between different epileptic sites and sides.
RESULTS
Heart rate increased in 177 (89.4%) of 198 seizures. In 82 (44.8%) of 183 seizures, the change in heart rate occurred before seizure onset. The median period of heart rate change was seven seconds (interquartile range: 3–11 seconds) in seizures with heart rate change before seizure onset. The number of seizures with heart rate increase before seizure onset was significantly greater for medial temporal lobe epilepsy compared to lateral temporal lobe epilepsy (p=0.019) and extratemporal lobe epilepsy (p=0.002).
SIGNIFICANCE
A change in heart rate prior to seizure onset is more likely to occur in patients with medial temporal lobe epilepsy, compared to those with lateral temporal lobe epilepsy and extratemporal lobe epilepsy. Patients with medial temporal lobe epilepsy may likely benefit from seizure warning and detection devices.
Topics: Electroencephalography; Epilepsies, Partial; Epilepsy; Epilepsy, Temporal Lobe; Heart Rate; Humans; Seizures
PubMed: 35904041
DOI: 10.1684/epd.2022.1473 -
Journal of Clinical Monitoring and... Oct 2021Feedback indicators can improve chest compression quality during cardiopulmonary resuscitation (CPR). However, the application of feedback indicators in the clinic...
Feedback indicators can improve chest compression quality during cardiopulmonary resuscitation (CPR). However, the application of feedback indicators in the clinic practice is rare. Pulse oximetry has been widely used and reported to correlate spontaneous circulation restoration during CPR. However, it is unclear if pulse oximetry can monitor the quality of chest compression. We hypothesized that pulse rate monitored by pulse oximetry can be used as a feedback indicator of the chest compression rate during CPR in a porcine model of cardiac arrest. Seven domestic male pigs (30-35 kg) were utilized in this study. Eighteen intermittent chest compression periods of 2 min were performed on each animal. Chest compression and pulse oximetry plethysmographic waveforms were recorded simultaneously. Chest compression and pulse rates were calculated based on both waveforms. Compression interruption and synchronous pulse interruption times were also measured. Agreement was analyzed between pulse rates and synchronous chest compression rates, as well as between compression interruption times and synchronous pulse interruption times. A total of 126 compression periods of 2 min were performed on seven animals. Interclass correlation coefficients and Bland-Altman analysis revealed reliable agreement between pulse rates and synchronous chest compression rates. Similarly, compression interruption and synchronous pulse interruption times obtained also showed high agreement. Pulse rate can be used as an alternative indicator of chest compression rate during CPR in a porcine model of cardiac arrest. Pulse interruption time also can be used to reflect compression interruption time precisely in this model.
Topics: Animals; Cardiopulmonary Resuscitation; Feedback; Heart Arrest; Heart Rate; Male; Oximetry; Swine
PubMed: 32780354
DOI: 10.1007/s10877-020-00576-x -
Scientific Reports Nov 2023Associations between cerebrovascular disease and impaired autonomic function and cerebrovascular reactivity have led to increased interest in variability of heart rate...
Associations between cerebrovascular disease and impaired autonomic function and cerebrovascular reactivity have led to increased interest in variability of heart rate (HRV) and blood pressure (BPV) following stroke. In this study, beat-to-beat pulse rate variability (PRV) and BPV were measured in clinically stable stroke patients (6 ischemic, 2 hemorrhagic) at least one year after their last cerebrovascular event. Beat-to-beat blood pressure (BP) measurements were collected from subjects while resting in the sitting position for one hour. Compared with healthy controls, stroke patients exhibited significantly greater time-domain (standard deviation, coefficient of variation, average real variability) and normalized high-frequency BPV (all p < 0.05). Stroke patients also exhibited lower LF:HF ratios than control subjects (p = 0.003). No significant differences were observed in PRV between the two groups, suggesting that BPV may be a more sensitive biomarker of cerebrovascular function in long-term post-stroke patients. Given a paucity of existing literature investigating beat-to-beat BPV in clinically stable post-stroke patients long (> 1 year) after their cerebrovascular events, this pilot study can help inform future studies investigating the mechanisms and effects of BPV in stroke. Elucidating this physiology may facilitate long-term patient monitoring and pharmacological management to mitigate the risk for recurrent stroke.
Topics: Humans; Blood Pressure; Heart Rate; Pilot Projects; Stroke; Monitoring, Physiologic
PubMed: 37935766
DOI: 10.1038/s41598-023-45479-4 -
Sensors (Basel, Switzerland) Nov 2022Heart rate at rest and exercise may predict cardiovascular risk. Heart rate variability is a measure of variation in time between each heartbeat, representing the... (Review)
Review
Heart rate at rest and exercise may predict cardiovascular risk. Heart rate variability is a measure of variation in time between each heartbeat, representing the balance between the parasympathetic and sympathetic nervous system and may predict adverse cardiovascular events. With advances in technology and increasing commercial interest, the scope of remote monitoring health systems has expanded. In this review, we discuss the concepts behind cardiac signal generation and recording, wearable devices, pros and cons focusing on accuracy, ease of application of commercial and medical grade diagnostic devices, which showed promising results in terms of reliability and value. Incorporation of artificial intelligence and cloud based remote monitoring have been evolving to facilitate timely data processing, improve patient convenience and ensure data security.
Topics: Humans; Heart Rate; Reproducibility of Results; Artificial Intelligence; Wearable Electronic Devices; Monitoring, Physiologic; Arrhythmias, Cardiac
PubMed: 36433498
DOI: 10.3390/s22228903 -
Journal of Physiological Anthropology Feb 2020Recently, attempts have been made to use the pulse rate variability (PRV) as a surrogate for heart rate variability (HRV). PRV, however, may be caused by the...
BACKGROUND
Recently, attempts have been made to use the pulse rate variability (PRV) as a surrogate for heart rate variability (HRV). PRV, however, may be caused by the fluctuations of left ventricular pre-ejection period and pulse transit time besides HRV. We examined whether PRV differs not only from HRV but also depending on the measurement site.
RESULTS
In five healthy subjects, pulse waves were measured simultaneously on both wrists and both forearms together with single-lead electrocardiogram (ECG) in the supine and sitting positions. Although average pulse interval showed no significant difference from average R-R interval in either positions, PRV showed greater power for the low-frequency (LF) and high-frequency (HF) components and lower LF/HF than HRV. The deviations of PRV from HRV in the supine and sitting positions were 13.2% and 7.9% for LF power, 24.5% and 18.3% for HF power, and - 15.0% and - 30.2% for LF/HF, respectively. While the average pulse interval showed 0.8% and 0.5% inter-site variations among the four sites in the supine and sitting positions, respectively, the inter-site variations in PRV were 4.0% and 3.6% for LF power, 3.8% and 4.7% for HF power, and 18.0% and 17.5% for LF/HF, respectively.
CONCLUSIONS
These suggest that PRV shows not only systemic differences from HRV but also considerable inter-site variations.
Topics: Adult; Electrocardiography; Female; Forearm; Heart Rate; Humans; Male; Posture; Pulse Wave Analysis; Signal Processing, Computer-Assisted; Wearable Electronic Devices; Wrist; Young Adult
PubMed: 32085811
DOI: 10.1186/s40101-020-0214-1