Wearable Ring-Shaped Biomedical Device for Physiological Monitoring through Finger-Based Acquisition of Electrocardiographic, Photoplethysmographic, and Galvanic Skin Response Signals: Design and Preliminary Measurements

Wearable health devices (WHDs) are rapidly gaining ground in the biomedical field due to their ability to monitor the individual physiological state in everyday life scenarios, while providing a comfortable wear experience. This study introduces a novel wearable biomedical device capable of synchronously acquiring electrocardiographic (ECG), photoplethysmographic (PPG), galvanic skin response (GSR) and motion signals. The device has been specifically designed to be worn on a finger, enabling the acquisition of all biosignals directly on the fingertips, offering the significant advantage of being very comfortable and easy to be employed by the users. The simultaneous acquisition of different biosignals allows the extraction of important physiological indices, such as heart rate (HR) and its variability (HRV), pulse arrival time (PAT), GSR level, blood oxygenation level (SpO2), and respiratory rate, as well as motion detection, enabling the assessment of physiological states, together with the detection of potential physical and mental stress conditions. Preliminary measurements have been conducted on healthy subjects using a measurement protocol consisting of resting states (i.e., SUPINE and SIT) alternated with physiological stress conditions (i.e., STAND and WALK). Statistical analyses have been carried out among the distributions of the physiological indices extracted in time, frequency, and information domains, evaluated under different physiological conditions. The results of our analyses demonstrate the capability of the device to detect changes between rest and stress conditions, thereby encouraging its use for assessing individuals' physiological state. Furthermore, the possibility of performing synchronous acquisitions of PPG and ECG signals has allowed us to compare HRV and pulse rate variability (PRV) indices, so as to corroborate the reliability of PRV analysis under stationary physical conditions. Finally, the study confirms the already known limitations of wearable devices during physical activities, suggesting the use of algorithms for motion artifact correction.

Cardiac Abnormalities in a Predictive Mouse Model of Chagas Disease

Chronic Chagas cardiomyopathy (CCC) results from infection with the protozoan parasite Trypanosoma cruzi and is a prevalent cause of heart disease in endemic countries. We previously found that cardiac fibrosis can vary widely in C3H/HeN mice chronically infected with T. cruzi JR strain, mirroring the spectrum of heart disease in humans. In this study, we examined functional cardiac abnormalities in this host:parasite combination to determine its potential as an experimental model for CCC. We utilised electrocardiography (ECG) to monitor T. cruzi-infected mice and determine whether ECG markers could be correlated with cardiac function abnormalities. We found that the C3H/HeN:JR combination frequently displayed early onset CCC indicators, such as sinus bradycardia and right bundle branch block, as well as prolonged PQ, PR, RR, ST, and QT intervals in the acute stage. Our model exhibited high levels of cardiac inflammation and enhanced iNOS expression in the acute stage, but denervation did not appear to have a role in pathology. These results demonstrate the potential of the C3H/HeN:JR host:parasite combination as a model for CCC that could be used for screening new compounds targeted at cardiac remodelling and for examining the potential of antiparasitic drugs to prevent or alleviate CCC development and progression.

Tablet-Based Wearable Patch Sensor Design for Continuous Cardiovascular System Monitoring in Postoperative Settings

Meticulous monitoring for cardiovascular systems is important for postoperative patients in postanesthesia or the intensive care unit. The continuous auscultation of heart and lung sounds can provide a valuable information for patient safety. Although numerous research projects have proposed the design of continuous cardiopulmonary monitoring devices, they primarily focused on the auscultation of heart and lung sounds and mostly served as screening tools. However, there is a lack of devices that could continuously display and monitor the derived cardiopulmonary parameters. This study presents a novel approach to address this need by proposing a bedside monitoring system that utilizes a lightweight and wearable patch sensor for continuous cardiovascular system monitoring. The heart and lung sounds were collected using a chest stethoscope and microphones, and a developed adaptive noise cancellation algorithm was implemented to remove the background noise corrupted with those sounds. Additionally, a short-distance ECG signal was acquired using electrodes and a high precision analog front end. A high-speed processing microcontroller was used to allow real-time data acquisition, processing, and display. A dedicated tablet-based software was developed to display the acquired signal waveforms and the processed cardiovascular parameters. A significant contribution of this work is the seamless integration of continuous auscultation and ECG signal acquisition, thereby enabling the real-time monitoring of cardiovascular parameters. The wearability and lightweight design of the system were achieved through the use of rigid-flex PCBs, which ensured patient comfort and ease of use. The system provides a high-quality signal acquisition and real-time monitoring of the cardiovascular parameters, thus proving its potential as a health monitoring tool.

Surgical placement of implantable cardiac loop recorders in great apes

Cardiovascular disease is the leading cause of morbidity and mortality in zoologically managed adult great apes, accounting for 29%-77% of adult deaths in the North American population depending on the species. In an effort to better understand the underlying causes of heart disease, implantable loop recorders (ILRs) have been used in some cases to monitor great apes with suspected or known cases of arrhythmia. This is a 10-year review of the Great Ape Heart Project's experience of implanting 21 ILRs in 7 gorillas (Gorilla gorilla gorilla; 9 total ILR devices), 5 chimpanzees (Pan troglodytes, 11 total ILR devices), and 1 orangutan (Pongo abelii, 1 ILR device) in an effort to develop effective methods for surgical implantation and remote collection of the data for analysis.

Cross-Domain Transfer of EEG to EEG or ECG Learning for CNN Classification Models

Electroencephalography (EEG) is often used to evaluate several types of neurological brain disorders because of its noninvasive and high temporal resolution. In contrast to electrocardiography (ECG), EEG can be uncomfortable and inconvenient for patients. Moreover, deep-learning techniques require a large dataset and a long time for training from scratch. Therefore, in this study, EEG-EEG or EEG-ECG transfer learning strategies were applied to explore their effectiveness for the training of simple cross-domain convolutional neural networks (CNNs) used in seizure prediction and sleep staging systems, respectively. The seizure model detected interictal and preictal periods, whereas the sleep staging model classified signals into five stages. The patient-specific seizure prediction model with six frozen layers achieved 100% accuracy for seven out of nine patients and required only 40 s of training time for personalization. Moreover, the cross-signal transfer learning EEG-ECG model for sleep staging achieved an accuracy approximately 2.5% higher than that of the ECG model; additionally, the training time was reduced by >50%. In summary, transfer learning from an EEG model to produce personalized models for a more convenient signal can both reduce the training time and increase the accuracy; moreover, challenges such as data insufficiency, variability, and inefficiency can be effectively overcome.

Clinical Implications of Cardiac Symptoms and Electrocardiographic Abnormalities for Advanced Liver Fibrosis in Patients with Nonalcoholic Fatty Liver Disease

Background and Objectives: Advanced liver fibrosis in patients with nonalcoholic fatty liver disease (NAFLD) can be a major predictor of cardiovascular disease (CVD) events and cardiac complications. However, the clinical significance of cardiac symptoms and abnormal electrocardiography (ECG) findings in patients with NAFLD associated with advanced liver fibrosis is unclear. Therefore, our study was aimed to evaluate the clinical implications based on the association between cardiac symptoms with ECG abnormalities for advanced liver fibrosis in patients with NAFLD. Materials and Methods: Of 31,795 participants who underwent health checkups, 6293 were diagnosed with NAFLD using ultrasound and inclusion criteria in a retrospective cross-sectional study. Advanced liver fibrosis was assessed based on a low NAFLD fibrosis score (NFS) and fibrosis-4 index (Fib-4) cut-off values (COVs). Cardiac data were assessed using a cardiac symptom questionnaire and 12-lead electrocardiography (ECG). Results: Among 6293 NAFLD patients with NAFLD, 304 (4.8%) experienced cardiac symptoms. NFS and Fib-4 indicated higher rates of advanced fibrosis in the cardiac-symptomatic group than in the non-symptomatic group (NFS: 7.3 vs. 4.1%; Fib-4: 7.8 vs. 3.7%; both p < 0.001). Cardiac symptoms were independently associated with advanced liver fibrosis using a step-wise-adjusted model and NFS and Fib-4 (final adjusted odds ratio (aOR), 1.40; 95% CI, 1.06-1.85; p = 0.018 for NFS; aOR, 1.67; 95%, 1.30-2.15; p < 0.001 for Fib-4). Cardiac symptoms with abnormal ECG findings independently predicted advanced liver fibrosis (aOR, 2.43; 95% CI, 1.72-3.39; p < 0.001 for NFS; aOR, 3.02; 95% CI, 2.19-4.15; p < 0.001 for Fib-4). Conclusions: Patients who have had cardiac symptoms and some ECG abnormalities may have a higher association with advanced liver fibrosis.

Electrocardiography Assessment of Sympatico-Vagal Balance during Resting and Pain Using the Texas Instruments ADS1299

Sympatico-vagal balance is essential for regulating cardiac electrophysiology and plays an important role in arrhythmogenic conditions. Various noninvasive methods, including electrocardiography (ECG), have been used for clinical assessment of the sympatico-vagal balance. This study aimed to use a custom-designed wearable device to record ECG and ECG-based cardiac function biomarkers to assess sympatico-vagal balance during tonic pain in healthy controls. Nineteen healthy volunteers were included for the ECG measurements using the custom-designed amplifier based on the Texas Instruments ADS1299. The ECG-based biomarkers of the sympatico-vagal balance, (including heart rate variability, deceleration capacity of the heart rate, and periodic repolarization dynamic), were calculated and compared between resting and pain conditions (tonic pain). The custom-designed device provided technically satisfactory ECG recordings. During exposure to tonic pain, the periodic repolarization dynamics increased significantly (p = 0.02), indicating enhancement of sympathetic nervous activity. This study showed that custom-designed wearable devices can potentially be useful in healthcare as a new telemetry technology. The ECG-based novel biomarkers, including periodic repolarization dynamic and deceleration capacity of heart rate, can be used to identify the cold pressor-induced activation of sympathetic and parasympathetic systems, making it useful for future studies on pain-evoked biomarkers.

Feasibility of Ultra-Short-Term Analysis of Heart Rate and Systolic Arterial Pressure Variability at Rest and during Stress via Time-Domain and Entropy-Based Measures

Heart Rate Variability (HRV) and Blood Pressure Variability (BPV) are widely employed tools for characterizing the complex behavior of cardiovascular dynamics. Usually, HRV and BPV analyses are carried out through short-term (ST) measurements, which exploit ~five-minute-long recordings. Recent research efforts are focused on reducing the time series length, assessing whether and to what extent Ultra-Short-Term (UST) analysis is capable of extracting information about cardiovascular variability from very short recordings. In this work, we compare ST and UST measures computed on electrocardiographic R-R intervals and systolic arterial pressure time series obtained at rest and during both postural and mental stress. Standard time-domain indices are computed, together with entropy-based measures able to assess the regularity and complexity of cardiovascular dynamics, on time series lasting down to 60 samples, employing either a faster linear parametric estimator or a more reliable but time-consuming model-free method based on nearest neighbor estimates. Our results are evidence that shorter time series down to 120 samples still exhibit an acceptable agreement with the ST reference and can also be exploited to discriminate between stress and rest. Moreover, despite neglecting nonlinearities inherent to short-term cardiovascular dynamics, the faster linear estimator is still capable of detecting differences among the conditions, thus resulting in its suitability to be implemented on wearable devices.

Electrocardiographic Features of Left Ventricular Diastolic Dysfunction and Heart Failure With Preserved Ejection Fraction: A Systematic Review

Background: Electrocardiographic features are well-known for heart failure with reduced ejection fraction (HFrEF), but not for left ventricular diastolic dysfunction (LVDD) and heart failure with preserved ejection fraction (HFpEF). As ECG features could help to identify high-risk individuals in primary care, we systematically reviewed the literature for ECG features diagnosing women and men suspected of LVDD and HFpEF. Methods and Results: Among the 7,127 records identified, only 10 studies reported diagnostic measures, of which 9 studied LVDD. For LVDD, the most promising features were T-end-P/(PQ*age), which is the electrocardiographic equivalent of the passive-to-active filling (AUC: 0.91-0.96), and repolarization times (QTc interval ≥ 350 ms, AUC: 0.85). For HFpEF, the Cornell product ≥ 1,800 mm*ms showed poor sensitivity of 40% (AUC: 0.62). No studies presented results stratified by sex. Conclusion: Electrocardiographic features are not widely evaluated in diagnostic studies for LVDD and HFpEF. Only for LVDD, two ECG features related to the diastolic interval, and repolarization measures showed diagnostic potential. To improve diagnosis and care for women and men suspected of heart failure, reporting of sex-specific data on ECG features is encouraged.

Automated Detection and Removal of Cardiac and Pulse Interferences from Neonatal EEG Signals

Electrical cardiac and pulsatile interference is very difficult to remove from electroencephalographic (EEG) signals, especially if recorded in neonates, for which a small number of EEG channels is used. Several methods were proposed, including Blind Source Separation (BSS) methods that required the use of artificial cardiac-related signals to improve the separation of artefactual components. To optimize the separation of cardiac-related artefactual components, we propose a method based on Independent Component Analysis (ICA) that exploits specific features of the real electrocardiographic (ECG) signals that were simultaneously recorded with the neonatal EEG. A total of forty EEG segments from 19-channel neonatal EEG recordings with and without seizures were used to test and validate the performance of our method. We observed a significant reduction in the number of independent components (ICs) containing cardiac-related interferences, with a consequent improvement in the automated classification of the separated ICs. The comparison with the expert labeling of the ICs separately containing electrical cardiac and pulsatile interference led to an accuracy = 0.99, a false omission rate = 0.01 and a sensitivity = 0.93, outperforming existing methods. Furthermore, we verified that true brain activity was preserved in neonatal EEG signals reconstructed after the removal of artefactual ICs, demonstrating the effectiveness of our method and its safe applicability in a clinical context.

The Association of Early Electrocardiographic Abnormalities With Brain Injury Severity and Outcome in Severe Traumatic Brain Injury

The aim of this study was to evaluate the frequency of electrocardiographic (ECG) abnormalities in the acute phase of severe traumatic brain injury (TBI) and the association with brain injury severity and outcome. In contrast to neurovascular diseases, sparse information is available on this issue. Data of adult patients with severe TBI admitted to the Intensive Care Unit (ICU) for intracranial pressure monitoring of a level-1 trauma center from 2002 till 2018 were analyzed. Patients with a cardiac history were excluded. An ECG recording was obtained within 24 h after ICU admission. Admission brain computerized tomography (CT)-scans were categorized by Marshall-criteria (diffuse vs. mass lesions) and for location of traumatic lesions. CT-characteristics and maximum Therapy Intensity Level (TILmax) were used as indicators for brain injury severity. We analyzed data of 198 patients, mean (SD) age of 40 ± 19 years, median GCS score 3 [interquartile range (IQR) 3–6], and 105 patients (53%) had thoracic injury. In-hospital mortality was 30%, with sudden death by cardiac arrest in four patients. The incidence of ECG abnormalities was 88% comprising ventricular repolarization disorders (57%) mostly with ST-segment abnormalities, conduction disorders (45%) mostly with QTc-prolongation, and arrhythmias (38%) mostly of supraventricular origin. More cardiac arrhythmias were observed with increased grading of diffuse brain injury (p = 0.042) or in patients treated with hyperosmolar therapy (TILmax) (65%, p = 0.022). No association was found between ECG abnormalities and location of brain lesions nor with thoracic injury. Multivariate analysis with baseline outcome predictors showed that cardiac arrhythmias were not independently associated with in-hospital mortality (p = 0.097). Only hypotension (p = 0.029) and diffuse brain injury (p = 0.017) were associated with in-hospital mortality. In conclusion, a high incidence of ECG abnormalities was observed in patients with severe TBI in the acute phase after injury. No association between ECG abnormalities and location of brain lesions or presence of thoracic injury was present. Cardiac arrhythmias were indicative for brain injury severity but not independently associated with in-hospital mortality. Therefore, our findings likely suggest that ECG abnormalities should be considered as cardiac mimicry representing the secondary effect of traumatic brain injury allowing for a more rationale use of neuroprotective measures.

Self-Adherent Biodegradable Gelatin-Based Hydrogel Electrodes for Electrocardiography Monitoring

Patch-type hydrogel electrodes have received increasing attention in biomedical applications due to their high biocompatibility and conformal adherence. However, their poor mechanical properties and non-uniform electrical performance in a large area of the hydrogel electrode should be improved for use in wearable devices for biosignal monitoring. Here, we developed self-adherent, biocompatible hydrogel electrodes composed of biodegradable gelatin and conductive polymers for electrocardiography (ECG) measurement. After incorporating conductive poly(3,4-ethylenedioxythiophene):poly(4-styrenesulfonate) (PEDOT:PSS) into gelatin hydrogels crosslinked by natural crosslinkers (genipin), the mechanical properties and electrical conductivity of the hydrogel electrodes were improved and additionally optimized by adjusting the amounts of crosslinker and PEDOT:PSS, respectively. Furthermore, the effect of dimethyl sulfoxide, as a dopant, on the conductivity of hydrogels was investigated. The gelatin-based, conductive hydrogel patch displayed self-adherence to human skin with an adhesive strength of 0.85 N and achieved conformal contact with less skin irritation compared to conventional electrodes with a chemical adhesive layer. Eyelet-type hydrogel electrodes, which were compatible with conventional ECG measurement instruments, exhibited a comparable performance in 12-lead human ECG measurement with commercial ECG clinical electrodes (3M Red Dot). These self-adherent, biocompatible, gelatin-based hydrogel electrodes could be used for monitoring various biosignals, such as in electromyography and electroencephalography.

Dynamics of the use of magnetocardiography in the study of the cardiac conduction system of the chick embryo

INTRODUCTION

Human fetal magnetocardiography (fMCG) has been done for several decades to evaluate fetal arrhythmias using a superconducting quantum interference device (SQUID) magnetometer, but there is little work in embryonic/fetal animal models. This study uses an optically-pumped magnetometer (OPM) to obtain an fMCG in the chick embryo.

METHODS

White Leghorn chick embryos were examined from incubation Day #10-19. Different examination chambers were tested to optimize embryonic thermal stability and magnetic signal acquisition. All examinations were done with magnetic shielding. The OPM sensors were placed next to the egg shell. The embryo's position was localized by transilluminating the intact egg or ultrasound imaging the egg with an open air cell to optimize sensor placement. The raw data for each embryo was postprocessed to obtain a fMCG composite waveform.

RESULTS

fMCG's were obtained in embryos from Day #12 to 19. The best success with intact eggs was obtained using five sensors; one at the bottom and four around the lower perimeter of the egg at 90° intervals with the egg oriented vertically and the air cell up. Using ultrasound imaging with the air cell open only two sensors were necessary, one at the bottom and one laterally next to the embryo. fMCGs were analyzed for heart rate and rhythm, each portion of the PQRST waveform, and the PR interval, QRS complex, RR interval, and QT interval.

CONCLUSIONS

This study validates the chick embryo as an animal model to study in a longitudinal and noninvasive fashion the fetal cardiac conduction system by using OPM magnetocardiography.

ECG-Quality Assessment of Dry-Electrode Cooperative Sensors

Classical approaches for measuring high-quality ECG require the use of gel electrodes and individually shielded cables, which limit patient comfort, especially in long-term use. We recently introduced a novel sensing architecture-so-called cooperative sensors-that allow the use of active dry electrodes connected by two unshielded wires. The aim of this work is to qualitatively evaluate an ECG recorded with a dry-electrode cooperative-sensor system. To that end, preliminary observations were made on three healthy subjects. The ECGs were concurrently recorded with cooperative sensors and a gold-standard 12-lead ECG device during a stress test on a stationary bicycle. First experimental measurements demonstrated the reliability of the approach for a wearable 12-lead ECG monitoring system tested in real settings.

Is Continuous Heart Rate Monitoring of Livestock a Dream or Is It Realistic? A Review

For all homoeothermic living organisms, heart rate (HR) is a core variable to control the metabolic energy production in the body, which is crucial to realize essential bodily functions. Consequently, HR monitoring is becoming increasingly important in research of farm animals, not only for production efficiency, but also for animal welfare. Real-time HR monitoring for humans has become feasible though there are still shortcomings for continuously accurate measuring. This paper is an effort to estimate whether it is realistic to get a continuous HR sensor for livestock that can be used for long term monitoring. The review provides the reported techniques to monitor HR of living organisms by emphasizing their principles, advantages, and drawbacks. Various properties and capabilities of these techniques are compared to check the potential to transfer the mostly adequate sensor technology of humans to livestock in term of application. Based upon this review, we conclude that the photoplethysmographic (PPG) technique seems feasible for implementation in livestock. Therefore, we present the contributions to overcome challenges to evolve to better solutions. Our study indicates that it is realistic today to develop a PPG sensor able to be integrated into an ear tag for mid-sized and larger farm animals for continuously and accurately monitoring their HRs.

Limitations of Electrocardiography for Detecting Left Ventricular Hypertrophy or Concentric Remodeling in Athletes

BACKGROUND

Electrocardiography (ECG) is used to screen for left ventricular hypertrophy (LVH), but common ECG-LVH criteria have been found less effective in athletes. The purpose of this study was to comprehensively evaluate the value of ECG for identifying athletes with LVH or a concentric cardiac phenotype.

METHODS

A retrospective analysis of 196 male Division I college athletes routinely screened with ECG and echocardiography within the Stanford Athletic Cardiovascular Screening Program was performed. Left-ventricular mass and volume were determined using echocardiography. LVH was defined as left ventricular mass (LVM) >102 g/m²; a concentric cardiac phenotype as LVM-to-volume (M/V) ≥1.05 g/mL. Twelve-lead electrocardiograms including high-resolution time intervals and QRS voltages were obtained. Thirty-seven previously published ECG-LVH criteria were applied, of which the majority have never been evaluated in athletes. C-statistics, including area under the receiver operating curve (AUC) and likelihood ratios were calculated.

RESULTS

ECG lead voltages were poorly associated with LVM (r = 0.18-0.30) and M/V (r = 0.15-0.25). The proportion of athletes with ECG-LVH was 0%-74% across criteria, with sensitivity and specificity ranging between 0% and 91% and 27% and 99.5%, respectively. The average AUC of the criteria in identifying the 11 athletes with LVH was 0.57 (95% confidence interval [CI] 0.56-0.59), and the average AUC for identifying the 8 athletes with a concentric phenotype was 0.59 (95% CI 0.56-0.62).

CONCLUSION

The diagnostic capacity of all ECG-LVH criteria were inadequate and, therefore, not clinically useful in screening for LVH or a concentric phenotype in athletes. This is probably due to the weak association between LVM and ECG voltage.

Subarachnoid Hemorrhage Presenting with Second-Degree Type I Sinoatrial Exit Block: A Case Report

The understanding of neural regulation of the cardiovascular function and the implications of a "Heart-Brain Axis "has been a topic of interest for clinicians for many years. Electrocardiographic (ECG) and structural cardiac changes, ranging from mild, asymptomatic, transient alteration in cardiovascular function to severe, irreversible, and potentially life-threatening injury, can actually be a manifestation of several neurological disorders. When managing cardiac disorders, a high index of clinical suspicion, detailed history-taking and physical examination skills, and an extensive workup that covers both cardiac and non-cardiac causes should be utilized. It is important to consider that cardiovascular dysfunction of an underlying neurological etiology may lead to difficulty in diagnosing and optimizing treatment of the latter. We report the case of a middle-aged female with the chief complaint of syncope preceded by a headache with no focal neurological deficits, originally diagnosed with- and whose syncope was attributed to sinus bradycardia and type I sinoatrial (SA) exit block on ECG. Subsequently, when the patient became altered, however, computer tomography (CT) angiography revealed subarachnoid hemorrhage (SAH) with middle cerebral artery aneurysm. This presentation emphasizes the importance of tabulating neurological injury as one of the differential diagnoses while managing ECG changes in cardiovascular disease (CVD), as missing and delaying the former can result in disastrous consequences.

Multi-Site Photoplethysmographic and Electrocardiographic System for Arterial Stiffness and Cardiovascular Status Assessment

The development and validation of a system for multi-site photoplethysmography (PPG) and electrocardiography (ECG) is presented. The system could acquire signals from 8 PPG probes and 10 ECG leads. Each PPG probe was constituted of a light-emitting diode (LED) source at a wavelength of 940 nm and a silicon photomultiplier (SiPM) detector, located in a back-reflection recording configuration. In order to ensure proper optode-to-skin coupling, the probe was equipped with insufflating cuffs. The high number of PPG probes allowed us to simultaneously acquire signals from multiple body locations. The ECG provided a reference for single-pulse PPG evaluation and averaging, allowing the extraction of indices of cardiovascular status with a high signal-to-noise ratio. Firstly, the system was characterized on optical phantoms. Furthermore, in vivo validation was performed by estimating the brachial-ankle pulse wave velocity (baPWV), a metric associated with cardiovascular status. The validation was performed on healthy volunteers to assess the baPWV intra- and extra-operator repeatability and its association with age. Finally, the baPWV, evaluated via the developed instrumentation, was compared to that estimated with a commercial system used in clinical practice (Enverdis Vascular Explorer). The validation demonstrated the system's reliability and its effectiveness in assessing the cardiovascular status in arterial ageing.

Magnetic Resonance Imaging Compatible Non-Invasive Fibre-Optic Sensors Based on the Bragg Gratings and Interferometers in the Application of Monitoring Heart and Respiration Rate of the Human Body: A Comparative Study

The publication presents a comparative study of two fibre-optic sensors in the application of heart rate (HR) and respiratory rate (RR) monitoring of the human body. After consultation with clinical practitioners, two types of non-invasive measuring and analysis systems based on fibre Bragg grating (FBG) and fibre-optic interferometer (FOI) have been designed and assembled. These systems use probes (both patent pending) that have been encapsulated in the bio-compatible polydimethylsiloxane (PMDS). The main advantage of PDMS is that it is electrically non-conductive and, as well as optical fibres, has low permeability. The initial verification measurement of the system designed was performed on four subjects in a harsh magnetic resonance (MR) environment under the supervision of a senior radiology assistant. A follow-up comparative study was conducted, upon a consent of twenty volunteers, in a laboratory environment with a minimum motion load and discussed with a head doctor of the Radiodiagnostic Institute. The goal of the laboratory study was to perform measurements that would simulate as closely as possible the environment of harsh MR or the environment of long-term health care facilities, hospitals and clinics. Conventional HR and RR measurement systems based on ECG measurements and changes in the thoracic circumference were used as references. The data acquired was compared by the objective Bland⁻Altman (B⁻A) method and discussed with practitioners. The results obtained confirmed the functionality of the designed probes, both in the case of RR and HR measurements (for both types of B⁻A, more than 95% of the values lie within the ±1.96 SD range), while demonstrating higher accuracy of the interferometric probe (in case of the RR determination, 95.66% for the FOI probe and 95.53% for the FBG probe, in case of the HR determination, 96.22% for the FOI probe and 95.23% for the FBG probe).

Portable out-of-hospital electrocardiography: A review of current technologies

Background

Availability of portable and home‐based electrocardiography (ECG) is an important medical innovation, which has a potential to transform medical care. We performed this review to understand the current state of out‐of‐hospital portable ECG technologies with respect to their scope, ease of use, data transmission capabilities, and diagnostic accuracy.

Methods

We conducted PubMed and Internet searches for “handheld” or “wearable” or “patch” electrocardiography devices to enlist available technologies. We also searched PubMed with names of individual devices to obtain additional citations. We classified available devices as a “single limb lead ECG recording devices” and chest‐lead “ECG recording devices.” If a device used more than three electrodes, it was defined as a conventional electrocardiography or Holter machine and was excluded from this review.

Results

We identified a total of 15 devices. Overall, only six of these devices (five single lead and one chest lead) featured in published medical literature as identified from PubMed search. A total of 13 citations were available for the single limb lead ECG recording devices and 6 citations for the chest‐lead ECG recording devices.

Conclusions

Despite the increase in number of such devices, published biomedical literature regarding their diagnostic accuracy, reproducibility, or utility is scant.

Electrocardiographic unrecognized myocardial infarction does not improve prediction of cardiovascular events beyond traditional risk factors. The Tromsø Study

Background Unrecognized myocardial infarction (MI) is a frequent and intriguing entity associated with a similar risk of death as recognized MI. Previous studies have not fully addressed whether the poor prognosis is explained by traditional cardiovascular risk factors. We investigated whether electrocardiographically detected unrecognized MI was independently associated with cardiovascular events and death and whether it improved prediction for future MI in a general population. Design Prospective cohort study. Methods We studied 5686 women and men without clinically recognized MI at baseline in 2007-2008. We assessed the risk of future MI, stroke and all-cause mortality in persons with unrecognized MI compared with persons with no MI during 31,051 person-years of follow-up. Results In the unadjusted analyses, unrecognized MI was associated with increased risk of future recognized MI (hazard ratio 1.84, 95% confidence interval (CI) 1.15-2.96) and all-cause mortality (hazard ratio 1.78, 95% CI 1.21-2.61), but not stroke (hazard ratio 1.09, 95% CI 0.56-2.17). The associations did not remain significant after adjustment for traditional risk factors (hazard ratio 1.25, 95% CI 0.76-2.06 and hazard ratio 1.38, 95% CI 0.93-2.05) for MI and all-cause mortality respectively. Unrecognized MI did not improve risk prediction for future recognized MI using the Framingham Risk Score ( p = 0.96) or the European Systematic COronary Risk Evaluation ( p = 0.65). There was no significant sex interaction regarding any of the endpoints. Conclusion Electrocardiographic unrecognized MI was not significantly associated with future risk of MI, stroke or all-cause mortality in the general population after adjustment for the traditional cardiovascular risk factors, and it did not improve prediction of future MI.

Seismocardiography-Based Cardiac Computed Tomography Gating Using Patient-Specific Template Identification and Detection

To more accurately trigger cardiac computed tomography angiography (CTA) than electrocardiography (ECG) alone, a sub-system is proposed as an intermediate step toward fusing ECG with seismocardiography (SCG). Accurate prediction of quiescent phases is crucial to prospectively gating CTA, which is susceptible to cardiac motion and, thus, can affect the diagnostic quality of images. The key innovation of this sub-system is that it identifies the SCG waveform corresponding to heart sounds and determines their phases within the cardiac cycles. Furthermore, this relationship is modeled as a linear function with respect to heart rate. For this paper, B-mode echocardiography is used as the gold standard for identifying the quiescent phases. We analyzed synchronous ECG, SCG, and echocardiography data acquired from seven healthy subjects (mean age: 31; age range: 22–48; males: 4) and 11 cardiac patients (mean age: 56; age range: 31–78; males: 6). On average, the proposed algorithm was able to successfully identify 79% of the SCG waveforms in systole and 68% in diastole. The simulated results show that SCG-based prediction produced less average phase error than that of ECG. It was found that the accuracy of ECG-based gating is more susceptible to increases in heart rate variability, while SCG-based gating is susceptible to high cycle to cycle variability in morphology. This pilot work of prediction using SCG waveforms enriches the framework of a comprehensive system with multiple modalities that could potentially, in real time, improve the image quality of CTA.

Cardiac screening to prevent sudden death in young athletes

Sudden cardiac death (SCD) is a sudden and unexpected death caused by loss of heart of function. SCD may occur in any population, but when it occurs on the playing field in a young individual, communities worldwide are affected. Although these events are rare, media coverage of sudden cardiac arrests in young athletes have created the impression that these events are far more common than they appear. With a heightened awareness of SCD in young athletes, screening methods have been developed to try and prevent these events from occurring. The American Heart Associations (AHA) currently employs history and physical examination alone during the preparticipation physical exam (PPE), which clears a young athlete for participation in sports. There has been recent discussion on whether to include screening electrocardiogram (ECG) in the PPE especially after one study in Italy by Corrado et al. found that using routine ECG reduced the annual incidence of SCD by 90%. In this article we will discuss how effective the current screening recommendations are, whether routine ECG use should be included in the PPE and if it is cost effective, and review other screening modalities that may be useful in the detection of young athletes at risk for SCD.

A comparison of Cornell and Sokolow-Lyon electrocardiographic criteria for left ventricular hypertrophy in a military male population in Taiwan: the Cardiorespiratory fitness and HospItalization Events in armed Forces study

BACKGROUND

The Cornell and Sokolow-Lyon electrocardiography (ECG) criteria have been widely used for diagnosing left ventricular hypertrophy (LVH) in patients with hypertension. However, the correlations of these ECG criteria with LVH were rarely compared in military members who received rigorous training, particularly of the Asian male population.

METHODS

We compared the Cornell voltage and product criteria with the Sokolow-Lyon criteria for the echocardiographic LVH in 539 military male members, ages 18-50 years and free of hypertension in the Cardiorespiratory fitness and HospItalization Events in armed Forces (CHIEF) study in Taiwan. Pearson's correlation coefficient was used to determine the association of each ECG criterion with the index of left ventricular mass (LVM, g)/height (m)^2.7. The sensitivities and specificities were estimated using a receiver-operating characteristics (ROC) curve in relation to the echocardiographic LVH which was defined as LVM index ≥49 g/m^2.7.

RESULTS

The correlations of the Cornell voltage and product criteria (r=0.24 and 0.26 respectively, both P<0.0001) were stronger than that of the Sokolow-Lyon criteria (r=0.049 and 0.095, and P=0.26 and 0.03 respectively) with the LVM index. Similarly the performances of the Cornell voltage and product criteria for the echocardiographic LVH [area under curve (AUC): 0.66 and 0.68, both P<0.0001] were superior to that of the Sokolow-Lyon criteria (AUC: 0.54 and 0.53, both P>0.1) in the area under the ROC curve analysis.

CONCLUSIONS

The Cornell ECG criteria for the echocardiographic LVH had better performance than the Sokolow-Lyon criteria in a young military male cohort in Taiwan.

A Comparison of Physiological Signal Analysis Techniques and Classifiers for Automatic Emotional Evaluation of Audiovisual Contents

This work focuses on finding the most discriminatory or representative features that allow to classify commercials according to negative, neutral and positive effectiveness based on the Ace Score index. For this purpose, an experiment involving forty-seven participants was carried out. In this experiment electroencephalography (EEG), electrocardiography (ECG), Galvanic Skin Response (GSR) and respiration data were acquired while subjects were watching a 30-min audiovisual content. This content was composed by a submarine documentary and nine commercials (one of them the ad under evaluation). After the signal pre-processing, four sets of features were extracted from the physiological signals using different state-of-the-art metrics. These features computed in time and frequency domains are the inputs to several basic and advanced classifiers. An average of 89.76% of the instances was correctly classified according to the Ace Score index. The best results were obtained by a classifier consisting of a combination between AdaBoost and Random Forest with automatic selection of features. The selected features were those extracted from GSR and HRV signals. These results are promising in the audiovisual content evaluation field by means of physiological signal processing.

Modeling temporal sequences of cognitive state changes based on a combination of EEG-engagement, EEG-workload, and heart rate metrics

The objective of this study was to investigate the feasibility of physiological metrics such as ECG-derived heart rate and EEG-derived cognitive workload and engagement as potential predictors of performance on different training tasks. An unsupervised approach based on self-organizing neural network (NN) was utilized to model cognitive state changes over time. The feature vector comprised EEG-engagement, EEG-workload, and heart rate metrics, all self-normalized to account for individual differences. During the competitive training process, a linear topology was developed where the feature vectors similar to each other activated the same NN nodes. The NN model was trained and auto-validated on combat marksmanship training data from 51 participants that were required to make "deadly force decisions" in challenging combat scenarios. The trained NN model was cross validated using 10-fold cross-validation. It was also validated on a golf study in which additional 22 participants were asked to complete 10 sessions of 10 putts each. Temporal sequences of the activated nodes for both studies followed the same pattern of changes, demonstrating the generalization capabilities of the approach. Most node transition changes were local, but important events typically caused significant changes in the physiological metrics, as evidenced by larger state changes. This was investigated by calculating a transition score as the sum of subsequent state transitions between the activated NN nodes. Correlation analysis demonstrated statistically significant correlations between the transition scores and subjects' performances in both studies. This paper explored the hypothesis that temporal sequences of physiological changes comprise the discriminative patterns for performance prediction. These physiological markers could be utilized in future training improvement systems (e.g., through neurofeedback), and applied across a variety of training environments.

Electrocardiography changes during adjuvant breast cancer therapy: incidence and risk factors

BACKGROUND/AIM

Breast cancer survivors have a higher cardiovascular morbidity/mortality rate, when compared with healthy age-matched general population. Electrocardiography (ECG) changes have been found to be associated with chemo- and radiation therapy. In the present study we investigated changes in ECG patterns following modern adjuvant therapy for breast cancer.

PATIENTS AND METHODS

A standard 12-lead electrocardiogram was recorded at rest three times (prior and after adjuvant therapy) and retrospectively analyzed in 414 breast cancer patients, who participated in the open prospective phase III randomized trial (BREX) of exercise training 2005-2007.

RESULTS

New electrocardiographic changes in the T-wave or ST-segment (depression or elevation) after the adjuvant therapy were recorded in 49 patients (13%). In multivariate analyses, hypertension treated with anti-hypertensive medication was the only significant factor associated with irreversible ECG changes (OR=4.71; 95% CI=1.36-16.38; p=0.015).

CONCLUSION

New irreversible pathological electrocardiographic changes, which acquired during the adjuvant therapy, had a clear relationship with hypertension This patients subgroup needs to be studied further.

Ultra-wideband sensors for improved magnetic resonance imaging, cardiovascular monitoring and tumour diagnostics

The specific advantages of ultra-wideband electromagnetic remote sensing (UWB radar) make it a particularly attractive technique for biomedical applications. We partially review our activities in utilizing this novel approach for the benefit of high and ultra-high field magnetic resonance imaging (MRI) and other applications, e.g., for intensive care medicine and biomedical research. We could show that our approach is beneficial for applications like motion tracking for high resolution brain imaging due to the non-contact acquisition of involuntary head motions with high spatial resolution, navigation for cardiac MRI due to our interpretation of the detected physiological mechanical contraction of the heart muscle and for MR safety, since we have investigated the influence of high static magnetic fields on myocardial mechanics. From our findings we could conclude, that UWB radar can serve as a navigator technique for high and ultra-high field magnetic resonance imaging and can be beneficial preserving the high resolution capability of this imaging modality. Furthermore it can potentially be used to support standard ECG analysis by complementary information where sole ECG analysis fails. Further analytical investigations have proven the feasibility of this method for intracranial displacements detection and the rendition of a tumour’s contrast agent based perfusion dynamic. Beside these analytical approaches we have carried out FDTD simulations of a complex arrangement mimicking the illumination of a human torso model incorporating the geometry of the antennas applied.