Detecting Cardiac Activity by Capacitive Electrodes from a Single Point on the Wrist

Ballistocardiography (BCG) is the measurement of body movement by forces associated with heart contraction that can be used for monitoring cardiac activity. It has already been measured by force sensor and accelerometer. In this research, we developed a capacitive wristband that provides a method for single point, continuous BCG measurement, which has the potential to become a new type of sensor for wearable health care. The aim of this paper is to validate that the signal detected by capacitive electrodes is actually the BCG signal. Signals from four healthy subjects were acquired by a capacitive wristband together with Electrocardiogram (ECG). The capacitive signal was validated by both morphology matching analysis and wave occurrence time matching analysis to show that it is indeed BCG signal. JJ intervals extracted from BCG were shown to have potential to be surrogate of ECG RR series in heart rate variability analysis.

Bayesian fusion algorithm for improved oscillometric blood pressure estimation

A variety of oscillometric algorithms have been recently proposed in the literature for estimation of blood pressure (BP). However, these algorithms possess specific strengths and weaknesses that should be taken into account before selecting the most appropriate one. In this paper, we propose a fusion method to exploit the advantages of the oscillometric algorithms and circumvent their limitations. The proposed fusion method is based on the computation of the weighted arithmetic mean of the oscillometric algorithms estimates, and the weights are obtained using a Bayesian approach by minimizing the mean square error. The proposed approach is used to fuse four different oscillometric blood pressure estimation algorithms. The performance of the proposed method is evaluated on a pilot dataset of 150 oscillometric recordings from 10 subjects. It is found that the mean error and standard deviation of error are reduced relative to the individual estimation algorithms by up to 7 mmHg and 3 mmHg in estimation of systolic pressure, respectively, and by up to 2 mmHg and 3 mmHg in estimation of diastolic pressure, respectively.

Characteristic Ratio-Independent Arterial Stiffness-Based Blood Pressure Estimation

Noninvasive blood pressure (BP) measurement is an important tool for managing hypertension and cardiovascular disease. However, automated noninvasive BP measurement devices, which are usually based on the oscillometric method, do not always provide accurate estimation of BP. It has been found that change in arterial stiffness (AS) is an underlying mechanism of disagreement between an oscillometric BP monitor and a sphygmomanometer. This problem is addressed by incorporating parameters related to AS in the algorithm for BP measurement. Pulse transit time (PTT) is first used to estimate AS parameters, which are fixed into a model of the oscillometric envelope. This model can then be used to perform curve fitting to the measured signal using only four parameters: systolic BP, diastolic BP, mean BP, and lumen area at zero transmural pressure. The proposed technique is independent of the experimentally determined characteristic ratios that are commonly used in existing oscillometric methods. The accuracy of the proposed technique was evaluated by comparing with the same model without incorporation of AS, and with reference BP device measurements. The new method achieved standard deviation of error less than 8 mmHg and mean error less than 5 mmHg. The results show consistency with ANSI/AAMI SP-10 standard for noninvasive BP measurement techniques.

Bioimpedance spectroscopy method for investigating changes to intracranial dose during transcranial direct current stimulation

Tissue resistance changes upon application of DC current. We posit that in a similar fashion, that scalp and skull resistances during trancranial direct current stimulation (tDCS) are variable, resulting in changes to intracranial dose. Transcranial magnetic stimulation (TMS), electoencephelogram (EEG), functional magnetic resonance imaging (fMRI), proton magnetic resonance spectroscopy ((1)H MRS) and functional near infrared spectroscopy (fNIRS) are technologies used to measure individual neural response to tDCS. These technologies are complex and may not be directly correlated to intracranial dose. We therefore present a bioimpedance spectroscopy method of measuring changes to the intracranial dose in vivo. Scalp resistance changes are measured during tDCS. Current flow through the scalp is calculated as the ratio of voltage measured on the scalp and scalp resistance. Variation of intracranial current is indirectly calculated from changes in the current shunted through the scalp. We thus demonstrate a novel methodology of on-line monitoring of scalp resistance and current as an objective feedback of estimated individual tDCS dose.

Model of human breathing reflected signal received by PN-UWB radar

Human detection is an integral component of civilian and military rescue operations, military surveillance and combat operations. Human detection can be achieved through monitoring of vital signs. In this article, a mathematical model of human breathing reflected signal received in PN-UWB radar is proposed. Unlike earlier published works, both chest and abdomen movements are considered for modeling the radar return signal along with the contributions of fundamental breathing frequency and its harmonics. Analyses of recorded reflected signals from three subjects in different postures and at different ranges from the radar indicate that ratios of the amplitudes of the harmonics contain information about posture and posture change.

Mathematical analysis of dermal absorption rate of heavy metals

Presently 90 - 95% of children in the US wear disposable diapers before completing their toilet training at average age of 30 months. The diaper absorbs urine and liquid component from feces contaminated with excreted toxicants. In this initial study, we posit that the long contact between the diaper and the skin leads to increased dermal reabsorption of excreted body toxicants, mainly heavy metals, which are statistically associated with autism and neurodevelopmental disorder. We developed a mathematical model to analyse the increase of the level of toxicants due to dermal reabsorption after excretion. This simple kinetic model gives us the average reabsorbtion factor in the range of 1.6 to 5. The limitation of this work is that only mathematical model has been considered and it has not been verified experimentally.

Theoretical Analysis of the Effect of Temperature on Current Delivery to the Brain During tDCS

BACKGROUND

Transcranial direct current simulation (tDCS) is a non-invasive neuromodulation technique that has become increasingly popular as a potential therapeutic method for a variety of brain disorders. Since the treatment outcome may depend on the current density delivered to the brain cortical region, a significant challenge is to control the current dose reaching the cortical region.

OBJECTIVE AND METHODS

This study aims to investigate the effect of temperature on current delivery to the brain. We devised a method for modulating the amount of current delivered to the brain by changing the temperature of the scalp. We developed analytical and numerical models that describe the relationship between temperature and electrical properties of the scalp based on the following mechanisms: ion mobility and blood perfusion in scalp.

RESULTS AND CONCLUSIONS

The current delivery to brain was investigated by changing the temperature between two electrodes that are attached to the surface of the scalp, within a tolerable physiological range. Results show that by increasing the temperature between two electrodes, a higher portion of current is shunted via the scalp and the proportion of the current that penetrates the scalp and skull into brain is decreased. On the other hand, cooling the area between two electrodes on the scalp increases the current delivery to the cortical region of the brain. Our results show that cooling the scalp during tDCS can be considered as a possible way to effectively control the current delivery to the brain and increase the efficacy of tDCS.

Sampling rate of heart rate variability impacts the ability to detect acidemia in ovine fetuses near-term

BACKGROUND

To evaluate the impact of sampling rate on the predictive capability of continuous fetal heart rate (FHR) variability (fHRV) monitoring for detecting fetal acidemia during labor, we tested the performance of the root mean square of successive differences (RMSSD) in R-R intervals from the ECG when acquired with the sampling rate of 4 Hz currently available in FHR monitors, in comparison to the gold standard of 1000 Hz.

METHODS

Near-term ovine fetuses (N = 9) were chronically prepared with precordial electrodes for recording ECG, vascular catheters for blood sampling, and an umbilical cord occluder. For 1 min every 2.5 min, animals underwent mild partial umbilical cord occlusions (UCO) × 1 h, moderate partial UCO × 1 h, then complete UCO × 2 h, or until arterial pH reached <7.00. Arterial blood samples were drawn at baseline and every 20 min during the UCO series. RMSSD was calculated continuously in 5 min windows using an automated, standardized system (CIMVA.com). RESULTS are presented as mean ± SEM with significance assumed for p < 0.05.

RESULTS

Repetitive UCO resulted in pH decreasing from 7.35 ± 0.01 to 7.00 ± 0.03. In all nine animals, RMSSD increased from 16.7 ± 1.0 ms at baseline to 44.4 ± 2.3 ms, 70 ± 15 min prior to reaching the pH nadir when sampled at 1000 Hz. When sampled at 4 Hz, RMSSD at baseline measured 36.1 ± 6.0 ms and showed no significant increase during the UCO series until the pH nadir was reached. Consequently, early detection of severe hypoxic-acidemia would have been missed in all fetuses.

CONCLUSION

RMSSD as a measure of fHRV when calculated from FHR sampled at 1000 Hz allowed for the early detection of worsening hypoxic-acidemia in each fetus. However, when calculated at the low sampling rate of 4 Hz used clinically, RMSSD remained unchanged until terminally when the nadir pH was reached. For early detection of fetal acidemia during labor, more sensitive means of acquiring FHR are therefore recommended than currently deployed, e.g., trans-abdominal fetal ECG.

Coefficient-free blood pressure estimation based on pulse transit time-cuff pressure dependence

Oscillometry is a popular technique for automatic estimation of blood pressure (BP). However, most of the oscillometric algorithms rely on empirical coefficients for systolic and diastolic pressure evaluation that may differ in various patient populations, rendering the technique unreliable. A promising complementary technique for automatic estimation of BP, based on the dependence of pulse transit time (PTT) on cuff pressure (CP) (PTT-CP mapping), has been proposed in the literature. However, a theoretical grounding for this technique and a nonparametric BP estimation approach are still missing. In this paper, we propose a novel coefficient-free BP estimation method based on PTT-CP dependence. PTT is mathematically modeled as a function of arterial lumen area under the cuff. It is then analytically shown that PTT-CP mappings computed from various points on the arterial pulses can be used to directly estimate systolic, diastolic, and mean arterial pressure without empirical coefficients. Analytical results are cross-validated with a pilot investigation on ten healthy subjects where 150 simultaneous electrocardiogram and oscillometric BP recordings are analyzed. The results are encouraging whereby the mean absolute errors of the proposed method in estimating systolic and diastolic pressures are 5.31 and 4.51 mmHg, respectively, relative to the Food and Drug Administration approved Omron monitor. Our work thus shows promise toward providing robust and objective BP estimation in a variety of patients and monitoring situations.

Electrocardiogram-assisted blood pressure estimation

Accurate automatic noninvasive assessment of blood pressure (BP) presents a challenge due to conditions like arrhythmias, obesity, and postural changes that tend to obfuscate arterial amplitude pulsations sensed by the cuff. Researchers tried to overcome this challenge by analyzing oscillometric pulses with the aid of a higher fidelity signal-the electrocardiogram (ECG). Moreover, pulse transit time (PTT) was employed to provide an additional method for BP estimation. However, these methods were not fully developed, suitably integrated, or tested. To address these issues, we present a novel method whereby ECG-assisted oscillometric and PTT (measured between ECG R-peaks and maximum slope of arterial pulse peaks) analyses are seamlessly integrated into the oscillometric BP measurement paradigm. The method bolsters oscillometric analysis (amplitude modulation) with more reliable ECG R-peaks provides a complementary measure with PTT analysis (temporal modulation) and fuses this information for robust BP estimation. We have integrated this technology into a prototype that comprises a BP cuff with an embedded conductive fabric ECG electrode, associated hardware, and algorithms. A pilot study has been undertaken on ten healthy subjects (150 recordings) to validate the performance of our prototype against United States Food and Drug Administration approved Omron oscillometric monitor (HEM-790IT). Our prototype achieves mean absolute difference of less than 5 mmHg and grade A as per the British Hypertension Society protocol for estimating BP, with the reference Omron monitor.

Feasibility of continuous multiorgan variability analysis in the intensive care unit

PURPOSE

The aim of the study was to evaluate the feasibility of continuous heart and respiratory rate variability (HRV and RRV, respectively) monitoring in critically ill patients derived from electrocardiogram (ECG) and end-tidal capnography (etCO(2)) waveforms.

METHODS

Thirty-four patients (age, 56.5 ± 15.9 years; Acute Physiology and Chronic Health Evaluation II score, 22.8 ± 6.7) underwent continuous recording of ECG and etCO(2) waveforms from intensive care unit admission and intubation to discharge or maximum of 14 days. Overlapping 5-minute windows were analyzed with a wide range of variability measures (time, frequency, entropy, and scale-invariant and nonlinear domains). Waveform data quality, presence of disconnections and arrhythmias, quality of beat and breath detection, and subsequent variability computations were evaluated.

RESULTS

Patients were enrolled for 11.0 ± 3.6 days. The proportion of missing waveform data among all patients was (median [interquartile range, maximum]) 2.9% (1.3%-9.7%, 36.4%) for ECG and 3.1% (1.1%-11.4%, 84.5%) for etCO(2). Heart rate variability data loss (ie, proportion of windows removed) was 1.3% (1.0%-2.1%, 5.9%) due to disconnection, 0.6% (0.1%-3.9%, 39.5%) due to atrial fibrillation, and 6.6% (1.4%-17.9%, 89.0%) due to data cleaning. Respiratory rate variability data loss was 7.3% (2.9%-11.6%, 47.7%) due to disconnection (or apnea) and 5.5% (2.9%-8.4%, 56.4%) due to cleaning. Continuous individualized multiorgan variability analysis processing resulted in HRV and RRV computations for 81.2% ± 25.0% and 87.5% ± 11.9% of available ECG and etCO(2) waveform data, respectively.

CONCLUSIONS

The quality of continuously recorded ECG and etCO(2) waveforms in critically ill patients is adequate for subsequent continuous variability monitoring in this pilot study. The clinical utility of continuous variability analysis merits further investigation.

Continuous multi-parameter heart rate variability analysis heralds onset of sepsis in adults

BACKGROUND

Early diagnosis of sepsis enables timely resuscitation and antibiotics and prevents subsequent morbidity and mortality. Clinical approaches relying on point-in-time analysis of vital signs or lab values are often insensitive, non-specific and late diagnostic markers of sepsis. Exploring otherwise hidden information within intervals-in-time, heart rate variability (HRV) has been documented to be both altered in the presence of sepsis, and correlated with its severity. We hypothesized that by continuously tracking individual patient HRV over time in patients as they develop sepsis, we would demonstrate reduced HRV in association with the onset of sepsis.

METHODOLOGY/PRINCIPAL FINDINGS

We monitored heart rate continuously in adult bone marrow transplant (BMT) patients (n = 21) beginning a day before their BMT and continuing until recovery or withdrawal (12+/-4 days). We characterized HRV continuously over time with a panel of time, frequency, complexity, and scale-invariant domain techniques. We defined baseline HRV as mean variability for the first 24 h of monitoring and studied individual and population average percentage change (from baseline) over time in diverse HRV metrics, in comparison with the time of clinical diagnosis and treatment of sepsis (defined as systemic inflammatory response syndrome along with clinically suspected infection requiring treatment). Of the 21 patients enrolled, 4 patients withdrew, leaving 17 patients who completed the study. Fourteen patients developed sepsis requiring antibiotic therapy, whereas 3 did not. On average, for 12 out of 14 infected patients, a significant (25%) reduction prior to the clinical diagnosis and treatment of sepsis was observed in standard deviation, root mean square successive difference, sample and multiscale entropy, fast Fourier transform, detrended fluctuation analysis, and wavelet variability metrics. For infected patients (n = 14), wavelet HRV demonstrated a 25% drop from baseline 35 h prior to sepsis on average. For 3 out of 3 non-infected patients, all measures, except root mean square successive difference and entropy, showed no significant reduction. Significant correlation was present amongst these HRV metrics for the entire population.

CONCLUSIONS/SIGNIFICANCE

Continuous HRV monitoring is feasible in ambulatory patients, demonstrates significant HRV alteration in individual patients in association with, and prior to clinical diagnosis and treatment of sepsis, and merits further investigation as a means of providing early warning of sepsis.

Gamma-spectroscopy investigation of radon daughter deposition on electrostatically charged surfaces

The effect of static electricity on the deposition of radon daughters onto charged surfaces is determined by a combined experimental and theoretical analysis. Experiments with charged surfaces exposed to the air in a normal working environment are analysed to determine an empirical radon daughter deposition rate. This factor is utilized to estimate the daughter deposition on a human head which is exposed to similar conditions of air quality and static charging. The results indicate that typical levels of static electricity can enhance the deposition of radon daughters by orders of magnitude compared with the uncharged condition. The corresponding yearly alpha dose equivalents to the basal skin layer and to the eye exceed recommended limits. Beside having an important impact from the public health perspective, these results suggest that the obscure and contradictory correlations found between radon concentrations and adverse health effects may arise from a failure to account for the effects of static electricity.