Showing papers in "Physiological Measurement in 2011"
TL;DR: It is demonstrated that fallers have difficulty with specific TUG aspects that can be quantified using an accelerometer, as well as complementary, objective measures that allow for a more complete, sensitive TUG-based fall risk assessment.
Abstract: The Timed Up and Go (TUG) test is a widely used measure of mobility and fall risk among older adults that is typically scored using a stopwatch. We tested the hypothesis that a body-fixed accelerometer can enhance the ability of the TUG to identify community-living older adults with a relatively high fall risk of unknown origin. Twenty-three community-living elderly fallers (76.0 ± 3.9 years) and 18 healthy controls (68.3 ± 9.1 years) performed the TUG while wearing a 3D-accelerometer on the lower back. Accelerationderived parameters included Sit-to-Stand and Stand-to-Sit times, amplitude range (Range), and slopes (Jerk). Average step duration, number of steps, average step length, gait speed, acceleration-median, and standard-deviation were also calculated. While the stopwatch-based TUG duration was not significantly different between the groups, acceleration-derived TUG duration was significantly higher (p = 0.007) among the fallers. Fallers generally exhibited lower Range and Jerk (p < 0.01). While TUG stopwatch duration successfully identified 63% of the subjects, an accelerometer-derived threemeasure-combination correctly classified 87% of the subjects. Accelerometerderived measures were generally not correlated with TUG duration. These findings demonstrate that fallers have difficulty with specific TUG aspects that can be quantified using an accelerometer. Without compromising simplicity of testing, an accelerometer can apparently be combined with TUG duration
166 citations
TL;DR: The study suggests that non-stationarities increase the likelihood to overestimate the contribution of sympathetic control and affect the power of statistical tests utilized to discriminate conditions and/or groups.
Abstract: The autonomic regulation is non-invasively estimated from heart rate variability (HRV). Many methods utilized to assess autonomic regulation require stationarity of HRV recordings. However, non-stationarities are frequently present even during well-controlled experiments, thus potentially biasing HRV indices. The aim of our study is to quantify the potential bias of spectral, symbolic and entropy HRV indices due to non-stationarities. We analyzed HRV series recorded in healthy subjects during uncontrolled daily life activities typical of 24 h Holter recordings and during predetermined levels of robotic-assisted treadmill-based physical exercise. A stationarity test checking the stability of the mean and variance over short HRV series (about 300 cardiac beats) was utilized to distinguish stationary periods from non-stationary ones. Spectral, symbolic and entropy indices evaluated solely over stationary periods were contrasted with those derived from all the HRV segments. When indices were calculated solely over stationary series, we found that (i) during both uncontrolled daily life activities and controlled physical exercise, the entropy-based complexity indices were significantly larger; (ii) during uncontrolled daily life activities, the spectral and symbolic indices linked to sympathetic modulation were significantly smaller and those associated with vagal modulation were significantly larger; (iii) while during uncontrolled daily life activities, the variance of spectral, symbolic and entropy rate indices was significantly larger, during controlled physical exercise, it was smaller. The study suggests that non-stationarities increase the likelihood to overestimate the contribution of sympathetic control and affect the power of statistical tests utilized to discriminate conditions and/or groups.
146 citations
TL;DR: Results demonstrate that automated identification of signal artifact in the PPG signal through waveform morphology analysis is achievable and a clear improvement in the accuracy of the derived heart rate is also evident when such methods are employed.
Abstract: Pulse oximetry has been extensively used to estimate oxygen saturation in blood, a vital physiological parameter commonly used when monitoring a subject's health status. However, accurate estimation of this parameter is difficult to achieve when the fundamental signal from which it is derived, the photoplethysmograph (PPG), is contaminated with noise artifact induced by movement of the subject or the measurement apparatus. This study presents a novel method for automatic rejection of artifact contaminated pulse oximetry waveforms, based on waveform morphology analysis. The performance of the proposed algorithm is compared to a manually annotated gold standard. The creation of the gold standard involved two experts identifying sections of the PPG signal containing good quality PPG pulses and/or noise, in 104 fingertip PPG signals, using a simultaneous electrocardiograph (ECG) signal as a reference signal. The fingertip PPG signals were each 1 min in duration and were acquired from 13 healthy subjects (10 males and 3 females). Each signal contained approximately 20 s of purposely induced artifact noise from a variety of activities involving subject movement. Some unique waveform morphology features were extracted from the PPG signals, which were believed to be correlated with signal quality. A simple decision-tree classifier was employed to arrive at a classification decision, at a pulse-by-pulse resolution, of whether a pulse was of acceptable quality for use or not. The performance of the algorithm was assessed using Cohen's kappa coefficient (κ), sensitivity, specificity and accuracy measures. A mean κ of 0.64 ± 0.22 was obtained, while the mean sensitivity, specificity and accuracy were 89 ± 10%, 77 ± 19% and 83 ± 11%, respectively. Furthermore, a heart rate estimate, extracted from uncontaminated sections of PPG, as identified by the algorithm, was compared with the heart rate derived from an uncontaminated simultaneous ECG signal. The mean error between both heart rate readings was 0.49 ± 0.66 beats per minute (BPM), in comparison to an error value observed without using the artifact detection algorithm of 7.23 ± 5.78 BPM. These results demonstrate that automated identification of signal artifact in the PPG signal through waveform morphology analysis is achievable. In addition, a clear improvement in the accuracy of the derived heart rate is also evident when such methods are employed.
145 citations
TL;DR: New data indicate that diet and natural intra-individual biological and diurnal variability result in wide variations in breath acetone concentration, which places an uncertainty in the use of breath acet one alone to monitor blood glucose and glycaemic control.
Abstract: Previous measurements of acetone concentrations in the exhaled breath of healthy individuals and the small amount of comparable data for individuals suffering from diabetes are briefly reviewed as a prelude to the presentation of new data on the sporadic and wide variations of breath acetone that occur in ostensibly healthy individuals Data are also presented which show that following a ketogenic diet taken by eight healthy individuals their breath acetone concentrations increased up to five times over the subsequent 6 h Similarly, the breath acetone increased six and nine times when a low carbohydrate diet was taken by two volunteers and remained high for the several days for which the diet was continued These new data, together with the previous data, clearly indicate that diet and natural intra-individual biological and diurnal variability result in wide variations in breath acetone concentration This places an uncertainty in the use of breath acetone alone to monitor blood glucose and glycaemic control, except and unless the individual acts as their own control and is cognizant of the need for dietary control
123 citations
TL;DR: The ability of MMT more than TMG to detect an inherent change in stiffness can be conceivably exploited in a number of clinical/therapeutic applications that have to do with unnatural changes in passive muscle stiffness.
Abstract: Portable tensiomyography (TMG) and myotonometry (MMT) devices have been developed to measure mechanical and contractile properties of skeletal muscle. The aim of this study was to explore the sensitivity of the aforementioned techniques in detecting a change in passive mechanical properties of the biceps femoris (BF) muscle as a result of change in knee joint angle (i.e. muscle length). BF responses were assessed in 16 young participants (23.4 ± 4.9 years), at three knee joint angles (0°, 45° and 90°), for maximal isometric torque (MIT) along with myo-electrical activity. Contractile and mechanical properties were measured in a relaxed state. Inter-day reliability of the TMG and MMT was also assessed. MIT changed significantly (p < 0.01) across the three angles, so did stiffness and other parameters measured with MMT (p < 0.01). Conversely, TMG could detect changes only at two knee angles (0° and 45°, p < 0.01), when there is enough tension in the muscle. Reliability was overall insufficient for TMG whilst absolute reliability was excellent (coefficient of variation < 5%) for MMT. The ability of MMT more than TMG to detect an inherent change in stiffness can be conceivably exploited in a number of clinical/therapeutic applications that have to do with unnatural changes in passive muscle stiffness.
119 citations
TL;DR: Results show that the traditional (and still most common) adjacent stimulation and measurement patterns have by far the poorest performance, and are presented as a call to action: adjacent patterns are harmful, and should be abandoned.
Abstract: We characterize the ability of electrical impedance tomography (EIT) to distinguish changes in internal conductivity distributions, and analyze it as a function of stimulation and measurement patterns. A distinguishability measure, z, is proposed which is related to the signal-to-noise ratio of a medium and to the probability of detection of conductivity changes in a region of interest. z is a function of the number of electrodes, the EIT stimulation and measurement protocol, the stimulation amplitude, the measurement noise, and the size and location of the contrasts. Using this measure we analyze various choices of stimulation and measurement patterns under the constraint of medical electrical safety limits (maximum current into the body). Analysis is performed for a planar placement of 16 electrodes for simulated 3D tank and chest shapes, and measurements in a saline tank. Results show that the traditional (and still most common) adjacent stimulation and measurement patterns have by far the poorest performance (by 6.9 ×). Good results are obtained for trigonometric patterns and for pair drive and measurement patterns separated by over 90°. Since the possible improvement over adjacent patterns is so large, we present this result as a call to action: adjacent patterns are harmful, and should be abandoned. We recommend using pair drive and measurement patterns separated by one electrode less than 180°. We describe an approach to modify an adjacent pattern EIT system by adjusting electrode placement.
103 citations
TL;DR: The results showed that the empirical formula proposed by Chon et al is a good method for analyzing the random signal, but not an appropriate tool for analyzing nonlinear signals, such as the logistic or HRV signals.
Abstract: Approximate entropy (ApEn) is widely accepted as a complexity measure of the heart rate variability (HRV) signal, but selecting the criteria for the threshold value r is controversial. This paper aims to verify whether Chon's method of forecasting the r(max) is an appropriate one for the HRV signal. The standard limb lead ECG signals of 120 subjects were recorded for 10 min in a supine position. The subjects were divided into two groups: the heart failure (22 females and 38 males, median age 62.4 ± 12.6) and healthy control group (33 females and 27 males, median age 51.5 ± 16.9). Three types of ApEn were calculated: the ApEn(0.2) using the recommended constant r = 0.2, the ApEn(chon) using Chon's method and the ApEn(max) using the true r(max). A Wilcoxon rank sum test showed that the ApEn(0.2) (p = 0.267) and the ApEn(max) (p = 0.813) had no statistical differences between the two groups, while the ApEn(chon) (p = 0.040) had. We generated a synthetic database to study the effect of two influential factors (the signal length N and the ratio of short- and long-term variability sd(1)/sd(2)) on the empirical formula in Chon's method (Chon et al 2009 IEEE Eng. Med. Biol. Mag. 28 18-23). The results showed that the empirical formula proposed by Chon et al is a good method for analyzing the random signal, but not an appropriate tool for analyzing nonlinear signals, such as the logistic or HRV signals.
102 citations
TL;DR: Measuring both in-phase and quadrature components of trans-impedances at multiple frequencies simultaneously, the KHU Mark2 is apt at spectroscopic EIT imaging.
Abstract: We report the development of a new multi-frequency electrical impedance tomography (EIT) system called the KHU Mark2. It is descended from the KHU Mark1 in terms of technical details such as digital waveform generation, Howland current source with multiple generalized impedance converters and digital phase-sensitive demodulators. New features include flexible electrode configurations to accommodate application-specific requirements, multiple independent current sources and voltmeters for fully parallel operations, improved data acquisition speeds for faster frame rates and compact mechanical design. Given an electrode configuration, we can design an analog backplane in such a way that both current injections and voltage measurements can be done without using any switch. The KHU Mark2 is based on an impedance measurement module (IMM) comprising a current source and a voltmeter. Using multiple IMMs, we can construct a multi-channel system with 16, 32 or 64 channels, for example. Adopting a pipeline structure, it has the maximum data acquisition speed of 100 scans s(-1) with the potential to detect fast physiological changes during respiration and cardiac activity. Measuring both in-phase and quadrature components of trans-impedances at multiple frequencies simultaneously, the KHU Mark2 is apt at spectroscopic EIT imaging. In this paper, we describe its design, construction, calibration and performance evaluation. It has about 84 dB signal-to-noise ratio and 0.5% reciprocity error. Time-difference images of an admittivity phantom are presented showing spectroscopic admittivity images. Future application studies using the KHU Mark2 are briefly discussed.
97 citations
TL;DR: It is found that measurements of standard deviation, sample asymmetry and sample entropy are highly related to imminent clinical illness.
Abstract: We have applied principles of statistical signal processing and nonlinear dynamics to analyze heart rate time series from premature newborn infants in order to assist in the early diagnosis of sepsis, a common and potentially deadly bacterial infection of the bloodstream. We began with the observation of reduced variability and transient decelerations in heart rate interval time series for hours up to days prior to clinical signs of illness. We find that measurements of standard deviation, sample asymmetry and sample entropy are highly related to imminent clinical illness. We developed multivariable statistical predictive models, and an interface to display the real-time results to clinicians. Using this approach, we have observed numerous cases in which incipient neonatal sepsis was diagnosed and treated without any clinical illness at all. This review focuses on the mathematical and statistical time series approaches used to detect these abnormal heart rate characteristics and present predictive monitoring information to the clinician.
96 citations
TL;DR: Results indicate that the studied ZHF sensor tracks T(es) very well in hot and stable ambient conditions and may be a promising alternative for reliable non-invasive continuous core temperature measurement in hospital.
Abstract: Reliable continuous core temperature measurement is of major importance for monitoring patients. The zero heat flux method (ZHF) can potentially fulfil the requirements of non-invasiveness, reliability and short delay time that current measurement methods lack. The purpose of this study was to determine the performance of a new ZHF device on the forehead regarding these issues. Seven healthy subjects performed a protocol of 10 min rest, 30 min submaximal exercise (average temperature increase about 1.5 °C) and 10 min passive recovery in ambient conditions of 35 °C and 50% relative humidity. ZHF temperature (Tzhf) was compared to oesophageal (Tes) and rectal (Tre) temperature. ΔTzhf-Tes had an average bias standard deviation of 0.17 ± 0.19 °C in rest, -0.05 ± 0.18 °C during exercise and -0.01 ± 0.20 °C during recovery, the latter two being not significant. The 95% limits of agreement ranged from -0.40 to 0.40 °C and Tzhf had hardly any delay compared to Tes. Tre showed a substantial delay and deviation from Tes when core temperature changed rapidly. Results indicate that the studied ZHF sensor tracks Tes very well in hot and stable ambient conditions and may be a promising alternative for reliable non-invasive continuous core temperature measurement in hospital. © 2011 Institute of Physics and Engineering in Medicine.
86 citations
TL;DR: Real-time breath analysis revealed previously unmeasurable differences in clearance kinetics of ammonia and trimethylamine, potentially useful in assessment of dialysis efficacy.
Abstract: Non-invasive monitoring of breath ammonia and trimethylamine using Selected-ion-flow-tube mass spectroscopy (SIFT-MS) could provide a real-time alternative to current invasive techniques. Breath ammonia and trimethylamine were monitored by SIFT-MS before, during and after haemodialysis in 20 patients. In 15 patients (41 sessions), breath was collected hourly into Tedlar bags and analysed immediately (group A). During multiple dialyses over 8 days, five patients breathed directly into the SIFT-MS analyser every 30 min (group B). Pre- and post-dialysis direct breath concentrations were compared with urea reduction, Kt/V and creatinine concentrations. Dialysis decreased breath ammonia, but a transient increase occurred mid treatment in some patients. Trimethylamine decreased more rapidly than reported previously. Pre-dialysis breath ammonia correlated with pre-dialysis urea in group B (r(2) = 0.71) and with change in urea (group A, r(2) = 0.24; group B, r(2) = 0.74). In group B, ammonia correlated with change in creatinine (r(2) = 0.35), weight (r(2) = 0.52) and Kt/V (r(2) = 0.30). The ammonia reduction ratio correlated with the urea reduction ratio (URR) (r(2) = 0.42) and Kt/V (r(2) = 0.38). Pre-dialysis trimethylamine correlated with Kt/V (r(2) = 0.21), and the trimethylamine reduction ratio with URR (r(2) = 0.49) and Kt/V (r(2) = 0.36). Real-time breath analysis revealed previously unmeasurable differences in clearance kinetics of ammonia and trimethylamine. Breath ammonia is potentially useful in assessment of dialysis efficacy.
TL;DR: Using nonlinear parameters such as approximate entropy, fractal dimension, correlation dimension, largest Lyapunov exponent and Hurst exponent to extract physiological information can potentially reduce the need of polysomnography (PSG) and bring advantages to patients, because the proposed system is less cumbersome when compared to PSG.
Abstract: Sleep apnoea is a very common sleep disorder which can cause symptoms such as daytime sleepiness, irritability and poor concentration. To monitor patients with this sleeping disorder we measured the electrical activity of the heart. The resulting electrocardiography (ECG) signals are both non-stationary and nonlinear. Therefore, we used nonlinear parameters such as approximate entropy, fractal dimension, correlation dimension, largest Lyapunov exponent and Hurst exponent to extract physiological information. This information was used to train an artificial neural network (ANN) classifier to categorize ECG signal segments into one of the following groups: apnoea, hypopnoea and normal breathing. ANN classification tests produced an average classification accuracy of 90%; specificity and sensitivity were 100% and 95%, respectively. We have also proposed unique recurrence plots for the normal, hypopnea and apnea classes. Detecting sleep apnea with this level of accuracy can potentially reduce the need of polysomnography (PSG). This brings advantages to patients, because the proposed system is less cumbersome when compared to PSG.
TL;DR: It is found that both the model's thickness of the stratum corneum as well as experimental soaking conditions affect the fit between the model and measurements, and it is essential that the electrical properties of the skin are presented in the context of the ion concentration aswell as the soaking time.
Abstract: The functional integrity and pathology of the skin is reflected in its electrical impedance spectra. Non-invasive electrical impedance measurements of intact skin are dominated by the high impedic stratum corneum in low frequencies and with increasing frequency gradually comes to be dominated by viable skin. Models of this multi-layered organ can increase our understanding of the actual physical properties/dimensions and facilitate better diagnostics in certain applications. Therefore, a mathematical model considering conservation of charge in the various layers of the skin and adjacent electrodes is derived and validated with experimental findings; the latter was carried out on 60 young female subjects. The impact of the stratum corneum thickness, inundation, solvent and cohort size on the electrical properties is studied. Both model parameters and experimental conditions were adjusted for calibration and subsequent validation of the model with measurements. It is found that both the model's thickness of the stratum corneum as well as experimental soaking conditions (both time and saline concentration) affect the fit between the model and measurements. It is concluded that it is essential that the electrical properties of the skin are presented in the context of the ion concentration (if a moisturizer is employed) as well as the soaking time. Further refinements should be made to determine even more accurate dielectrical properties of the stratum corneum and viable skin layers by accounting for the true skin thickness and the heterogeneity of the skin layers-this would be useful in applications where subtle alterations in the skin are of interest.
TL;DR: The effect of conformal deformations on image reconstruction when using the CEM was of specific interest and was quantified using a measure that compared an ideal image to the reconstructed image, in this case a no-noise reconstruction that isolated the electrodes' effects.
Abstract: Electrical impedance tomography (EIT) measures the conductivity distribution within an object based on the current applied and voltage measured at surface electrodes. Thus, EIT images are sensitive to electrode properties (i.e. contact impedance, electrode area and boundary shape under the electrode). While some of these electrode properties have been investigated individually, this paper investigates these properties and their interaction using finite element method simulations and the complete electrode model (CEM). The effect of conformal deformations on image reconstruction when using the CEM was of specific interest. Observed artefacts were quantified using a measure that compared an ideal image to the reconstructed image, in this case a no-noise reconstruction that isolated the electrodes' effects. For electrode contact impedance and electrode area, uniform reductions to all electrodes resulted in ringing artefacts in the reconstructed images when the CEM was used, while parameter variations that were not correlated amongst electrodes resulted in artefacts distributed throughout the image. When the boundary shape changed under the electrode, as with non-symmetric conformal deformations, using the CEM resulted in structured distortions within the reconstructed image. Mean electrode contact impedance increases, independent of inter-electrode variation, did not result in artefacts in the reconstructed image.
TL;DR: It is found that MSE of heart rate and blood pressure signals is sensitive to changes in autonomic balance caused by postural change from the supine to the standing position, and provides a sensitive tool to detect changes inautonomous balance as induced byPostural change.
Abstract: Cardiovascular control acts over multiple time scales, which introduces a significant amount of complexity to heart rate and blood pressure time series. Multiscale entropy (MSE) analysis has been developed to quantify the complexity of a time series over multiple time scales. In previous studies, MSE analyses identified impaired cardiovascular control and increased cardiovascular risk in various pathological conditions. Despite the increasing acceptance of the MSE technique in clinical research, information underpinning the involvement of the autonomic nervous system in the MSE of heart rate and blood pressure is lacking. The objective of this study is to investigate the effect of orthostatic challenge on the MSE of heart rate and blood pressure variability (HRV, BPV) and the correlation between MSE (complexity measures) and traditional linear (time and frequency domain) measures. MSE analysis of HRV and BPV was performed in 28 healthy young subjects on 1000 consecutive heart beats in the supine and standing positions. Sample entropy values were assessed on scales of 1?10. We found that MSE of heart rate and blood pressure signals is sensitive to changes in autonomic balance caused by postural change from the supine to the standing position. The effect of orthostatic challenge on heart rate and blood pressure complexity depended on the time scale under investigation. Entropy values did not correlate with the mean values of heart rate and blood pressure and showed only weak correlations with linear HRV and BPV measures. In conclusion, the MSE analysis of heart rate and blood pressure provides a sensitive tool to detect changes in autonomic balance as induced by postural change.
TL;DR: The results establish the feasibility of developing a snore-based OSAHS community-screening device, which does not require any contact measurements and is based solely on snore sound analysis.
Abstract: Snoring is the most common symptom of obstructive sleep apnea hypopnea syndrome (OSAHS), which is a serious disease with high community prevalence. The standard method of OSAHS diagnosis, known as polysomnography (PSG), is expensive and time consuming. There is evidence suggesting that snore-related sounds (SRS) carry sufficient information to diagnose OSAHS. In this paper we present a technique for diagnosing OSAHS based solely on snore sound analysis. The method comprises a logistic regression model fed with snore parameters derived from its features such as the pitch and total airway response (TAR) estimated using a higher order statistics (HOS)-based algorithm. Pitch represents a time domain characteristic of the airway vibrations and the TAR represents the acoustical changes brought about by the collapsing upper airways. The performance of the proposed method was evaluated using the technique of K-fold cross validation, on a clinical database consisting of overnight snoring sounds of 41 subjects. The method achieved 89.3% sensitivity with 92.3% specificity (the area under the ROC curve was 0.96). These results establish the feasibility of developing a snore-based OSAHS community-screening device, which does not require any contact measurements.
TL;DR: The results showed that the PHS model generated unreliable predictions on body core temperature when human subjects wore thick protective clothing such as firefighting clothing (I(cl) > 1.0 clo) and there is a need for further extension for the clothing insulation validation range of the P HS model.
Abstract: In this paper, the prediction accuracy of the PHS (predicted heat strain) model on human physiological responses while wearing protective clothing ensembles was examined. Six human subjects (aged 29 ± 3 years) underwent three experimental trials in three different protective garments (clothing thermal insulation Icl ranges from 0.63 to 2.01 clo) in two hot environments (40 °C, relative humidities: 30% and 45%). The observed and predicted mean skin temperature, core body temperature and sweat rate were presented and statistically compared. A significant difference was found in the metabolic rate between FIRE (firefighting clothing) and HV (high visibility clothing) or MIL (military clothing) (p 1.0 clo). The predicted mean skin temperatures in three clothing ensembles HV, MIL and FIRE were also outside the expected limits. Thus, there is a need for further extension for the clothing insulation validation range of the PHS model. It is recommended that the PHS model should be amended and validated by individual algorithms, physical or physiological parameters, and further subject studies.
TL;DR: A new method applicable in real time to detect ambient and internal body noises manifested in heart sound during acquisition, developed on the basis of the periodic nature of heart sounds and physiologically inspired criteria.
Abstract: Heart sound is a valuable biosignal for diagnosis of a large set of cardiac diseases. Ambient and physiological noise interference is one of the most usual and highly probable incidents during heart sound acquisition. It tends to change the morphological characteristics of heart sound that may carry important information for heart disease diagnosis. In this paper, we propose a new method applicable in real time to detect ambient and internal body noises manifested in heart sound during acquisition. The algorithm is developed on the basis of the periodic nature of heart sounds and physiologically inspired criteria. A small segment of uncontaminated heart sound exhibiting periodicity in time as well as in the time-frequency domain is first detected and applied as a reference signal in discriminating noise from the sound. The proposed technique has been tested with a database of heart sounds collected from 71 subjects with several types of heart disease inducing several noises during recording. The achieved average sensitivity and specificity are 95.88% and 97.56%, respectively.
TL;DR: Significant changes from baseline were present in the responses to the cognitive and affective stimuli at non-palmar sites, suggesting that these sites may provide viable signal measurements for use in affective computing and human-machine interface applications.
Abstract: Measurements of blood volume pulse (BVP) and skin conductance are commonly used as indications of psychological arousal in affective computing and human–machine interfaces. To date, palmar surfaces remain the primary site for these measurements. Placement of sensors on palmar surfaces, however, is undesirable when recordings are fraught with motion and pressure artifacts. These artifacts are frequent when the human participant has involuntary movements as in hyperkinetic cerebral palsy. This motivates the use of alternative measurement sites. The present study examined the correlation between measurements of blood volume pulse and skin conductance obtained from three different sites on the body (fingers, toes and ear for BVP; fingers, toes and arch of the foot for skin conductance) in response to cognitive and affective stimuli. The results of this pilot study indicated significant inter-site correlation among signal features derived from different sites, with the exception of BVP amplitude, the number of electrodermal reactions and the slope of the electrodermal activity response. We attribute these differences in part to inter-site discrepancies in local skin conditions, such as skin temperature. Despite these differences, significant changes from baseline were present in the responses to the cognitive and affective stimuli at non-palmar sites, suggesting that these sites may provide viable signal measurements for use in affective computing and human–machine interface applications.
TL;DR: Recent extensions allow assessing directed interactions from short and transient signals and are particularly suited for the analysis of evoked and event-related activity.
Abstract: The study of synchronization phenomena in coupled dynamical systems is an active field of research in many scientific disciplines including the neurosciences. Over the last decades, a number of time series analysis techniques have been proposed to capture both linear and nonlinear aspects of interactions. While most of these techniques allow one to quantify the strength of interactions, developments that resulted from advances in nonlinear dynamics and in information and synchronization theory aim at assessing directed interactions. Most of these techniques, however, assume the underlying systems to be at least approximately stationary and require a large number of data points to robustly assess directed interactions. Recent extensions allow assessing directed interactions from short and transient signals and are particularly suited for the analysis of evoked and event-related activity.
TL;DR: A systematic approach to evaluate the performance of the EIT systems and all details of the phantom, test objects and position controller design are made publicly available including the source code of the evaluation and reporting software.
Abstract: An electrical impedance tomography (EIT) system images internal conductivity from surface electrical stimulation and measurement. Such systems necessarily comprise multiple design choices from cables and hardware design to calibration and image reconstruction. In order to compare EIT systems and study the consequences of changes in system performance, this paper describes a systematic approach to evaluate the performance of the EIT systems. The system to be tested is connected to a saline phantom in which calibrated contrasting test objects are systematically positioned using a position controller. A set of evaluation parameters are proposed which characterize (i) data and image noise, (ii) data accuracy, (iii) detectability of single contrasts and distinguishability of multiple contrasts, and (iv) accuracy of reconstructed image (amplitude, resolution, position and ringing). Using this approach, we evaluate three different EIT systems and illustrate the use of these tools to evaluate and compare performance. In order to facilitate the use of this approach, all details of the phantom, test objects and position controller design are made publicly available including the source code of the evaluation and reporting software.
TL;DR: A method is proposed to improve the robustness of HAR to the installation errors of accelerometers by using Gram-Schmidt orthonormalization and a low-pass filter with a cut-off frequency of 10 Hz to eliminate the main effect of the sensor's misplacement.
Abstract: Human activity recognition (HAR) by using wearable accelerometers has gained significant interest in recent years in a range of healthcare areas, including inferring metabolic energy expenditure, predicting falls, measuring gait parameters and monitoring daily activities. The implementation of HAR relies heavily on the correctness of sensor fixation. The installation errors of wearable accelerometers may dramatically decrease the accuracy of HAR. In this paper, a method is proposed to improve the robustness of HAR to the installation errors of accelerometers. The method first calculates a transformation matrix by using Gram–Schmidt orthonormalization in order to eliminate the sensor's orientation error and then employs a low-pass filter with a cut-off frequency of 10 Hz to eliminate the main effect of the sensor's misplacement. The experimental results showed that the proposed method obtained a satisfactory performance for HAR. The average accuracy rate from ten subjects was 95.1% when there were no installation errors, and was 91.9% when installation errors were involved in wearable accelerometers.
TL;DR: An effective PAF predictor which is based on the analysis of the RR-interval signal is proposed which presents better results than other existing approaches.
Abstract: Atrial fibrillation (AF) is the most common cardiac arrhythmia and increases the risk of stroke. Predicting the onset of paroxysmal AF (PAF), based on noninvasive techniques, is clinically important and can be invaluable in order to avoid useless therapeutic intervention and to minimize risks for the patients. In this paper, we propose an effective PAF predictor which is based on the analysis of the RR-interval signal. This method consists of three steps: preprocessing, feature extraction and classification. In the first step, the QRS complexes are detected from the electrocardiogram (ECG) signal and then the RR-interval signal is extracted. In the next step, the recurrence plot (RP) of the RR-interval signal is obtained and five statistically significant features are extracted to characterize the basic patterns of the RP. These features consist of the recurrence rate, length of longest diagonal segments (Lmax ), average length of the diagonal lines (Lmean), entropy, and trapping time. Recurrence quantification analysis can reveal subtle aspects of dynamics not easily appreciated by other methods and exhibits characteristic patterns which are caused by the typical dynamical behavior. In the final step, a support vector machine (SVM)-based classifier is used for PAF prediction. The performance of the proposed method in prediction of PAF episodes was evaluated using the Atrial Fibrillation Prediction Database (AFPDB) which consists of both 30 min ECG recordings that end just prior to the onset of PAF and segments at least 45 min distant from any PAF events. The obtained sensitivity, specificity, positive predictivity and negative predictivity were 97%, 100%, 100%, and 96%, respectively. The proposed methodology presents better results than other existing approaches.
TL;DR: The study confirmed the need for developing CPR abilities in untrained lay persons via training by real-time feedback from the instructor or CC-Device and embedded feedback was shown to be comprehensible and easy to be followed and interpreted.
Abstract: This study aims to contribute to the scarce data available about the abilities of untrained lay persons to perform hands-only cardio-pulmonary resuscitation (CPR) on a manikin and the improvement of their skills during training with an autonomous CPR feedback device. The study focuses on the following questions: (i) Is there a need for such a CPR training device? (ii) How adequate are the embedded visual feedback and audio guidance for training of lay persons who learn and correct themselves in real time without instructor guidance? (iii) What is the achieved effect of only 3 min of training? This is a prospective study in which 63 lay persons (volunteers) received a debriefing to basic life support and then performed two consecutive 3 min trials of hands-only CPR on a manikin. The pre-training skills of the lay persons were tested in trial 1. The training process with audio guidance and visual feedback from a cardio compression control device (CC-Device) was recorded in trial 2. After initial debriefing for correct chest compressions (CC) with rate 85-115 min(-1), depth 3.8-5.4 cm and complete recoil, in trial 1 the lay persons were able to perform CC without feedback at mean rate 95.9 ± 18.9 min(-1), mean depth 4.13 ± 1.5 cm, with low proportions of 'correct depth', 'correct rate' and 'correct recoil' at 33%, 43%, 87%, resulting in the scarce proportion of 14% for compressions, which simultaneously fulfill the three quality criteria ('correct all'). In trial 2, the training process by the CC-Device was established by the significant improvement of the CC skills until the 60th second of training, when 'correct depth', 'correct rate' and 'correct recoil' attained the plateau of the highest quality at 82%, 90%, 96%, respectively, resulting in 73% 'correct all' compressions within 3 min of training. The training was associated with reduced variance of the mean rate 102.4 ± 4.7 min(-1) and mean depth 4.3 ± 0.4 cm, indicating a steady CC performance achieved among all trained participants. Multivariable linear regression showed that the compression depth, rate and complete chest recoil did not strongly depend on lay person age, gender, height, weight in pre-training and training stage (correlation coefficient below 0.54). The study confirmed the need for developing CPR abilities in untrained lay persons via training by real-time feedback from the instructor or CC-Device. The CC-Device embedded feedback was shown to be comprehensible and easy to be followed and interpreted. The high quality of the CC-Device-assisted training process of lay persons was confirmed. Thus learning or refresher courses in basic life support could be organized for more people trained at the same time with fewer instructors needed only for the initial debriefing and presentation of the CC-Device.
TL;DR: The use of ρ(N)(,5) as a new comparator allowing a clinician to incrementally monitor removal of extracellular fluid from patients over the course of dialysis treatments is established.
Abstract: Prescription of an appropriate dialysis target weight (dry weight) requires accurate evaluation of the degree of hydration. The aim of this study was to investigate whether a state of normal hydration (DWcBIS) as defined by calf bioimpedance spectroscopy (cBIS) and conventional whole body bioimpedance spectroscopy (wBIS) could be characterized in hemodialysis (HD) patients and normal subjects (NS). wBIS and cBIS were performed in 62 NS (33 m/29 f) and 30 HD patients (16 m/14 f) pre- and post-dialysis treatments to measure extracellular resistance and fluid volume (ECV) by the whole body and calf bioimpedance methods. Normalized calf resistivity (ρN,5) was defined as resistivity at 5 kHz divided by the body mass index. The ratio of wECV to total body water (wECV/TBW) was calculated. Measurements were made at baseline (BL) and at DWcBIS following the progressive reduction of post-HD weight over successive dialysis treatments until the curve of calf extracellular resistance is flattened (stabilization) and the ρN,5 was in the range of NS. Blood pressures were measured pre- and post-HD treatment. ρN,5 in males and females differed significantly in NS. In patients, ρN,5 notably increased with progressive decrease in body weight, and systolic blood pressure significantly decreased pre- and post-HD between BL and DWcBIS respectively. Although wECV/TBW decreased between BL and DWcBIS, the percentage of change in wECV/TBW was significantly less than that in ρN,5 (−5.21 ± 3.2% versus 28 ± 27%, p < 0.001). This establishes the use of ρN,5 as a new comparator allowing a clinician to incrementally monitor removal of extracellular fluid from patients over the course of dialysis treatments. The conventional whole body technique using wECV/TBW was less sensitive than the use of ρN,5 to measure differences in body hydration between BL and DWcBIS.
TL;DR: A mathematical programming model in which size and safety constraints are considered is proposed for transmission efficiency, optimal frequency and current, and overall system effectiveness and can be used to direct the design of transmitting and receiving coils.
Abstract: Multipurpose active capsule endoscopes have drawn considerable attention in recent years, but these devices continue to suffer from energy limitations. A wireless power supply system is regarded as a practical way to overcome the power shortage problem in such devices. This paper focuses on the efficiency optimization of a wireless energy supply system with size and safety constraints. A mathematical programming model in which these constraints are considered is proposed for transmission efficiency, optimal frequency and current, and overall system effectiveness. To verify the feasibility of the proposed method, we use a wireless active capsule endoscope as an illustrative example. The achieved efficiency can be regarded as an index for evaluating the system, and the proposed approach can be used to direct the design of transmitting and receiving coils.
TL;DR: Computer fluid dynamic simulations carried out for idealized CCA geometries derived from 3D contrast-enhanced magnetic resonance angiograms demonstrated that mild cervical curvature is sufficient to prevent flow from fully-developing to axisymmetry, independent of the degree of thoracic curvature.
Abstract: Clinical and engineering studies typically assume that the common carotid artery (CCA) is straight enough to assume fully developed flow, yet recent studies have demonstrated the presence of skewed velocity profiles. Toward elucidating the influence of mild vascular curvatures on blood flow patterns and atherosclerosis, this study aimed to characterize the three-dimensional shape of the human CCA. The left and right carotid arteries of 28 participants (63 ± 12 years) in the VALIDATE (Vascular Aging-–The Link that Bridges Age to Atherosclerosis) study were digitally segmented from 3D contrast-enhanced magnetic resonance angiograms, from the aortic arch to the carotid bifurcation. Each CCA was divided into nominal cervical and thoracic segments, for which curvatures were estimated by least-squares fitting of the respective centerlines to planar arcs. The cervical CCA had a mean radius of curvature of 127 mm, corresponding to a mean lumen:curvature radius ratio of 1:50. The thoracic CCA was significantly more curved at 1:16, with the plane of curvature tilted by a mean angle of 25° and rotated close to 90° with respect to that of the cervical CCA. The left CCA was significantly longer and slightly more curved than the right CCA, and there was a weak but significant increase in CCA curvature with age. Computational fluid dynamic simulations carried out for idealized CCA geometries derived from these and other measured geometric parameters demonstrated that mild cervical curvature is sufficient to prevent flow from fully-developing to axisymmetry, independent of the degree of thoracic curvature. These findings reinforce the idea that fully developed flow may be the exception rather than the rule for the CCA, and perhaps other nominally long and straight vessels.
TL;DR: Most of the features utilized for FHR characterization, including FIGO, HRV, nonlinear, wavelet, and time and frequency domain features, are investigated and assessed based on their statistical significance in the task of distinguishing the FHR into three FIGO classes.
Abstract: Cardiotocography is the monitoring of fetal heart rate (FHR) and uterine contractions (TOCO), used routinely since the 1960s by obstetricians to detect fetal hypoxia. The evaluation of the FHR in clinical settings is based on an evaluation of macroscopic morphological features and so far has managed to avoid adopting any achievements from the HRV research field. In this work, most of the features utilized for FHR characterization, including FIGO, HRV, nonlinear, wavelet, and time and frequency domain features, are investigated and assessed based on their statistical significance in the task of distinguishing the FHR into three FIGO classes. We assess the features on a large data set (552 records) and unlike in other published papers we use three-class expert evaluation of the records instead of the pH values. We conclude the paper by presenting the best uncorrelated features and their individual rank of importance according to the meta-analysis of three different ranking methods. The number of accelerations and decelerations, interval index, as well as Lempel-Ziv complexity and Higuchi's fractal dimension are among the top five features.
TL;DR: It is suggested that H1 or 2Pm perform better than LR analysis and should be used for the estimation of CrCP and RAP for both static and dynamic applications.
Abstract: The critical closing pressure (CrCP) of cerebral circulation is normally estimated by extrapolation of instantaneous velocity?pressure curves. Different methods of estimation were analysed to assess their robustness and reproducibility in both static and dynamic applications. In ten healthy subjects (mean ? SD age 37.5 ? 9.2 years) continuous recordings of arterial blood pressure (BP, Finapres) and bilateral cerebral blood flow velocity (transcranial Doppler ultrasound, middle cerebral arteries) were obtained at rest. Each session consisted of three separate 5 min recordings. A total of four recording sessions for each subject took place over a 2 week period. A total of 117 recordings contained 34?014 cardiac cycles. For each cardiac cycle, CrCP and resistance-area product (RAP) were estimated using linear regression (LR), principal component analysis (PCA), first harmonic fitting (H1), 2-point systolic/diastolic values (2Ps) and 2-point mean/diastolic values (2Pm). LR and PCA were also applied using only the diastolic phase (LRd, PCAd). The mean values of CrCP and RAP for the entire 5 min recording ('static' condition) were not significantly different for LRd, PCAd, H1 and 2Pm, as opposed to the other methods. The same four methods provided the best results regarding the absence of negative values of CrCP and the coefficient of variation (CV) of the intra-subject standard error of the mean (SEM). On the other hand, 'dynamic' applications, such as the transfer function between mean BP and RAP (coherence and RAP step response) led to a different ranking of methods, but without significant differences in CV SEM coherence. For the CV of the RAP step response though, LRd and PCAd performed badly. These results suggest that H1 or 2Pm perform better than LR analysis and should be used for the estimation of CrCP and RAP for both static and dynamic applications.
TL;DR: Results were supportive of the notion that the parasympathetic system is pre-potent to influence slower (than respiratory) frequency components in HRV spectrum and that HRV was not a simple linear surrogate for cardiac vagal effects.
Abstract: The origin of very low frequency (VLF) oscillations in the power spectra of heart rate variability (HRV) is controversial with possible mechanisms involving thermoregulation and/or renin-angiotensin-aldosterone system. Recently, a major contribution from vagal influences has been suggested. The present study investigated the behaviour of VLF (0.004-0.040 Hz) components of HRV power spectra in a group of healthy male volunteers during their exposure to (1) dry, supine, immersion in thermo-neutral water for 6 h (n = 7) and (2) non-hypoxic hypobaria (breathing 40-60% oxygen at 15,000' simulated in a decompression chamber) for 5 h (n = 15). The two manoeuvres are established to increase vagal outflow. During both the manoeuvres, all the frequency domain indices of HRV exhibited a significant increase. Increase in HRV was much more than that in the R-R interval. At 6 h of immersion, the R-R interval increased by ∼ 15% but the total power increased ∼ fourfold. Similarly, at 5 h of exposure to hypobaria, total power increased ∼ twofold with a very modest increase in an R-R of ∼ 9%. Increase in spectral power was appreciable even after normalization with mean R-R(2). Increase in VLF during immersion was more than reported during enalaprilat blockade of angiotensin convertase enzyme. Plasma renin activity did not vary during hypobaria. There was a significant increase in pNN50, an established marker of cardiac vagal activity. Centre frequencies of the spectra and slope (β) of the relation between log(PSD) and log(frequency) did not change. Results were supportive of the notion that the parasympathetic system is pre-potent to influence slower (than respiratory) frequency components in HRV spectrum. Additionally, such an effect was without a change in the time constant of effector responses or pacemaker frequencies of VLF and LF periodicities and HRV was not a simple linear surrogate for cardiac vagal effects. An invariance of spectral exponent (β) ruled out contamination of VLF and LF spectra from fractal power as an alternate explanation.