Table of contents

Multi-frequency electrical impedance tomography (MF-EIT) systems require current sources that are accurate over a wide frequency range (1 MHz) and with large load impedance variations. The most commonly employed current source design in EIT systems is the modified Howland circuit (MHC). The MHC requires tight matching of resistors to achieve high output impedance and may suffer from instability over a wide frequency range in an integrated solution. In this paper, we introduce a new integrated current source design in CMOS technology and compare its performance with the MHC. The new integrated design has advantages over the MHC in terms of power consumption and area. The output current and the output impedance of both circuits were determined through simulations and measurements over the frequency range of 10 kHz to 1 MHz. For frequencies up to 1 MHz, the measured maximum variation of the output current for the integrated current source is 0.8% whereas for the MHC the corresponding value is 1.5%. Although the integrated current source has an output impedance greater than 1 MΩ up to 1 MHz in simulations, in practice, the impedance is greater than 160 kΩ up to 1 MHz due to the presence of stray capacitance.

The purpose of this study was to investigate the linearity and reliability of the mechanomyographic (MMG) amplitude versus submaximal isometric force relationship for the vastus lateralis. Twenty healthy subjects (mean ± SD age = 24.0 ± 4.3 years) volunteered to perform submaximal isometric muscle actions of the dominant leg extensors from 10 to 50% of the maximum voluntary contraction (MVC) on two separate occasions. During each muscle action, the surface MMG signal was detected from the vastus lateralis. The coefficients of determination for the MMG amplitude versus isometric force relationship ranged from r² = 0.001 to 0.962, thus indicating a wide range of linearity between subjects. In addition, the linear MMG amplitude versus force slope coefficient was not particularly reliable, with an intraclass correlation coefficient of 0.743 and a standard error of the measurement of 50.66% of the mean value. These findings indicated that the MMG amplitude versus submaximal isometric force relationship did not demonstrate sufficient linearity and reliability to be used for examining the effects of interventions (e.g. training, detraining, stretching, etc). Future studies need to be done to determine the cause(s) for this lack of linearity and reliability and possible techniques that can be used to improve it.

The analysis of heart rate fluctuations, or heart rate variability (HRV), may be applied to explore children's neurodevelopment. However, previous studies have reported poor reliability (repeatability) of HRV measures in children at rest and during light exercise. Whether the reliability can be improved by controlling variables such as physical activity, breathing rate and tidal volume, or by selecting non-conventional techniques for analysing the data remains as an open question. We evaluated the short-term repeatability of RR-interval data from medicated children with congenital hypothyroidism (CH). The α₁ exponents, obtained by detrended fluctuation analysis (DFA), from the data of 21 children collected at two different sessions were compared. Elapsed days between sessions were 59 ± 33, and data were obtained during 10 min, trying to restrict the children's activity while being seated. We found statistical agreement between the means of α₁ exponents for each session (p = 0.94) and no bias with a low-coefficient variation (9.1%); an intraclass correlation coefficient ri = 0.48 ([0.14 0.72], 95% confidence interval) was also estimated. These findings, which were compared with results obtained by conventional time and frequency techniques, indicate the existence of agreement between the α₁ exponents obtained at each session, thereby providing support concerning the repeatability of HRV data as analysed by DFA in children with congenital hypothyroidism. Of particular interest was also the agreement found by using the central frequency of the high-frequency band and the parameter pNN20, both showing better or similar ri than α₁ (0.77 [0.57 0.89] and 0.51 [0.17 0.74], respectively), yet considerably better repeatability than other conventional time and frequency parameters.

Falling is an important problem in the health maintenance of people above middle age. Portable accelerometer systems have been designed to detect falls. However, false alarms induced by some dynamic motions, such as walking and jumping, are difficult to avoid. Acceleration cross-product (AC)-related methods are proposed and examined by this study to seek solutions for detecting falls with less motion-evoked false alarms. A set of tri-axial acceleration data is collected during simulated falls, posture transfers and dynamic activities by wireless sensors for making methodological comparisons. The performance of fall detection is evaluated in aspects of parameter comparison, threshold selection, sensor placement and post-fall posture (PP) recruitment. By parameter comparison, AC leads to a larger area under the receiver operating characteristic (ROC) curve than acceleration magnitude (AM). Three strategies of threshold selection, for 100% sensitivity (Sen100), for 100% specificity (Spe100) and for the best sum (BS) of sensitivity and specificity, are evaluated. Selecting a threshold based on Sen100 and BS leads to more practicable results. Simultaneous data recording from sensors in the chest and waist is performed. Fall detection based on the data from the chest shows better global accuracy. PP recruitment leads to lower false alarm ratios (FR) for both AC- and AM-based methods.

In this study, optimal methods for re-sampling and spectral estimation in frequency-domain heart rate variability (HRV) analysis were investigated through a simulation using artificial RR-interval data. Nearest-neighbour, linear, cubic spline and piecewise cubic Hermite interpolation methods were considered for re-sampling and representative non-parametric, parametric, and uneven approaches were used for spectral estimation. Based on this result, the effects of missing RR-interval data on frequency-domain HRV analysis were observed through the simulation of missing data using real RR-interval tachograms. For this simulation, data including the simulated artefact section (0–100 s) were used; these data were selected randomly from the real RR data obtained from the MIT-BIH normal sinus rhythm RR-interval database. In all, 7182 tachograms of 5 min durations were used for this analysis. The analysis for certain missing data durations is performed by 100 Monte Carlo runs. TF, VLF, LF and HF were estimated as the frequency-domain parameters in each run, and the normalized errors between the data with and without the missing data duration for these parameters were calculated. Rules obtained from the results of these simulations were evaluated with real missing RR-interval data derived from a capacitive-coupled ECG during sleep.

We propose a multi-stage approach using Wavelet and Hilbert transforms to identify uterine contraction bursts in magnetomyogram (MMG) signals measured using a 151 magnetic sensor array. In the first stage, we decompose the MMG signals by wavelet analysis into multilevel approximate and detail coefficients. In each level, the signals are reconstructed using the detail coefficients followed by the computation of the Hilbert transform. The Hilbert amplitude of the reconstructed signals from different frequency bands (0.1–1 Hz) is summed up over all the sensors to increase the signal-to-noise ratio. Using a novel clustering technique, affinity propagation, the contractile bursts are distinguished from the noise level. The method is applied on simulated MMG data, using a simple stochastic model to determine its robustness and to seven MMG datasets.

The sense of vision requires that light penetrate through the ocular lens. Experiments, performed and published by many research groups, have suggested that the lens, which has no blood vessels, relies on internally directed ion and water fluxes for its circulation, survival and transparency. We investigated the internal diffusive pathways of the lens in order to better understand the constraints that may be operating on directional lens fluxes. Small animal magnetic resonance imaging, including T2-weighted and diffusion tensor imaging, was used to measure tissue properties and diffusivity throughout cultured bovine lenses. A range of concentric regions of signal intensity was distinguished inside the lens, by both T2-weighted signal and mean diffusivity. Diffusivity mapping of the lens revealed novel anisotropic polar and equatorial zones of pronounced diffusivity directed transverse to the fiber cells. In contrast, an inner zone including the lens nucleus showed isotropic and weak diffusivity. Our results lend support to models of internally directed lens micro-circulation, by placing non-structural diffusive constraints on global patterns of fluid circulation.

Ventilation in larger animals and humans is gravity dependent and mainly distributed to the dependent lung. Little is known of the effect of gravity on ventilation distribution in small animals such as rodents. The aim of this study was to investigate gravity-dependent ventilation distribution and regional filling characteristics in rats. Ventilation distribution and regional lung filling were measured in six rats using electrical impedance tomography (EIT). Measurements were performed in four body positions (supine, prone, left and right lateral), and all animals were ventilated with increasing tidal volumes from 3 to 8 mL kg⁻¹. The effect of gravity on regional ventilation distribution was assessed with profiles of relative impedance change and calculation of the geometric centre. Regional filling was measured by calculating the slope of the plot of regional versus global relative impedance change on a breath-by-breath basis. Ventilation was significantly distributed to the non-dependent lung regardless of body position and tidal volume used. The geometric centre was located in the dependent lung in all but prone position. The regional filling characteristics followed an anatomical pattern with the posterior and the right lung generally filling faster. Gravity had little impact on regional filling. Ventilation distribution in rats is gravity dependent, whereas regional filling characteristics are dependent on anatomy.

A new method for producing frequency-difference images in electrical impedance tomography (EIT) has been recently suggested. It employed the use of a weighted voltage difference between two frequencies. In this paper, we first explain why the weighted difference is advantageous for some applications of the frequency-difference EIT (fdEIT). Based on a relationship between injection currents at two frequencies and a weighted difference of two corresponding complex voltages, we establish an fdEIT image reconstruction algorithm. In order to apply the algorithm to a practical setting, we propose the concept of an equivalent homogeneous admittivity whose value can be estimated by measuring induced voltages at the third frequency. To test this new fdEIT algorithm, we performed numerical simulations and imaging experiments using two-dimensional phantoms with frequency-dependent admittivity distributions. From reconstructed real- and imaginary-part fdEIT images, we could validate its advantage in terms of visualizing anomalies with fewer amounts of artifacts. We propose the method for applications in tumor or stroke imaging where we are mainly interested in contrast information within an fdEIT image. We suggest investigating the forward and inverse problems of an imaging domain with a frequency-dependent admittivity distribution, which has not been addressed rigorously until now.

In this paper, an approach for the estimation of single trial event-related potentials (ST-ERPs) using particle filters (PFs) is presented. The method is based on recursive Bayesian mean square estimation of ERP wavelet coefficients using their previous estimates as prior information. To enable a performance evaluation of the approach in the Gaussian and non-Gaussian distributed noise conditions, we added Gaussian white noise (GWN) and real electroencephalogram (EEG) signals recorded during rest to the simulated ERPs. The results were compared to that of the Kalman filtering (KF) approach demonstrating the robustness of the PF over the KF to the added GWN noise. The proposed method also outperforms the KF when the assumption about the Gaussianity of the noise is violated. We also applied this technique to real EEG potentials recorded in an odd-ball paradigm and investigated the correlation between the amplitude and the latency of the estimated ERP components. Unlike the KF method, for the PF there was a statistically significant negative correlation between amplitude and latency of the estimated ERPs, matching previous neurophysiological findingsSome preliminary results of this work were presented in Mohseni et al (2008b Proc. IEEE Int. Conf. Acoust. Speech Signal Process. (ICASSP) pp 465–68)..

Blood flow to the splanchnic circulation increases postprandially which may cause a reduction in systemic and cerebral perfusion leading to postprandial syncope in the elderly who lack adequate cardiovascular reserve. We used multi-station 2D phase contrast cine magnetic resonance imaging (PC-MRI) with the aim of characterizing the time course of the haemodynamic response to an oral glucose challenge test (OGCT) in the large arteries perfusing the splanchnic, systemic and cerebral circulations (superior mesenteric artery SMA, abdominal aorta AA, internal carotid arteries, ICA and vertebral arteries VA). In this study nine fasted healthy volunteers were studied. Separate cine PC-MRI scans were acquired in the neck and in the abdomen every 88 s, these two measurements being interleaved for ten baseline scans at each station with the scanner automatically moving the subject between the two stations. After ingestion of the OGCT, a further 30 cine PC-MRI scans were acquired at each station. Using this technique we were able to characterize with frequent sampling of volumetric blood flow the time course of blood flow response to the OGCT of the SMA, AA and both VA and ICA. We found a substantial variation between individuals in the amplitude and the time to the peak of the SMA blood flow response to the OGCT which correlated positively with body mass index. MRI provides a robust, non-invasive method of studying normal physiology that could be valuable in studies of diseases such as postprandial hypotension.

The measurement of the excretion of urinary albumin (albuminuria) is an important and well-established method to assess clinical outcomes. A high-performance liquid chromatography (HPLC) method has been introduced to measure albuminuria. Using this method, it was found that commonly used immunological methods do not measure a fraction of urinary albumin. Some authors presumed that the reason of immuno-unreactivity is the modification of urinary albumin; some others presumed that the difference is merely because of interference. In order to decide this question, we established an HPLC method equipped with tandem UV and fluorescent detection to assess the changes in the detectability of albumin with the rate of modification. For this measurement, differently modified forms of albumin were used. Urine samples of diabetic patients were also measured to find a potential connection between the modification rate and clinical parameters. Secondly, we have established a reversed phase HPLC method to assess the interference rate. We conclude that albumin modification does not affect immunoreactivity. The modification rate of urinary albumin in diabetic patients showed a correlation with renal function. The interference rate of the albumin peak was found to be 12.7% on average, which does not explain the difference between the two methods.

The relationship between cerebral blood volume (CBV) and blood flow (CBF) has gained widespread interest because of its utility in using functional magnetic resonance imaging and optical imaging methods to estimate the cerebral metabolic rate of oxygen (CMRO₂). A recent paper by Leung et al (2009 Physiol. Meas.30 1–12) nicely presents measurements relating CBV to cerebral blood flow velocity (CBFV) as measured by near infrared spectroscopy and transcranial Doppler, respectively. They suggest that this relationship cannot be inverted to estimate CBF (or CBFV) from CBV, and that doing so to estimate CMRO₂ is inappropriate. We argue that these data, and other related published data, do permit the estimation of CBF from CBV and thus enable CMRO₂ to be estimated when only measures of CBV and deoxygenated hemoglobin are available.

Grubb's exponent is a useful parameter quantifying cerebral hemodynamics. This letter is a reply to the Comment by Boas and Payne (2009 Physiol. Meas.30 L9–11). We reiterated our view that Grubb's exponent estimated by linear regression is theoretically inappropriate to be used to predict cerebral blood flow (CBF). In their Comment, Boas and Payne proposed the novel use of total least squares (TLS) to estimate Grubb's exponent which we also agreed is a better technique than linear regression, and Grubb's exponent estimated by TLS will allow the prediction of CBF from cerebral blood volume (CBV).