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Abstract

Apnea is one of the deadliest diseases that can be prevented and cured if it is detected in time. In this paper, we propose a precise method for early detection of the obstructive sleep apnea (OSA) disease using the latest feature selection and extraction methods. The feature selection in this paper is based on the Dual tree complex wavelet (DT-CWT) coefficients of the ECG signals of several patients. The feature extraction from these coefficients is done using frequency and time techniques. The Feature selection is done using the spectral regression discriminant analysis (SRDA) algorithm and the classification is performed using the hybrid RBF network. A hybrid RBF neural network is introduced in this paper for detecting apnea that is much less computationally demanding than the previously presented SVM networks. Our findings showed a 3 percent improvement in the detection and at least a 30 percent reduction in the computational complexity in comparison with methods that have been presented recently.

Abstract

Nonhuman primates are often used in biomedical research and to investigate physiologic processes that occur in man. Impedance plethysmography was used to measure calf, thigh, pelvic, abdominal, and thoracic volume changes in ten Rhesus and eight squirrel monkeys during five-minute exposures to HUT and HDT at angles of 5, 10, and 20 degrees. Calf, rump and tail measurements were made in three squirrel monkeys at 10 and 20 degrees of HUT and HDT. Fluid volume changes in all segments of the Rhesus monkeys were found to change during HUT an HDT in direct relation to the angle of tilt used. However, the volume changes that occurred in the squirrel monkeys were found to be quite different. Their calf, thigh, and pelvic segments lost volume during both HUT and HDT while their abdominal and thoracic segments responded similarly to those of the Rhesus monkeys. These results and those of the calf/tail measurements of the squirrel monkeys suggest that they may utilize their tails as a compensatory reservoir during postural changes and therefore, may not be an appropriate animal model for man under some orthostatic test conditions.

Abstract

Impedance cardiography (ICG) is a non-invasive method of hemodynamic measurement, mostly known for estimation of stroke volume and cardiac output based on characteristic features of the signal. Compared with electrocardiography, the knowledge on the morphology of the ICG signal is scarce, especially with respect to age-dependent changes in ICG waveforms. Based on recordings from ten younger (20–29 years) and ten older (60–79) healthy human subjects after three different levels of physical activity, the typical interbeat ICG waveforms were derived based on ensemble averages. Comparison of these waveforms between the age groups indicates the following differences: a later initial upward deflection for the younger group, an additional hump in the waveform from many older subjects not presented in the younger group, and a more pronounced second wave in the younger group. The explanation for these differences is not clear, but may be related to arterial stiffness. Further studies are suggested to determine whether these morphological differences have clinical value.

Abstract

Overall survival of oncologic patients is strongly influenced by the incidence of malnutrition, with subsequent loss of muscle mass until sarcopenia. In this respect, the assessment of body composition has a pivotal role in order to manage the clinical consequences of muscle loss.

Aim:

This study focuses on the body composition assessment in oncologic patients, following a diet plan in order to detect and contrast neoplastic cachexia.

Materials and Method:

35 oncologic patients were enrolled and divided into two groups: 24 responders (R) and 11 non-responders (NR). Anthropometric data were collected and body composition was assessed through bioimpedentiometry. All patients received an individualized normocaloric diet. Energetic content was assigned on the basis of individual basal metabolic rate estimated by BIA. All patients were revaluated by anthropometry and bioimpedentiometry 3 and 6 months thereafter.

Results:

Comparing the two male groups R and NR after 6 months, the former maintained almost the same confidence interval, unlike the latter whose interval increased, indicating a light worsening both of body composition and of clinical conditions. Furthermore, in the same male responder group, an improvement of the phase angle (PhA), a positive prognostic factor, was found, with an average weight loss between 2,6 – 3 kg of fat mass (FM). Besides, data show how the R female group maintained the confidence interval unlike the NR female group, whose confidence interval remarkably increased, therefore indicating an important alteration of body composition and subsequently a clinical conditions worsening. Finally, comparing the NR male group with the NR female group after 6 months, a remarkable worsening of body composition (marker of tissue decay and damage) could be noticed in the latter group.

Conclusion:

After 6 months, NR patients show worse results (both in the body composition and in the clinical conditions) compared to the responders, with particularly worse results in females, probably because of a genetically determined sex-related smaller muscle cells and inferior muscular strength. A multidimensional assessment of oncologic patient is necessary, with a special attention to nutritional evaluation and body composition monitoring, in order to avoid malnutrition and subsequent further clinical worsening.

Abstract

Sixteen volunteers each drank 700 ml sugar-containing soft drink during two successive periods and the blood sugar was measured at 10 min intervals together with electrical impedance spectroscopy and near infrared spectroscopy (NIR). A maximum correlation of 0.46 was found for the electrical measurements but no clear separation between low and high blood glucose levels were found in the NIR measurements. The latter was attributed to the experimental design where the NIR probe was removed from the skin between each measurement.

Abstract

A circuit is presented that enables measurement of skin electrical conductance, susceptance, and potential simultaneously beneath the same monopolar electrode. Example measurements are shown to confirm the function of the circuit. The measurements are also in accordance with earlier findings that changes in skin conductance and potential do not always correspond and hence contain unique information.

Abstract

The objective of this study was to determine the potential value of electrical impedance myography (EIM) for assessing lumbosacral paraspinal muscle (LPM) condition in lower back pain (LBP) patients. Standard methods for assessing the condition of LPMs, such as magnetic resonance imaging, are inconvenient and expensive. One tool that could be useful for this purpose is electrical impedance myography (EIM) a technique that can be performed rapidly at the bedside. After undergoing a screening history and examination, subjects were studied with the mView EIM device (Myolex, Inc, Boston). Bilateral LPMs were measured three times each and the two closest sets of measurements averaged on each side. Data analysis included non-parametric two-group comparisons between healthy subjects and back pain patients, receiver-operating curve analyses, and correlation analyses to age and body mass index. A total of 86 healthy individuals (median age (interquartile range) (IQR), 45.5 years (30.3–56.0 years), 42 men, 44 women) and 47 LBP (median age 51.0 year (39.5–57.5) years, 21 men, 26 women) were enrolled. Median EIM 100kHz phase was lower in the LBP patients (9.3°(IQR 8.4°–10.6°) versus 11.4°(IQR 9.4°–13.0°), p = 0.0007). Significantly increased normalized side-to-side differences were present for all three EIM variables (e.g., median 100 kHz phase 0.15 (IQR 0.07–0.31 in LBP patients versus 0.09 (IQR 0.04–0.17) in healthy individuals). A significant correlation between 100 kHz EIM phase and reactance was found with age (Rspearman=−0.46, P=0.0002 and Rspearman=−0.440, P=0.0003) but not for resistance. This study provides early evidence supporting that EIM has the potential to serve as a useful tool for evaluating the condition of LPMs.

Abstract

Electrical impedance spectroscopy (EIS) measurements on cells is a proven method to assess stem cell proliferation and differentiation. Cell regenerative medicine (CRM) is an emerging field where the need to develop and deploy stem cell assessment techniques is paramount as experimental treatments reach pre-clinical and clinical stages. However, EIS measurements on cells is a method requiring extensive post-processing and analysis. As a contribution to address this concern, we developed three machine learning models for three different stem cell lines able to classify the measured data as proliferation or differentiation laying the stone for future studies on using machine learning to profile EIS measurements on stem cells spectra.

Abstract

Electrical impedance tomography (EIT) has a large potential as a two dimensional imaging technique and is gaining attention among researchers across various fields of engineering. Beamforming techniques stem from the array signal processing field and is used for spatial filtering of array data to evaluate the location of objects. In this work the circular electrodes are treated as an array of sensors and beamforming technique is used to localize the object(s) in an electrical field. The conductivity distributions within a test tank is obtained by an EIT system in terms of electrode voltages. These voltages are then interpolated using elliptic partial differential equations. Finally, a narrowband beamformer detects the peak in the output response signal to localize the test object(s). Test results show that the beamforming technique can be used as a secondary method that may provide complementary information about accurate position of the test object(s) using an eight electrode EIT system. This method could possibly open new avenues for spatial EIT data filtering techniques with an understanding that the inverse problem is more likely considered here as a source localization algorithm instead as an image reconstruction algorithm.