Different excitation signals are applicable in the wideband impedance spectroscopy in general. However, in electrical bioimpedance (EBI) measurements, there are limitations that set specific demands on the properties of the excitation signals. This paper compares the efficiency of different excitation signals in a graspable presentation and gives recommendations for their use. More exactly, the paper deals with finding the efficient excitation waveforms for the fast spectroscopy of electrical bioimpedance. Nevertheless, the described solutions could be useful also in other implementations of impedance spectroscopy intended for frequency domain characterization of different objects.
It has been demonstrated before that human skin can be modeled as a memristor (memory resistor). Here we realize a memristor bridge by applying two voltages of opposite signs at two different skin sites. By this setup it is possible to use human skin as a frequency doubler and half-wave rectifier which is an application of the non-linear electrical properties of human skin. The corresponding electrical measurements are non-linear since these are affected by the applied stimulus itself.
In a succession of articles published over 65 years ago, Sir Alan Lloyd Hodgkin and Sir Andrew Fielding Huxley established what now forms our physical understanding of excitation in nerve, and how the axon conducts the action potential. They uniquely quantified the movement of ions in the nerve cell during the action potential, and demonstrated that the action potential is the result of a depolarizing event across the cell membrane. They confirmed that a complete depolarization event is followed by an abrupt increase in voltage that propagates longitudinally along the axon, accompanied by considerable increases in membrane conductance. In an elegant theoretical framework, they rigorously described fundamental properties of the Na+ and K+ conductances intrinsic to the action potential.
Notwithstanding the elegance of Hodgkin and Huxley’s incisive and explicative series of discoveries, their model is mathematically complex, relies on no small number of stochastic factors, and has no analytical solution. Solving for the membrane action potential and the ionic currents requires integrations approximated using numerical methods. In this article I present an analytical formalism of the nerve action potential, Vm and that of the accompanying cell membrane electric field, Em. To conclude, I present a novel description of Vm in terms of a single, nonlinear differential equation. This is an original stand-alone article: the major contribution is the latter, and how this description coincides with the cell membrane electric field. This work has necessitated unifying information from two preceding papers [1,2], each being concerned with the development of closed-form descriptions of the nerve action potential, Vm.
Lung pathologies such as edema, atelectasis or pneumonia are potentially life threatening conditions. Especially in critically ill and mechanically ventilated patients, an early diagnosis and treatment is crucial to prevent an Acute Respiratory Distress Syndrome . Thus, continuous monitoring tool for the lung condition available at the bedside would be highly appreciated. One concept for this is Electrical Impedance Tomography (EIT). In EIT, an electrode belt of typically 16 or 32 electrodes is attached at the body surface and multiple impedance measurements are performed. From this, the conductivity change inside the body is reconstructed in a two-dimensional image. In various studies, EIT proved to be a useful tool for quantifying recruitment maneuvers, the assessment of the ventilation homogeneity, the detection of lung edema or perfusion monitoring [2, 3, 4, 5]. Nevertheless, the main problem of EIT is the low spatial resolution (compared to CT) and the limitation to two dimensional images. In this paper, we try to address the latter issue: Instead of projecting conductivity changes onto a two-dimensional image, we adjust electrode positions to focus single tetrapolar measurements to specific, three-dimensional regions of interest. In earlier work, we defined guidelines to achieve this focusing [6, 7]. In this paper, we demonstrate in simulations and in a water tank experiment that applying these guidelines can help to detect pathologies in specific lung regions.
Tetra-polar electrical impedance measurement (TPIM) with a square geometry of electrodes is useful in the characterization of epithelial tissues, especially in the detection of cervical cancer at precancerous stages. However, in TPIM, the peak planar sensitivity just below the electrode surface is almost zero and increases to a peak value at a depth of about one third to one half of the electrode separation. To get high sensitivity for the epithelial layer, having thicknesses of 200 μm to 300 μm, the electrode separation needed is less than 1 mm, which is difficult to achieve in practical probes. This work proposes a conical conducting layer in front of a pencil like probe with a square geometry of TPIM electrodes to create virtual electrodes with much smaller separation at the body surface, thus increasing the sensitivity of the epithelial tissues. To understand the improvements, if any, 3D sensitivity distribution and transfer impedance were simulated using COMSOL Multiphysics software for a simplified body tissue model containing a 300 μm epithelial layer. It has been shown that fractional contribution of an epithelial layer can be increased several times placing a cylindrical conducting layer in between the tissue surface and the electrodes, which can further be enhanced using a conical conducting layer. The results presented in this paper can be used to choose an appropriate electrode separation, conducting layer height and cone parameters for enhanced sensitivity in the epithelial layer.
Bioimpedance measurement systems often use the Howland current sources to excite the biological material under study. Usually, difference or instrumentation amplifiers are used to measure the resulting voltage drop on this material. In these circuits, common mode voltage appears as artifacts in the measurement. Most researches on current sources are focused on improving the output impedance, letting other characteristics aside. In this paper, it is made a brief review on the load common mode voltage and output swing of various topologies of Howland current sources. Three circuits are proposed to reduce load common mode voltage and enhance load capability by using a fully differential amplifier as active component. These circuits are equated, simulated and implemented. The three proposed circuits were able to deliver an output current with cut-off frequency (-3dB) higher than 1 MHz for loads as big as 4.7 kΩ. The worst measured load common mode voltage was smaller than 24 mV for one of the circuits and smaller than 8 mV for the other two. Consequently, it could be obtained increases in the Common Mode Rejection Ratio (CMRR) up to 60 dB when compared to the Enhanced Howland Current Source (EHCS).
Accurate assessment of experienced pain is a well-known problem in the clinical practices. Therefore, a proper method for pain detection is highly desirable. Electrodermal activity (EDA) is known as a measure of the sympathetic nervous system activity, which changes during various mental stresses. As pain causes mental stress, EDA measures may reflect the felt pain. This study aims to evaluate changes in skin conductance responses (SCRs), skin potential responses (SPRs), and skin susceptance responses (SSRs) simultaneously as a result of sequences of electrical (painful) stimuli with different intensities. EDA responses as results of painful stimuli were recorded from 40 healthy volunteers. The stimuli with three different intensities were produced by using an electrical stimulator. EDA responses significantly changed (increased) with respect to the intensity of the stimuli. Both SCRs and SSRs showed linear relationship with the painful stimuli. It was found that the EDA responses, particularly SCRs (p < 0.001) and SSRs (p = 0.001) were linearly affected by the intensity of the painful stimuli. EDA responses, in particular SCRs, may be used as a useful indicator for assessment of experienced pain in clinical settings.
Dominant arm bioimpedance spectroscopy (BIS) and lumbar and hip dual energy X-ray absorptiometry (DXA) measurements were conducted simultaneously on 48 post-menopausal women, aged between 43 and 86 years, with no hip or arm fracture history at Department of Radiology of Istanbul University Cerrahpasa Hospital. According to lumbar DXA results, 21 women were classified as normal, 22 as osteopenia and 5 as osteoporosis; whereas hip DXA results classified 30 women as normal, 15 as osteopenia and 3 as osteoporosis. Only 26 participants had identical lumbar and hip bone mineral density (BMD) diagnostic results. Dominant arm characteristic frequencies of normal subjects were statistically significantly different from osteoporotic subjects based on both lumbar (p < 0.005) and hip classification groups (p < 0.001). Hip and lumbar spine DXA BMD values were significantly correlated (r = 0.55, p < 0.005). The dominant arm BIS characteristic frequency, considered as the single predictor in earlier diagnosis of osteoporosis, was found negatively correlated with DXA measurements for both hip and lumbar spine regions. The Spearman rank correlation coefficient of BIS values with the hip DXA values (r = -0.53, p < 0.001) was higher than that of lumbar spine (r = -0.37, p < 0.001). In receiver operating characteristic (ROC) curve analysis, the best discrimination of dominant arm characteristic frequency was made between normal and osteoporotic subjects based on the hip subgroups (p < 0.001). Both lumbar bone mineral content (BMC) (r = -0.47, p < 0.001) and hip BMC (r = -0.4340, p < 0.005) were statistically significantly correlated with dominant arm characteristic frequency.
Computational dosimetry has become the main tool for estimating induced electric fields within brain tissues in transcranial direct current stimulation (tDCS) which is recently attracting the attention of researches for motor function disturbances such as Parkinson’s disease. This paper investigates the effect of including or excluding the very thin meninges in computing tDCS electric fields using CST software. For this purpose, two models of the brain with and without meninges were used to induce electric field with two DC current electrodes (2 mA) in regions of the model referring to M1 and Prefrontal Cortex (FP2) similar to tDCS. Considering meninges, the results have shown differences in the induced field showing that there might be problems with conventional models in which meninges are not taken into account.