Improved EEG source localization with Bayesian uncertainty modelling of unknown skull conductivity.

Electroencephalography (EEG) source imaging is an ill-posed inverse problem that requires accurate conductivity modelling of the head tissues, especially the skull. Unfortunately, the conductivity values are difficult to determine in vivo. In this paper, we show that the exact knowledge of the skull conductivity is not always necessary when the Bayesian approximation error (BAE) approach is exploited. In BAE, we first postulate a probability distribution for the skull conductivity that describes our (lack of) knowledge on its value, and model the effects of this uncertainty on EEG recordings with the help of an additive error term in the observation model. Before the Bayesian inference, the likelihood is marginalized over this error term. Thus, in the inversion we estimate only our primary unknown, the source distribution. We quantified the improvements in the source localization when the proposed Bayesian modelling was used in the presence of different skull conductivity errors and levels of measurement noise. Based on the results, BAE was able to improve the source localization accuracy, particularly when the unknown (true) skull conductivity was much lower than the expected standard conductivity value. The source locations that gained the highest improvements were shallow and originally exhibited the largest localization errors. In our case study, the benefits of BAE became negligible when the signal-to-noise ratio dropped to 20 dB.

Electrical impedance tomography for three-dimensional drug release monitoring.

Electrical impedance tomography (EIT) was adapted to monitor drug release three-dimensionally as a function of time. EIT is an electrical imaging modality in which the three-dimensional conductivity distribution inside an object is computed based on electrical measurements from the boundaries. Here, the three-dimensional concentration distribution was monitored with the help of the experimentally determined relationship between drug concentration and conductivity. The EIT monitoring was carried out with propranolol hydrochloride tablets in an apparatus similar to USP dissolution apparatus 2. The release profiles estimated using EIT matched well with the UV/VIS spectrophotometric analyses that were performed as a reference. There are several benefits conferred by three-dimensional monitoring, i.e., comprehensive information about the release process; no need to take samples during experiments; and not essential to assume homogenous concentration distribution in the drug release analysis. EIT is an in-line technique, and moreover, it is non-intrusive and non-invasive. The possibilities and the characteristics of the EIT monitoring are described in detail, and some potential drug release applications are proposed. EIT is especially encouraged to be exploited for research and development purposes.

An electrical impedance tomography-based approach to monitor in vitro sodium chloride dissolution from pharmaceutical tablets.

An approach to monitor in vitro dissolution process from pharmaceutical tablets utilizing electrical impedance tomography (EIT) is introduced. In the demonstration, a tablet containing sodium chloride (NaCl) was dissolution tested using tap water as a dissolution medium within an apparatus similar to the United States Pharmacopoeia dissolution apparatus II. During the process, the three-dimensional sodium chloride concentration distribution was monitored with EIT measurements as a function of time. For EIT measurements, an array of electrodes was attached on the boundary of the dissolution vessel, a set of alternating electric currents was injected through the electrodes, and the resulting voltages were measured. With these data and by applying mathematical algorithms, an approximation for the spatial/temporal concentration distribution inside the vessel was computed. It was found that the computed distributions were relatively homogeneous. A NaCl release curve was computed by integrating the concentration distribution over the vessel volume, and the final value of the curve matched well with the reference point based on the weight loss of the tablet. Finally, EIT monitoring is suggested to be used for research and product development purposes.