Separation of cardiac and respiratory components from the electrical bio-impedance signal using PCA and fast ICA

This paper is an attempt to separate cardiac and respiratory signals from an electrical bio-impedance (EBI) dataset. For this two well-known algorithms, namely Principal Component Analysis (PCA) and Independent Component Analysis (ICA), were used to accomplish the task. The ability of the PCA and the ICA methods first reduces the dimension and attempt to separate the useful components of the EBI, the cardiac and respiratory ones accordingly. It was investigated with an assumption, that no motion artefacts are present. To carry out this procedure the two channel complex EBI measurements were provided using classical Kelvin type four electrode configurations for the each complex channel. Thus four real signals were used as inputs for the PCA and fast ICA. The results showed, that neither PCA nor ICA nor combination of them can not accurately separate the components at least are used only two complex (four real valued) input components.Comment: 4 pages, International Conference on Control, Engineering and Information Technology (CEIT'13

Noninvasive Acquisition of the Aortic Blood Pressure Waveform

Blood pressure reflects the status of our cardiovascular system. For the measurement of blood pressure, we typically use brachial devices on the upper arm, and much less often, the radial devices with pressure sensors on the wrist. Medical doctors know that this is an unfortunate case. The brachial pressure and even more, the radial pressure, both are poor replacements for the central aortic pressure (CAP). Moreover, the devices on the market cannot provide continuous measurements 24 h. In addition, most of the ambulatory and wearable monitors do not enable acquisition of the blood pressure curves in time. These circumstances limit the accuracy of diagnosing. The aim of this chapter is to introduce our experiments, experiences and results in developing the wearable monitor for central aortic blood pressure curve by using electrical bioimpedance sensing and measurement. First, electronic circuitry with embedded data acquisition and signal processing approaches is given. Second, finding appropriate materials, configurations and placements of electrodes is of interest. Third, the results of modelling and simulations are discussed for obtaining the best sensitivity and stability of the measurement procedures. Finally, the discussion on the provided provisional experiments evaluates the obtained results. The conclusions are drawn together with the need for further development

Realization and Evaluation of the Device for Measuring the Impedance of Human Body for Detecting the Respiratory and Heart Rate

The idea of a device for measuring the impedance of human body with the target of monitoring the respiratory and heart rate is proposed in this paper. Hardware realization of the proposed idea is described with the illustration of the custom designed printed circuit board. Preparation of electrode shirts with various electrode placement configurations is introduced. Series of experimental measurements in the cases of dynamic bioimpedance reference and single human subject are described and results shown to evaluate the custom made device. The excitation frequencies in the range of 2 MHz– 20 MHz are utilized in the cases of large foil and textile electrodes to focus on the use of the capacitive connection to theobject – constituting the novelty of the current paper. The results are analysed concerning the dependency of the visual availability of the interesting signal of breathing and heart rate of the material and the placement of the electrodes. Availability of breathing is found to be evident in all of the experimented cases. The heart rate is found to be challenging because of the presence of high frequency noise

Evaluation of VoIP QoS Performance in Wireless Mesh Networks

The main focus of this research article is the evaluation of selected voice over Internet protocol (VoIP) solutions in wireless mesh network (WMN) scenarios. While WMNs have self-healing, self-forming, and dynamic topology features, they still pose challenges for the implementation of multimedia applications such as voice in various scenarios. Therefore, various solutions to make WMN more suitable for VoIP application have been proposed in the scientific literature. In this work, we have extensively explored a set of applicable scenarios by conducting experiments by means of a network simulator. The following scenarios were selected as the most representatives for performance evaluation: first responders, flooded village, remote village, and platoon deployment. Each selected scenario has been studied under six sub-scenarios corresponding to various combinations of the IEEE 802.11g, 802.11n, 802.11s, and 802.11e standards; the G.711 and G.729 codecs; and the ad hoc on demand distance vector (AODV) and hybrid wireless mesh protocol (HWMP) routing protocols. The results in terms of quality of service (measured with the mean opinion score rating scale), supported by the analysis of delay, jitter and packet loss, show that 802.11g integration with both VoIP codecs and AODV routing protocol results in better VoIP performance as compared to most other scenarios. In case of 802.11g integration with 802.11s, VoIP performance decreases as compared to the other sub-scenarios without 802.11s. The results also show that 802.11n integration with 802.11e decreases VoIP performance in larger deployments. We conclude the paper with some recommendations in terms of combinations of those standards and protocols with a view to achieve a higher quality of service for the given scenarios

Dual-Source Linear Energy Prediction (LINE-P) Model in the Context of WSNs

Energy harvesting technologies such as miniature power solar panels and micro wind turbines are increasingly used to help power wireless sensor network nodes. However, a major drawback of energy harvesting is its varying and intermittent characteristic, which can negatively affect the quality of service. This calls for careful design and operation of the nodes, possibly by means of, e.g., dynamic duty cycling and/or dynamic frequency and voltage scaling. In this context, various energy prediction models have been proposed in the literature; however, they are typically compute-intensive or only suitable for a single type of energy source. In this paper, we propose Linear Energy Prediction “LINE-P”, a lightweight, yet relatively accurate model based on approximation and sampling theory; LINE-P is suitable for dual-source energy harvesting. Simulations and comparisons against existing similar models have been conducted with low and medium resolutions (i.e., 60 and 22 min intervals/24 h) for the solar energy source (low variations) and with high resolutions (15 min intervals/24 h) for the wind energy source. The results show that the accuracy of the solar-based and wind-based predictions is up to approximately 98% and 96%, respectively, while requiring a lower complexity and memory than the other models. For the cases where LINE-P’s accuracy is lower than that of other approaches, it still has the advantage of lower computing requirements, making it more suitable for embedded implementation, e.g., in wireless sensor network coordinator nodes or gateways