Sensor-Location-Specific Joint Acquisition of Peripheral Artery Bioimpedance and Photoplethysmogram for Wearable Applications.

BACKGROUND: Cardiovascular diseases (CVDs), being the culprit for one-third of deaths globally, constitute a challenge for biomedical instrumentation development, especially for early disease detection. Pulsating arterial blood flow, providing access to cardiac-related parameters, involves the whole body. Unobtrusive and continuous acquisition of electrical bioimpedance (EBI) and photoplethysmography (PPG) constitute important techniques for monitoring the peripheral arteries, requiring novel approaches and clever means. METHODS: In this work, five peripheral arteries were selected for EBI and PPG signal acquisition. The acquisition sites were evaluated based on the signal morphological parameters. A small-data-based deep learning model, which increases the data by dividing them into cardiac periods, was proposed to evaluate the continuity of the signals. RESULTS: The highest sensitivity of EBI was gained for the carotid artery (0.86%), three times higher than that for the next best, the posterior tibial artery (0.27%). The excitation signal parameters affect the measured EBI, confirming the suitability of classical 100 kHz frequency (average probability of 52.35%). The continuity evaluation of the EBI signals confirmed the advantage of the carotid artery (59.4%), while the posterior tibial artery (49.26%) surpasses the radial artery (48.17%). The PPG signal, conversely, commends the location of the posterior tibial artery (97.87%). CONCLUSIONS: The peripheral arteries are highly suitable for non-invasive EBI and PPG signal acquisition. The posterior tibial artery constitutes a candidate for the joint acquisition of EBI and PPG signals in sensor-fusion-based wearable devices-an important finding of this research.

Electrical Bioimpedance Analysis for Evaluating the Effect of Pelotherapy on the Human Skin: Methodology and Experiments.

BACKGROUND: Pelotherapy is the traditional procedure of applying curative muds on the skin's surface-shown to have a positive effect on the human body and cure illnesses. The effect of pelotherapy is complex, functioning through several mechanisms, and depends on the skin's functional condition. The current research objective was to develop a methodology and electrodes to assess the passage of the chemical and biologically active compounds of curative mud through human skin by performing electrical bioimpedance (EBI) analysis. METHODS: The methodology included local area mud pack and simultaneous tap water compress application on the forearms with the comparison to the measurements of the dry skin. A custom-designed small-area gold-plated electrode on a rigid printed circuit board, in a tetrapolar configuration, was designed. A pilot study experiment with ten volunteers was performed. RESULTS: Our results indicated the presence of an effect of pelotherapy, manifested by the varying electrical properties of the skin. Distinguishable difference in the measured real part of impedance (R) emerged, showing a very strong correlation between the dry and tap-water-treated skin (r = 0.941), while a poor correlation between the dry and mud-pack-treated skin (r = 0.166) appeared. The findings emerged exclusively in the frequency interval of 10 kHz …1 MHz and only for R. CONCLUSIONS: EBI provides a promising tool for monitoring the variations in the electrical properties of the skin, including the skin barrier. We foresee developing smart devices for promoting the exploitation of spa therapies.

Non-Standard Electrode Placement Strategies for ECG Signal Acquisition.

BACKGROUND: Wearable technologies for monitoring cardiovascular parameters, including electrocardiography (ECG) and impedance cardiography (ICG), propose a challenging research subject. The expectancy for wearable devices to be unobtrusive and miniaturized sets a goal to develop smarter devices and better methods for signal acquisition, processing, and decision-making. METHODS: In this work, non-standard electrode placement configurations (EPC) on the thoracic area and single arm were experimented for ECG signal acquisition. The locations were selected for joint acquisition of ECG and ICG, targeted to suitability for integrating into wearable devices. The methodology for comparing the detected signals of ECG was developed, presented, and applied to determine the R, S, and T waves and RR interval. An algorithm was proposed to distinguish the R waves in the case of large T waves. RESULTS: Results show the feasibility of using non-standard EPCs, manifesting in recognizable signal waveforms with reasonable quality for post-processing. A considerably lower median sensitivity of R wave was verified (27.3%) compared with T wave (49%) and S wave (44.9%) throughout the used data. The proposed algorithm for distinguishing R wave from large T wave shows satisfactory results. CONCLUSIONS: The most suitable non-standard locations for ECG monitoring in conjunction with ICG were determined and proposed.

Study of Electrode Locations for Joint Acquisition of Impedance- and Electro-cardiography Signals.

ICG (impedance cardiography) and ECG (electrocardiography) provide important indications about functioning of the heart and of overall cardiovascular system. Measuring ICG along with ECG using wearable devices will improve the quality of health monitoring, as ICG points to important hemodynamic parameters (such as time intervals, stroke volume, cardiac output, and their variability). In this work, various electrode locations (12 different setups) have been tested for possible joint ECG & ICG data acquisition (using the same electrodes) and signal quality has been evaluated for every setup. It is shown that, while typically ICG is acquired over the whole thorax, a wrist-based joint acquisition of ECG & ICG signals can achieve acceptable signal quality and therefore can be considered in wearable sensing.

Methods for Detection of Bioimpedance Variations in Resource Constrained Environments.

Changes in a certain parameter are often a few magnitudes smaller than the base value of the parameter, specifying significant requirements for the dynamic range and noise levels of the measurement system. In case of electrical bioimpedance acquisition, the variations can be 1000 times smaller than the entire measured value. Synchronous or lock-in measurement of these variations is discussed in the current paper, and novel measurement solutions are presented. Proposed methods are simple and robust when compared to other applicable solutions. A common feature shared by all members of the group of the proposed solutions is differentiation. It is achieved by calculating the differences between synchronously acquired consecutive samples, with lock-in integration and analog differentiation. All these methods enable inherent separation of variations from the static component of the signal. The variable component of the bioimpedance can, thus, be acquired using the full available dynamic range of the apparatus for its detection. Additive disturbing signals and omnipresent wideband noise are considered and the method for their reduction is proposed.

Adaptive LINE-P: An Adaptive Linear Energy Prediction Model for Wireless Sensor Network Nodes.

In the context of wireless sensor networks, energy prediction models are increasingly useful tools that can facilitate the power management of the wireless sensor network (WSN) nodes. However, most of the existing models suffer from the so-called fixed weighting parameter, which limits their applicability when it comes to, e.g., solar energy harvesters with varying characteristics. Thus, in this article we propose the Adaptive LINE-P (all cases) model that calculates adaptive weighting parameters based on the stored energy profiles. Furthermore, we also present a profile compression method to reduce the memory requirements. To determine the performance of our proposed model, we have used real data for the solar and wind energy profiles. The simulation results show that our model achieves 90-94% accuracy and that the compressed method reduces memory overheads by 50% as compared to state-of-the-art models.

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.

Crest factor optimization of the multisine waveform for bioimpedance spectroscopy.

The multisine excitation is widely used in impedance measurements to retain the advantages of the sine wave, while reducing the measurement time. Adding up sine waves increases the amplitude of the excitation signal, but, for the linearity assumption to be valid, the overall amplitude of the signal needs to be kept low. Thus, the crest factor (CF) of the excitation signal must be minimized. A novel empirical method for the minimization of the CF is described in this paper. As in the case of other known methods, the computed CF may be guaranteed to be only a local minimum. However, a systematic variation of initial parameters, which is possible due to the sparing algorithm, ensures a CF value very close or equal to the global minimum. The results of CF minimization and comparison with the results from other sources are provided. The direct CF optimization results (set of optimal phases) are not well suited for practical implementation. The influence of phase accuracy on the CF is discussed, and an algorithm for the recalculation of initial phases to the rougher set is described. It is shown that previously obtained optimization results (minimal CF) can be highly preserved, even in the case of rough phase resolutions. The CF of the multisine also depends on the frequency distribution and amplitudes of its components. The CF of multisines with several frequency distributions are compared.

Wearable system for non-invasive and continuous monitoring central aortic pressure curve and augmentation index.

The paper presents a non-invasive method and system for a long-term and continuous monitoring of the central aortic pressure (CAP) waveform and the augmentation index (AI). The CAP curve is estimated from the measured radial electrical bio-impedance (EBI) using spectral domain transfer functions (TF), which are established on the basis of data analysis during clinical experiments. Experiments were carried out on 3 volunteers by now. During the experiment, a 0.5 mg sublingual nitroglycerin tablet was administrated to each volunteer. Both, the reconstructed CAP curve and the AI have very good correlation with the results obtained by the SphygmoCor system. But, in opposite to the traditional tonometry based CAP curve and AI estimation methods, the proposed one is more convenient to use and allows continuous and long-term personalized monitoring of the CAP curve and of the AI.

Wearable data acquisition system of multimodal physiological signals for personal health care.

The paper proposes a wearable multimodal data acquisition system for biological signals. The system enables logging of electrical bioimpedance signals from multiple electrodes, electrocardiographic signals (ECG), acceleration signals from multiple locations, and spirometric data from a moving object. Later it will be used to conduct field measurements for characterizing health of the object under investigation. Main goal is to acquire enough data for development, refinement, and simplification of signal processing algorithms. The system is center part of the new wearable compact data acquisition modules ZCardio. Those modules enable multichannel impedance spectroscopy by logging ECG signals and data from the spirometric sensor. Initial reference measurements were conducted. Alternatively, tests were performed using Plessey Semiconductors capacitive sensors. Acceleration signals are gathered.

Binary signals in impedance spectroscopy.

Using of binary waveforms in the fast impedance spectroscopy of biological objects is discussed in the paper. There is shown that the energy of binary waveforms can be concentrated onto selected separate frequencies. We can optimize the binary excitation waveform depending on the shape of frequency response of the impedance under study to maximize the levels of signal components with certain selected frequencies. As a result, we are able to receive maximal amount of information about the properties and behavior of the impedance to be studied. We have designed and prototyped the impedance spectroscopy device operating in the frequency range from 100 mHz to 500 kHz to cover α- and ß-regions of the bio-impedance spectrum of time-varying subjects as, for example, fast moving cells in micro-fluidic devices, beating heart and breathing lungs or the whole cardiovascular system.

Improvements in design of spectra of multisine and binary excitation signals for multi-frequency bioimpedance measurement.

The paper discusses the usability of multi-frequency binary waveforms for broadband excitation in fast measurements of impedance spectrum of biological objects. It is shown that up to 70% of the energy of the amplitude spectrum of such two-level binary signals can be concentrated into the selected separate frequencies. The levels of selected frequency components are controllable in tens and hundreds of times. In this way we can underline the most important frequencies enhancing the corresponding amplitudes in the spectrum of excitation signal. As an implementation example, we consider the impedance spectroscopy in micro-fluidic devices for inline measurement of the conductivity of droplets in segmented flow. We use a thin-walled glass capillary with electrodes contacting the outer surface so that the contactless measurement of conductivity of liquid with biologic cells becomes possible.