Small UAS Online Audio DOA Estimation and Real-Time Identification Using Machine Learning.

The wide range of unmanned aerial system (UAS) applications has led to a substantial increase in their numbers, giving rise to a whole new area of systems aiming at detecting and/or mitigating their potentially unauthorized activities. The majority of these proposed solutions for countering the aforementioned actions (C-UAS) include radar/RF/EO/IR/acoustic sensors, usually working in coordination. This work introduces a small UAS (sUAS) acoustic detection system based on an array of microphones, easily deployable and with moderate cost. It continuously collects audio data and enables (a) the direction of arrival (DOA) estimation of the most prominent incoming acoustic signal by implementing a straightforward algorithmic process similar to triangulation and (b) identification, i.e., confirmation that the incoming acoustic signal actually emanates from a UAS, by exploiting sound spectrograms using machine-learning (ML) techniques. Extensive outdoor experimental sessions have validated this system's efficacy for reliable UAS detection at distances exceeding 70 m.

Nanopower Integrated Gaussian Mixture Model Classifier for Epileptic Seizure Prediction.

This paper presents a new analog front-end classification system that serves as a wake-up engine for digital back-ends, targeting embedded devices for epileptic seizure prediction. Predicting epileptic seizures is of major importance for the patient's quality of life as they can lead to paralyzation or even prove fatal. Existing solutions rely on power hungry embedded digital inference engines that typically consume several µW or even mW. To increase the embedded device's autonomy, a new approach is presented combining an analog feature extractor with an analog Gaussian mixture model-based binary classifier. The proposed classification system provides an initial, power-efficient prediction with high sensitivity to switch on the digital engine for the accurate evaluation. The classifier's circuit is chip-area efficient, operating with minimal power consumption (180 nW) at low supply voltage (0.6 V), allowing long-term continuous operation. Based on a real-world dataset, the proposed system achieves 100% sensitivity to guarantee that all seizures are predicted and good specificity (69%), resulting in significant power reduction of the digital engine and therefore the total system. The proposed classifier was designed and simulated in a TSMC 90 nm CMOS process, using the Cadence IC suite.

An Efficient Point-Matching Method-of-Moments for 2D and 3D Electrical Impedance Tomography Using Radial Basis Functions.

OBJECTIVE: The inverse problem of computing conductivity distributions in 2D and 3D objects interrogated by low-frequency electrical signals, which is called Electrical Impedance Tomography (EIT), is treated using a Method-of-Moment technique. METHODS: A Point-Matching-Method-of-Moment technique is used to formulate a global integral equation solver. Radial Basis Functions are adopted to express the conductivity distribution. Single-step quadratic-norm ( L2) and iterative total variation ( L1) regularization techniques are exploited to solve the inverse problem. RESULTS: Simulation and experimental tests on a circular reconstruction domain show satisfactory performance in deriving conductivity distribution, achieving a Correlation Coefficient ( CC) up to 0.863 for 70 dB voltage SNR and 0.842 for 40 dB voltage SNR. The proposed methodology with L2-norm regularization provided better results than traditional iterative Gauss-Newton's approach, whereas with L1-norm regularization it showed promising performance. Moreover, 3D reconstructions on a cylindrical cavity demonstrated superior results near the electrodes' planes compared to those of the conventional linearized approach. Finally, application to EIT medical data for dynamic lung imaging successfully revealed the breath-cycle conductivity changes. CONCLUSION: The results show that the proposed method can be effective for both 2D and 3D EIT and applicable to many applications. SIGNIFICANCE: Strong conductivity variations are successfully tackled with a very good Correlation Coefficient. In contrast to conventional EIT solutions based on weak-form and linearization on small conductivity changes, the proposed method requires only one step to converge with L2-norm regularization. The proposed method with L1-norm regularization also achieves good reconstruction quality with a low number of iterations.

A Point-Matching Method of Moment with Sparse Bayesian Learning Applied and Evaluated in Dynamic Lung Electrical Impedance Tomography.

Dynamic lung imaging is a major application of Electrical Impedance Tomography (EIT) due to EIT's exceptional temporal resolution, low cost and absence of radiation. EIT however lacks in spatial resolution and the image reconstruction is very sensitive to mismatches between the actual object's and the reconstruction domain's geometries, as well as to the signal noise. The non-linear nature of the reconstruction problem may also be a concern, since the lungs' significant conductivity changes due to inhalation and exhalation. In this paper, a recently introduced method of moment is combined with a sparse Bayesian learning approach to address the non-linearity issue, provide robustness to the reconstruction problem and reduce image artefacts. To evaluate the proposed methodology, we construct three CT-based time-variant 3D thoracic structures including the basic thoracic tissues and considering 5 different breath states from end-expiration to end-inspiration. The Graz consensus reconstruction algorithm for EIT (GREIT), the correlation coefficient (CC), the root mean square error (RMSE) and the full-reference (FR) metrics are applied for the image quality assessment. Qualitative and quantitative comparison with traditional and more advanced reconstruction techniques reveals that the proposed method shows improved performance in the majority of cases and metrics. Finally, the approach is applied to single-breath online in-vivo data to qualitatively verify its applicability.

Real-Time Passive Brain Monitoring System Using Near-Field Microwave Radiometry.

OBJECTIVE: Near-field microwave radiometry has emerged as a tool for real-time passive monitoring of local brain activation, possibly attributed to local changes in blood flow that correspond to temperature and/or conductivity changes. The aim of this study is to design and evaluate a prototype system based on microwave radiometry intended to detect local changes of temperature and conductivity in depth in brain tissues. A novel radiometric system that comprises a four port total power Dicke-switch sensitive receiver that operates at 1.5 GHz has been developed. METHODS AND RESULTS: The efficacy of the system was assessed through simulation and experiment on brain tissue mimicking phantoms under different setup conditions, where temperature and conductivity changes were accurately detected. In order to validate the radiometer's capability to sense low power signals occurring spontaneously from regions in the human brain, the somatosensory cortices of one volunteer were measured under pain-inducing psychophysiological conditions. The promising results from the initial in vivo measurements prove the system's potential for more extensive investigative trials. CONCLUSION AND SIGNIFICANCE: The significance of this study lies on the development of a compact and sensitive radiometer for totally passive monitoring of local brain activation as a potential complementary tool for contributing to the research effort for investigating brain functionality.

Publisher Correction to: Three-dimensional tumor growth in time-varying chemical fields: a modeling framework and theoretical study.

Following publication of the original article [1], the authors noticed that the following errors were introduced by pdf/html formatting issues.

Three-dimensional tumor growth in time-varying chemical fields: a modeling framework and theoretical study.

BACKGROUND: Contemporary biological observations have revealed a large variety of mechanisms acting during the expansion of a tumor. However, there are still many qualitative and quantitative aspects of the phenomenon that remain largely unknown. In this context, mathematical and computational modeling appears as an invaluable tool providing the means for conducting in silico experiments, which are cheaper and less tedious than real laboratory experiments. RESULTS: This paper aims at developing an extensible and computationally efficient framework for in silico modeling of tumor growth in a 3-dimensional, inhomogeneous and time-varying chemical environment. The resulting model consists of a set of mathematically derived and algorithmically defined operators, each one addressing the effects of a particular biological mechanism on the state of the system. These operators may be extended or re-adjusted, in case a different set of starting assumptions or a different simulation scenario needs to be considered. CONCLUSION: In silico modeling provides an alternative means for testing hypotheses and simulating scenarios for which exact biological knowledge remains elusive. However, finer tuning of pertinent methods presupposes qualitative and quantitative enrichment of available biological evidence. Validation in a strict sense would further require comprehensive, case-specific simulations and detailed comparisons with biomedical observations.

The effect of using a dielectric matching medium in focused microwave radiometry: an anatomically detailed head model study.

Microwave radiometry is a passive technique used to measure in-depth temperature distributions inside the human body, potentially useful in clinical applications. Experimental data imply that it may provide the capability of detecting in-depth local variations of temperature and/or conductivity of excitable tissues at microwave frequencies. Specifically, microwave radiometry may allow the real-time monitoring of brain temperature and/or conductivity changes, associated with local brain activation. In this paper, recent results of our ongoing research regarding the capabilities of focused microwave radiometry for brain intracranial applications are presented. Electromagnetic and thermal simulation analysis was performed using an anatomically detailed head model and a dielectric cap as matching medium placed around it, in order to improve the sensitivity and the focusing attributes of the system. The theoretical results were compared to experimental data elicited while exploring that the sensing depth and spatial resolution of the proposed imaging method at 2.1 GHz areas located 3 cm deep inside the brain can be measured, while at 2.5 GHz, the sensing area is confined specifically to the area of interest. The results exhibit the system's potential as a complementary brain imaging tool for multifrequency in-depth passive monitoring which could be clinically useful for therapeutic, diagnostic, and research applications.

Clinical implications of in silico mathematical modeling for glioblastoma: a critical review.

Glioblastoma remains a clinical challenge in spite of years of extensive research. Novel approaches are needed in order to integrate the existing knowledge. This is the potential role of mathematical oncology. This paper reviews mathematical models on glioblastoma from the clinical doctor's point of view, with focus on 3D modeling approaches of radiation response of in vivo glioblastomas based on contemporary imaging techniques. As these models aim to provide a clinically useful tool in the era of personalized medicine, the integration of the latest advances in molecular and imaging science and in clinical practice by the in silico models is crucial for their clinical relevance. Our aim is to indicate areas of GBM research that have not yet been addressed by in silico models and to point out evidence that has come up from in silico experiments, which may be worth considering in the clinic. This review examines how close these models have come in predicting the outcome of treatment protocols and in shaping the future of radiotherapy treatments.

Two 27 MHz Simple Inductive Loops, as Hyperthermia Treatment Applicators: Theoretical Analysis and Development.

BACKGROUND: Deep heating is still the main subject for research in hyperthermia treatment. AIM: The purpose of this study was to develop and analyze a simple loop as a heating applicator. METHODS: The performance of two 27 MHz inductive loop antennas as potential applicators in hyperthermia treatment was studied theoretically as well as experimentally in phantoms. Two inductive loop antennas with radii 7 cm and 9 cm were designed, simulated, and constructed. The theoretical analysis was performed by using Green's function and Bessel's function technique. Experiments were performed with phantoms radiated by the aforementioned loop antennas. RESULTS: The specific absorption rate (SAR) distributions were estimated from the respective local phantom temperature measurements. Comparisons of the theoretical, simulation, and experimental studies showed satisfying agreement. The penetration depth was measured theoretically and experimentally in the range of 2-3.5 cm. CONCLUSION: The theoretical and experimental analysis showed that current loops are efficient in the case where the peripheral heating of spherical tumor formation located at 2-3.5 cm depth is required.

Theoretical analysis, design and development of a 27-MHz folded loop antenna as a potential applicator in hyperthermia treatment.

PURPOSE: A hyperthermia system using a folded loop antenna applicator at 27 MHz for soft tissue treatment was investigated both theoretically and experimentally to evaluate its clinical value. MATERIALS AND METHODS: The electromagnetic analysis of a 27-MHz folded loop antenna for use in human tissue was based on a customised software tool and led to the design and development of the proposed hyperthermia system. The system was experimentally validated using specific absorption rate (SAR) distribution estimations through temperature distribution measurements of a muscle tissue phantom after electromagnetic exposure. Various scenarios for optimal antenna positioning were also performed. RESULTS: Comparison of the theoretical and experimental analysis results shows satisfactory agreement. The SAR level of 50% reaches 8 cm depth in the tissue phantom. Thus, based on the maximum observed SAR values that were of the order of 100 W/kg, the antenna specified is suitable for deep tumour heating. CONCLUSIONS: Theoretical and experimental SAR distribution results as derived from this study are in agreement. The proposed folded loop antenna seems appropriate for use in hyperthermia treatment, achieving proper planning and local treatment of deeply seated affected areas and lesions.

Analysis of Two Electrocution Accidents in Greece that Occurred due to Unexpected Re-energization of Power Lines.

Investigation and analysis of accidents are critical elements of safety management. The over-riding purpose of an organization in carrying out an accident investigation is to prevent similar accidents, as well as seek a general improvement in the management of health and safety. Hundreds of workers have suffered injuries while installing, maintaining, or servicing machinery and equipment due to sudden re-energization of power lines. This study presents and analyzes two electrical accidents (1 fatal injury and 1 serious injury) that occurred because the power supply was reconnected inadvertently or by mistake.

Motive related positivity: decision-making during a prisoners' dilemma task.

The neural mechanisms underlying decision-making to cooperate or defect were investigated using event-related potentials during an iterated computer Prisoner's Dilemma task, adapted to induce working memory operation. Event-related potentials from 64 leads of 22 participants were recorded during 90 trials and averaged depending on the condition of cooperation and defect. The P200 component of the event-related potentials provided evidence for activation differences between cooperation and defect. Cooperation elicited significantly increased P200 activation at parieto-occipital leads, while defect activated primarily the prefrontal electrodes. Functional mapping using Low Resolution Electromagnetic Tomography indicated that in the 150-180 ms time window Brodmann areas 19 (precuneus) and 17 (lingual gyrus), exhibited increased activation during cooperation, while Brodmann area 6 (precentral gyrus) exhibited increased activation when participants defected. In conclusion, the current study provides evidence that cooperation and defect elicit different brain activation at specific loci and within specific time windows.

Temporal processing dysfunction in schizophrenia as measured by time interval discrimination and tempo reproduction tasks.

OBJECTIVE: Time perception deficiency has been implicated in schizophrenia; however the exact nature of this remains unclear. The present study was designed with the aim to delineate timing deficits in schizophrenia by examining performance of patients with schizophrenia and healthy volunteers in an interval discrimination test and their accuracy and precision in a pacing reproduction­replication test. METHODS: The first task involved temporal discrimination of intervals, in which participants (60 patients with schizophrenia and 35 healthy controls) had to judge whether intervals were longer, shorter or equal than a standard interval. The second task required repetitive self-paced tapping to test accuracy and precision in the reproduction and replication of tempos. RESULTS: Patients were found to differ significantly from the controls in the psychoticism scale of EPQ, the proportion of correct responses in the interval discrimination test and the overall accuracy and precision in the reproduction and replication of sound sequences (p < 0.01). Within the patient group bad responders concerning the ability to discriminate time intervals were associated with increased scores in the Positive and Negative Syndrome Scale (PANSS) and in the Brief Psychiatric Rating Scale (BPRS) in comparison to good responders (p < 0.01). There were no gender effects and there were no differences between subgroups of patients taking different kinds or combinations of drugs. CONCLUSIONS: Analysis has shown that performance on timing tasks decreased with increasing psychopathology and therefore that timing dysfunctions are directly linked to the severity of the illness. Different temporal dysfunctions can be traced to different psychophysiological origins that can be explained using the Scalar Expectancy Theory (SET).

Experimental study of a hybrid microwave radiometry-hyperthermia apparatus with the use of an anatomical head phantom.

This paper presents the latest progress made concerning a hybrid diagnostic and therapeutic system able to provide focused microwave radiometric temperature and/or conductivity variation measurements and hyperthermia treatment. Previous experimental studies of our group have demonstrated the system performance and focusing properties in phantom as well as human experiments. The system is able to detect temperature and conductivity variations with frequency-dependent detection depth and spatial sensitivity. Numerous studies have also demonstrated the improvement of the system focusing properties attributed to the use of dielectric and left handed matching layers. In this study, similar experimental procedures are performed but this time using an anatomical head model as phantom aiming to achieve a more accurate modeling of the system's future real function. This way, another step is made toward the deeper understanding of the system's capabilities, with the view to further use it in experimental procedures with laboratory animals and human volunteers.

Effect of frequency deviance direction on performance and mismatch negativity.

The mismatch negativity (MMN) component of the auditory event-related potential is associated with automatic perceptual inference concerning changes in auditory stimulation. Recent studies have addressed the question whether performance and MMN is affected by the direction of frequency deviance. In the present study, the frequency MMN and performance is investigated during an auditory identification task. Specifically, we examined the effect of positive and negative differences between the present stimulus and the previous response frequencies on performance as well as on the characteristics of stimulus-locked ERPs and brain activation maps. The results show that frequency deviants creating mismatch conditions increase the likelihood of error commission. The decrease in performance achieves statistical significance in the case of positive frequency deviants. In the latter case, ERP amplitude values of the Fz electrode at 164 ms after stimulus onset are statistically larger for mismatch as opposed to no-mismatch condition. This corresponds to significance differences in the activation maps at Brodmann area 11, superior frontal gyrus, and the frontal lobe. The present findings revealed dissociations in behavioral and ERP responses in the processing of positive and negative frequency deviance, lending support to the notion that MMN is more sensitive to increments than to decrements in frequency.

Passive monitoring using a combination of focused and phased array radiometry: a simulation study.

Aim of this simulation study is to use the focusing properties of a conductive ellipsoidal reflector in conjunction with directive phased microwave antenna configurations in order to achieve brain passive monitoring with microwave radiometry. One of the main modules of the proposed setup which ensures the necessary beamforming and focusing on the body and brain areas of interest is a symmetrical axis ellipsoidal conductive wall cavity. The proposed system operates in an entirely non-invasive contactless manner providing temperature and/or conductivity variations monitoring and is designed to also provide hyperthermia treatment. In the present paper, the effect of the use of patch antennas as receiving antennas on the system's focusing properties and specifically the use of phased array setups to achieve scanning of the areas under measurement is investigated. Extensive simulations to compute the electric field distributions inside the whole ellipsoidal reflector and inside two types of human head models were carried out using single and two element microstrip patch antennas. The results show that clear focusing (creation of "hot spots") inside the head models is achieved at 1.53GHz. In the case of the two element antennas, the "hot spot" performs a linear scan around the brain area of interest while the phase difference of the two microstrip patch antennas significantly affects the way the scanning inside the head model is achieved. In the near future, phased array antennas with multiband and more elements will be used in order to enhance the system scanning properties toward the acquisition of tomography images without the need of subject movement.

Noninvasive focused monitoring and irradiation of head tissue phantoms at microwave frequencies.

In this study, new aspects of our research regarding a novel hybrid system able to provide focused microwave radiometric temperature and/or conductivity measurements and hyperthermia treatment via microwave irradiation are presented. On one hand, it is examined whether the system is capable of sensing real-time progressive local variations of temperature and/or conductivity in customized phantom setups; on the other hand, the focusing attributes of the system are explored for different positions and types of phantoms used for hyperthermia in conjunction with dielectric matching layers surrounding the areas of interest. The main module of the system is an ellipsoidal cavity, which provides the appropriate focusing of the electromagnetic energy on the area of interest. The system has been used for the past few years in experiments with different configuration setups including phantom, animal, and human volunteer measurements yielding promising outcome. The present results show that the system is able to detect local concentrated gradual temperature and conductivity variations expressed as an increase of the output radiometric voltage. Moreover, when contactless focused hyperthermia is performed, the results show significant temperature increase at specific phantom areas. In this case, the effect of the dielectric matching layers placed around the phantoms is critical, thus resulting in the enhancement of the energy penetration depth.

Contactless passive diagnosis for brain intracranial applications: A study using dielectric matching materials.

A prototype system for passive intracranial monitoring using microwave radiometry is proposed. It comprises an ellipsoidal conductive wall cavity to achieve beamforming and focusing, in conjunction with sensitive multiband receivers for detection. The system has already shown the capability to provide temperature and/or conductivity variations in phantoms and biological tissue. In this article, a variant of the initially constructed modality is theoretically and experimentally investigated. Specifically, dielectric matching materials are used in an effort to improve the system's focusing attributes. The theoretical study investigates the effect of dielectric matching materials on the system's detection depth, whereas measurements with phantoms focus on the investigation of the system's detection level and spatial resolution. The combined results suggest that the dielectric matching layers lead to the improvement of the system's detection depth and temperature detection level. Also, the system's spatial resolution is explored at various experimental setups. Theoretical and experimental results conclude that with the appropriate combination of operation frequencies and dielectric layers, it is possible to monitor areas of interest inside human head models with a variety of detection depths and spatial resolutions.

Mismatch task conditions and error related ERPs.

BACKGROUND: The N200 component of event related potentials (ERPs) is considered an index of monitoring error related responses. The aim of the present work was to study the effect of mismatch conditions on the subjects' responses in an auditory identification task and their relation to the N200 of stimulus-locked ERPs. METHODS: An auditory identification task required to correctly map a horizontal slider onto an active frequency range by selecting a slider position that matched the stimulus tone in each trial. Fourteen healthy volunteers participated in the study and ERPs were recorded by 32 leads. RESULTS: Results showed that the subjects' erroneous responses were equally distributed within trials, but were dependent on mismatch conditions, generated by large differences between the frequencies of the tones of consecutive trials. Erroneous trials showed a significantly greater negativity within the time window of 164-191 ms after stimulus, located mainly at the Cz and Fz electrodes. The LORETA solution showed that maximum activations, as well as maximum differences, were localized mainly at the frontal lobe. CONCLUSIONS: These findings suggest that the fronto-central N200 component, conceived an index of "reorientation of attention", represents a correlate of an error signal, being produced when representation of the actual response and the required response are compared. Furthermore the magnitude of the amplitude of the N200 rests on the relation between the present and the previous stimulus.