Analog processing of signals from a CZT strip detector with orthogonal coplanar anodes

We present the requirements, design, and performance of an analog circuit for processing the non-collecting anode strip signals from a cadmium zinc telluride (CZT) strip detector with orthogonal coplanar anodes. Detector signal simulations and measurements with a prototype are used to define the range of signal characteristics as a function of location of the gamma interaction in the detector. The signals from the non- collecting anode strip electrodes are used to define two of the three spatial coordinates including the depth of interaction, the z dimension. Analog signal processing options are discussed. A circuit to process the signals from the non- collecting anode strips and extract from them the depth of interaction is described. The circuit employs a time-over- threshold (TOT) measurement. The performance of the detector prototype with a preliminary version of this circuit is presented, and future development work is outlined

Computer Aided ECG Analysis - State of the Art and Upcoming Challenges

In this paper we present current achievements in computer aided ECG analysis and their applicability in real world medical diagnosis process. Most of the current work is covering problems of removing noise, detecting heartbeats and rhythm-based analysis. There are some advancements in particular ECG segments detection and beat classifications but with limited evaluations and without clinical approvals. This paper presents state of the art advancements in those areas till present day. Besides this short computer science and signal processing literature review, paper covers future challenges regarding the ECG signal morphology analysis deriving from the medical literature review. Paper is concluded with identified gaps in current advancements and testing, upcoming challenges for future research and a bullseye test is suggested for morphology analysis evaluation.Comment: 7 pages, 3 figures, IEEE EUROCON 2013 International conference on computer as a tool, 1-4 July 2013, Zagreb, Croati

MIMO signal processing in offset-QAM based filter bank multicarrier systems

Next-generation communication systems have to comply with very strict requirements for increased flexibility in heterogeneous environments, high spectral efficiency, and agility of carrier aggregation. This fact motivates research in advanced multicarrier modulation (MCM) schemes, such as filter bank-based multicarrier (FBMC) modulation. This paper focuses on the offset quadrature amplitude modulation (OQAM)-based FBMC variant, known as FBMC/OQAM, which presents outstanding spectral efficiency and confinement in a number of channels and applications. Its special nature, however, generates a number of new signal processing challenges that are not present in other MCM schemes, notably, in orthogonal-frequency-division multiplexing (OFDM). In multiple-input multiple-output (MIMO) architectures, which are expected to play a primary role in future communication systems, these challenges are intensified, creating new interesting research problems and calling for new ideas and methods that are adapted to the particularities of the MIMO-FBMC/OQAM system. The goal of this paper is to focus on these signal processing problems and provide a concise yet comprehensive overview of the recent advances in this area. Open problems and associated directions for future research are also discussed.Peer ReviewedPostprint (author's final draft

Continuous glucose monitoring sensors: Past, present and future algorithmic challenges

Continuous glucose monitoring (CGM) sensors are portable devices that allow measuring and visualizing the glucose concentration in real time almost continuously for several days and are provided with hypo/hyperglycemic alerts and glucose trend information. CGM sensors have revolutionized Type 1 diabetes (T1D) management, improving glucose control when used adjunctively to self-monitoring blood glucose systems. Furthermore, CGM devices have stimulated the development of applications that were impossible to create without a continuous-time glucose signal, e.g., real-time predictive alerts of hypo/hyperglycemic episodes based on the prediction of future glucose concentration, automatic basal insulin attenuation methods for hypoglycemia prevention, and the artificial pancreas. However, CGM sensors’ lack of accuracy and reliability limited their usability in the clinical practice, calling upon the academic community for the development of suitable signal processing methods to improve CGM performance. The aim of this paper is to review the past and present algorithmic challenges of CGM sensors, to show how they have been tackled by our research group, and to identify the possible future ones

Generalized multivariate analysis of variance - A unified framework for signal processing in correlated noise

Generalized multivariate analysis of variance (GMANOVA) and related reduced-rank regression are general statistical models that comprise versions of regression, canonical correlation, and profile analyses as well as analysis of variance (ANOVA) and covariance in univariate and multivariate settings. It is a powerful and, yet, not very well-known tool. We develop a unified framework for explaining, analyzing, and extending signal processing methods based on GMANOVA. We show the applicability of this framework to a number of detection and estimation problems in signal processing and communications and provide new and simple ways to derive numerous existing algorithms. Many of the methods were originally derived from scratch , without knowledge of their close relationship with the GMANOVA model. We explicitly show this relationship and present new insights and guidelines for generalizing these methods. Our results could inspire applications of the general framework of GMANOVA to new problems in signal processing. We present such an application to flaw detection in nondestructive evaluation (NDE) of materials. A promising area for future growth is image processing

Wireless Communications in the Era of Big Data

The rapidly growing wave of wireless data service is pushing against the boundary of our communication network's processing power. The pervasive and exponentially increasing data traffic present imminent challenges to all the aspects of the wireless system design, such as spectrum efficiency, computing capabilities and fronthaul/backhaul link capacity. In this article, we discuss the challenges and opportunities in the design of scalable wireless systems to embrace such a "bigdata" era. On one hand, we review the state-of-the-art networking architectures and signal processing techniques adaptable for managing the bigdata traffic in wireless networks. On the other hand, instead of viewing mobile bigdata as a unwanted burden, we introduce methods to capitalize from the vast data traffic, for building a bigdata-aware wireless network with better wireless service quality and new mobile applications. We highlight several promising future research directions for wireless communications in the mobile bigdata era.Comment: This article is accepted and to appear in IEEE Communications Magazin

Realtime processing of LOFAR data for the detection of nano-second pulses from the Moon

The low flux of the ultra-high energy cosmic rays (UHECR) at the highest energies provides a challenge to answer the long standing question about their origin and nature. Even lower fluxes of neutrinos with energies above $10^{22}$ eV are predicted in certain Grand-Unifying-Theories (GUTs) and e.g.\ models for super-heavy dark matter (SHDM). The significant increase in detector volume required to detect these particles can be achieved by searching for the nano-second radio pulses that are emitted when a particle interacts in Earth's moon with current and future radio telescopes. In this contribution we present the design of an online analysis and trigger pipeline for the detection of nano-second pulses with the LOFAR radio telescope. The most important steps of the processing pipeline are digital focusing of the antennas towards the Moon, correction of the signal for ionospheric dispersion, and synthesis of the time-domain signal from the polyphased-filtered signal in frequency domain. The implementation of the pipeline on a GPU/CPU cluster will be discussed together with the computing performance of the prototype.Comment: Proceedings of the 22nd International Conference on Computing in High Energy and Nuclear Physics (CHEP2016), US