FPGA design methodology for industrial control systems—a review

This paper reviews the state of the art of fieldprogrammable gate array (FPGA) design methodologies with a focus on industrial control system applications. This paper starts with an overview of FPGA technology development, followed by a presentation of design methodologies, development tools and relevant CAD environments, including the use of portable hardware description languages and system level programming/design tools. They enable a holistic functional approach with the major advantage of setting up a unique modeling and evaluation environment for complete industrial electronics systems. Three main design rules are then presented. These are algorithm refinement, modularity, and systematic search for the best compromise between the control performance and the architectural constraints. An overview of contributions and limits of FPGAs is also given, followed by a short survey of FPGA-based intelligent controllers for modern industrial systems. Finally, two complete and timely case studies are presented to illustrate the benefits of an FPGA implementation when using the proposed system modeling and design methodology. These consist of the direct torque control for induction motor drives and the control of a diesel-driven synchronous stand-alone generator with the help of fuzzy logic

Noninvasive methods for children\u27s cholesterol level determination

Today, there is a controversy about the role of cholesterol in infants and the measurement and management of blood cholesterol in children. Several scientific evidences are supporting relationship between elevated blood cholesterol in children and high cholesterol in adults and development of adult arteriosclerotic diseases such as cardiovascular and cerebrovascular disease. Therefore controlling the level of blood cholesterol in children is very important for the health of the whole population. Non-invasive methods are much more convenient for the children because of their anxieties about blood examinations. In this paper we will present a new try to find non-invasive methods for determining the level of blood cholesterol in children with the use of intelligent system

Surface EMG decomposition using a novel approach for blind source separation

We introduce a new method to perform a blind deconvolution of the surface electromyogram (EMG) signals generated by isometric muscle contractions. The method extracts the information from the raw EMG signals detected only on the skin surface, enabling longtime noninvasive monitoring of the electromuscular properties. Its preliminary results show that surface EMG signals can be used to determine the number of active motor units, the motor unit firing rate and the shape of the average action potential in each motor unit

Measurements, Models, Systems and Design

531 s.

Research in Metabolomics via Nuclear Magnetic Resonance Spectroscopy: Data Mining, Biochemistry and Clinical Chemistry

Metabolomics entails the comprehensive characterization of the ensemble of endogenous and exogenous metabolites present in a biological specimen. Metabolites represent, at the same time, the downstream output of the genome and the upstream input from various external factors, such as the environment, lifestyle, and diet. Therefore, in the last few years, metabolomic phenotyping has provided unique insights into the fundamental and molecular causes of several physiological and pathophysiological conditions. In parallel, metabolomics has been demonstrating an emerging role in monitoring the influence of different manufacturing procedures on food quality and food safety. In light of the above, this collection includes the latest research from various fields of NMR-based metabolomics applications ranging from biomedicine to data mining and food chemistry

A Neural Signal Processor for Low-Latency Spike Inference

This thesis describes the development of a system that can assign identities to a population of single-units, in multi-electrode recordings, at single-spike resolution with low-latency. The system has two parts. The first is a Field-Programmable Gate Array (FPGA)-based Neural Signal Processor (NSP) that receives raw input and generates labelled spikes as output, a process referred to as real-time spike inference. The second is a piece of software (Spiketag) that runs on a PC, communicates with the NSP, and generates a spike-sorted model to guide the real-time spike inference. The NSP provides clocks and control signals to five 32-channel INTAN RHD2132 chips to manage the acquisition of 160 channels of raw neural data. In parallel, the NSP further filters, detects and extracts extracellular spike waveforms from the raw neural data recorded by tetrodes or silicon probes and assigns single-unit identity to each detected spike. A set of Python application programming interfaces (APIs) was developed in Spiketag to enable the communication between the NSP and the PC. These APIs allow the NSP to obtain a model from the PC, which holds parameters such as reference channels, spike detection thresholds, spike feature transformation matrix and vector quantized clusters generated by spike sorting a short recording session. Using the spike-sorted model, the NSP performs data acquisition and real-time spike inference simultaneously. Algorithmic modules were implemented in the FPGA and pipelined to compute during 40 ms acquisition intervals. At the output end of the FPGA NSP, the real-time assigned single-unit identity (spike-id) is packaged with the timestamp, the electrode group, and the spike features as a spike-id packet. Spike-id packets are asynchronously transmitted through a low-latency Peripheral Component Interconnect Express (PCIe) interface to the PC, producing the real-time spike trains. The real-time spike trains can be used for further processing, such as real-time decoding. Several types of ground-truth data, including intracellular/extracellular paired recordings, synthesized tetrode extracellular waveforms with ground-truth spike timing and high-channel-count silicon probe recordings with ground-truth animal positions during navigation were used to validate the low-latency (1 ms) and high-accuracy (as high as state-of-the-art offline sorting and decoding algorithms) of the NSP’s real-time spike inference and the NSP-based real-time population decoding performance

GPS analysis of a team competing at a national Under 18 field hockey tournament

The purpose of this study was to utilise global-positioning system (GPS) technology to quantify the running demands of national Under 18 field hockey players competing in a regional field hockey tournament. Ten male players (mean ± SD; age 17.2 ± 0.4 years; stature 178.1 ± 5.2 cm; body mass 78.8 ± 8.8 kg) wore GPS units while competing in six matches over seven days at the 2018 New Zealand national under 18 field hockey tournament. GPS enabled the measurement of total distance (TD), low-speed activity (LSA; 0 -14.9 km/hr), and high-speed running (HSR; ≥ 15 km/hr) distances. Differences in running demands (TD, LSA, HSR) between positions were assessed using effect size and percent difference ± 90% confidence intervals. Midfielders covered the most TD and LSA per game and strikers the most HSR during the 6 matches. There were “very large” differences between strikers and midfielders for TD and LSA, strikers and defenders for LSA and HSR, and defenders and midfielders for LSA. These results suggest that these playing positions are sufficiently different to warrant specialised position-specific conditioning training leading into a field hockey tournament

The effects of morning preconditioning protocols on testosterone, cortisol and afternoon sprint cycling performance [conference presentation]

Opportunities exist for athletes to undertake morning exercise protocols in an attempt to potentate afternoon performance. Four sub elite track sprint cyclists completed a morning cycling (Cyc) or weights-based protocol (WP) prior to an afternoon cycling time trial (500m) in a repeated measures, counterbalance crossover design. Measured variables included heart rate, blood lactate, cycling peak power, salivary testosterone (T) and cortisol levels along with time trial performance. Standardised differences in means via magnitude-based inferences were calculated using paired samples T-tests in SPSS version 24 with statistical significance set at p < 0.05. The WP produced significantly faster times in the final 250m in comparison to CycP. The anticipated circadian decline of T was observed after the CycP but was however mitigated following the WP. While slight decreases in 500m times were experienced during the WP, they were not significant and were considered within the normal variations experienced between performances by elite athletes. The effect of the WP on the circadian rhythm of T could be linked to a greater recruitment of muscle fibres. Results suggest a morning resistance protocol can positively affect testosterone levels for afternoon performance. Possible gender and individual responses from conducting a W over Cyc protocol were observed and require further investigation