Abstract

Information Theory (IT) originated in the realm of telecommunications, focusing on channel optimization and encoding. In recent decades, IT has been applied to understanding fundamental concepts in various other fields such as cognitive neuroscience, biology, and dimensionality reduction in machine learning. This short video will present how IT can help us understand fundamental aspects of measurement, such as resolution and signal chain optimization. I will also demonstrate how some results can lead to practical applications, such as the optimal choice of quantization resolution in A/D conversion for a noisy interface. The goal is for this framework to simplify design challenges in more complex contexts.

Keywords: Information theory; Theory of measurement; Analog-to-digital conversion; Signal chain optimization; Sensor design

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Abstract

Autonomous systems are nowadays having an undisputed pervasiveness in the modern society. Autonomous driving cars as well as applications of service robots (e.g. cleaning robots, companion robots, intelligent healthcare solutions, tour guided systems) are becoming more and more popular and a general acceptance is now developing around such systems in the modern societies. Nonetheless, one of the major problems in building such applications relies on the capability of autonomous systems to understand their surroundings and then plan proper counteractions. The most popular solutions, which are gaining more and more attention, rely on artificial intelligence and deep learning as a means to understand the structured and complex natural environment.  Nonetheless, besides the importance of such complex tools, classical concept of metrology, such as uncertainty and precision, are still unavoidable to a clear and effective application of modern autonomous systems applications.

In this tutorial, some measurement concepts will be revised in light of the autonomous systems domain. In particular, we will cover the main concepts of the statistical approach to measurements that will then be applied to:

• Uncertainty analysis and synthesis for autonomous systems localisation
• Precision-based feedback for social robotics

Keywords: electrical, capacitance, tomography, ieee, ims, wuqiang yang, tutorials, education, applications

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Abstract

Medicine 4.0 is definitely a great revolution in patient care. New horizons are possible today. Relocation of services, which means remote monitoring, and remote diagnoses without direct contact between the doctor and the patient. Hospitals are freed from routine tests that could be performed by patients at home and reported by doctors on the internet. Telemedicine is not a WhatsApp where an elder tries to chat with a doctor. Telemedicine is a complete remote medical center connected to smart devices able to measure objective vital parameters. Medicine 4.0 requires new technologies for smart sensors, but also Artificial Intelligence is required to perform smart analysis using these smart sensors. A.I. is used both to manage intensive care rooms and to perform better and faster analyses. In this webinar, we’ll see how to use Machine learning techniques to improve ECG analyses and leg ulcer treatment.    

Keywords: Telemedicine, Artificial Intelligence, Artificial Neural Networks, Electronic Health, Smart Sensors

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Abstract

The video is addressing the general topic of measurements in emerging power systems. Firstly, disruptive changes in electric power systems are analyzed in order to understand the impact on the requirements for control and instrumentation in smart grids; then  modern measurement chains are presented together with their potential use in coping with limited knowledge on the grid infrastructure, new power quality issues generated by distributed generation or wide area measurement and control in low inertial systems. Ways of merging the information delivered by existing (SCADA, intelligent electronic devices ) and emerging (Phasor measurement units -PMUs and microPMUs) measurement systems are presented, as part of applications like the power system state estimation; The tutorial highlights the importance of assessment the measurement channel quality together with the silently adopted models for energy transfer, and issues like voltage and frequency variability; rate of change of frequency; the steady-state signal and rapid voltage changes; measurement data aggregation; filtering properties; time- aggregation algorithms in the PQ framework. The presentation ends with new applications enabled by smart metering with high reporting rate (1s) and highlights some of the challenges for measurement systems in smart grids.

Keywords: smart grids; active distribution grids; smart metering; high reporting rate measurements; unbundled smart meter

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Abstract

Heartrate monitors are becoming ubiquitous and are being used by both athletes and the general public to keep track of their health. Heartrate monitors are just an example of the wearables currently available to the public; other examples include oxygen saturation monitors, activity monitors, and muscle activity monitors. Wearables are typically not used in a controlled environment; therefore, the quality of the collected signals might be questionable. Even in a controlled environment such as a hospital, deterioration in the quality of the collected signals can lead to false alarm and reduction in the quality of patient care. As the signals are used to inform users about their health, it is imperative that the signals are of acceptable quality. Signal Quality is the field of identifying and improving the quality of collected signals. Signal Quality can be divided into four categories: 1) detection; 2) identification; 3) quantification; and 4) mitigation. Detection is the acknowledgement of the presence of noise in the signal. Identification is the determination of the type of noise. Quantification is the estimation of the level of the noise. Mitigation is the reduction of the noise through noise removal techniques. This tutorial will provide a high-level overview of the different techniques in each of the Signal Quality categories.

Keywords: wearables, hospital, mohamed abdelazez, ieee, ims, signal quality, tutorials, education

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Abstract

The increasing need for wearable systems capable of assessing cardiorespiratory functions across diverse domains, including clinical settings and sports science, is driven by the critical importance of cardiac and respiratory parameters in detecting various health conditions and stressors. However, achieving noninvasive data collection while ensuring comfort and accuracy remains a considerable challenge. Recent advances in flexible systems and materials offer promise in addressing these challenges by introducing a new generation of wearable devices that are both more effective and comfortable.

This tutorial provides an overview of next-generation wearables tailored for monitoring cardiac and respiratory activity, particularly focusing on those based on strain sensing. It then outlines the essential steps for developing flexible wearable strain sensors capable of detecting respiratory rate and heart rate through chest wall deformation.

These steps include:

1. The use of a finite element analysis to optimize the structural design of the sensor to enhance its performance in strain sensing.
2. A description of the main fabrication phases necessary for developing the modeled flexible sensor.
3. A description of experimental setups and protocols required to characterize the metrological properties of the fabricated sensor.
4. An exploration of the key data analysis techniques used to estimate cardiorespiratory parameters from the raw signal recorded by the developed flexible wearable sensor.

Keywords

Wearables; cardiorespiratory monitoring; design optimization; data analysis techniques; hear rate monitoring; respiratory rate monitoring.

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Abstract

Near infrared spectroscopy (NIRS) is an optical technique that allows investigating tissue hemodynamics in-vivo and non-invasively by measuring optical absorption Near infrared spectroscopy (NIRS) is an optical technique that allows investigating tissue hemodynamics in-vivo and non-invasively by measuring optical absorption properties of oxy- and deoxy-hemoglobin using near infrared light (650-1000 nm). Since its introduction more than forty years ago, NIRS has seen a tremendous research growth due to its unique combination of performance, portability and reduced cost in comparison to other imaging techniques such as functional magnetic resonance imaging (fMRI) or positron emission tomography (PET). Importantly, NIRS has also been adopted in the clinical setting as a reliable technique for monitoring cerebral oxygenation in critical care, and many other scientific and clinical applications are rapidly developing. This tutorial introduces the basic principles of NIRS and briefly describes some of the most relevant applications in the field. 

Keywords: 

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