Tutorial Speakers

Flexible hybrid electronics (FHE) combine flexible sensors and devices with rigid silicon integrated circuits (ICs) in order to produce flexible, light-weight electronic systems. The primary goal is to take the benefits of both technologies and synergistically combine them for a specific purpose. Flexible sensors offer many advantages in terms of conformability within wearable applications, but rigid silicon ICs offer highly efficient data processing and communication. While the benefits are evident, there are many challenges that are currently being addressed through research. 

NILM, or Non-Intrusive Load Monitoring, is a technique used in energy management to disaggregate total energy consumption into individual appliances' usage without requiring additional sensors. It relies on analyzing patterns in energy consumption data to identify and track the energy usage of specific devices within a household or building. Several methods have been proposed, and the state-of-the-art is solidly based on deep learning methods. 

To enable artificial intelligence for time-critical and remote applications, tiny machine learning (tinyML) provides hardware and software paradigms that enable always-on, real-time, low-cost, and ultra-low-power inference at the extreme edge. To achieve even lower power envelope, lower latency, and smaller footprint, sensor manufacturers now integrate custom processing logic directly within the sensors for data analytics. These integrated processing blocks provide instructions for on-chip sensor fusion, signal conditioning, and running Machine Learning models. 

Sustainable, inclusive, resilient technological innovations are fundamental to progress towards UN Sustainable Development Goals (SDGs). However, most often it is not the technology itself, but the way technology is developed and deployed that will be instrumental in achieving these goals. Well-designed sensors and trustworthy data pipe-lines, are critically important to enable smart “human and technology” environments that allow governments, businesses, and communities to reduce poverty, improve health, create new economic opportunities, and help mitigate climate change. 

3D perception, the ability to perceive depth and spatial relationships in the world, is fundamental to human cognition. In recent years, advancements in technology have enabled the development of 3D perception systems that replicate and enhance this capability in machines. From computer vision to robotics, 3D perception holds immense potential across various sensing domains, revolutionizing how we interact with and understand the world.

Almost 100% of MEMS gyroscopes you use in your everyday life is based on the well-consolidated capacitive mode-split architecture. A concurrent progress in technological developments and conception of new architectures gave birth in the last decade to alternative topologies, including mode-matching, amplitude-amplification, NEMS-based sensing, microshell-based sensing, frequency modulation, rate integrating… and other principles.

Photoplethysmography (PPG) is a low-cost electro-optical sensing technique that provides valuable health information. Due to the small dimensions, PPG has been largely applied to personal portable devices and pulse oximetry. However, discrepancies in PPG measurements based on skin tone, gender, body mass index, age and physical condition have been reported. Another important challenge of PPG sensor resolves around the significant power consumption of light-emitting diodes in a PPG sensor.

In this presentation we will feature our flexible electrochemical probes based on biomimetric responsive composite hydrogels for in-situ multiplex detection of biologically relevant chemical markers, e.g., redox biomarkers, pH, biogenic amines, lactate, cortisol, and adrenaline. The composite hydrogels in these sensors simultaneously serve as an interface for biological fluid sampling and a medium for electrochemical sensing. In this presentation we will demonstrate results of our e-skin wearable sensors for real-time wireless monitoring of mental health biomarkers (emphasis on cortisol and adrenaline) in human sweat, towards applications in diagnostics in mental health and wellness. An accompanying emotional sensor app will be demonstrated. 

Thanks to their exceptional performance, scalability, low-power consumption and cost-effectiveness, MEMS sensors are becoming integral components of modern technologies for a wide range of applications, including quantum, automotive, industrial, medical, aerospace and agricultural. Integration of MEMS sensors with CMOS circuits significantly enhances the performance of MEMS-based systems, in terms of higher sensitivity and lower power consumption, while reducing their footprint and cost. This tutorial will discuss various approaches in the designs of silicon-based CMOS-MEMS wireless sensors, their advantages and current challenges. 

Electrochemical Impedance Spectroscopy (EIS) is a powerful tool that offers deep insights into the behavior of complex electrochemical systems. Plenty of tutorials in the literature explain the basics of EIS in a detailed manner, but this tutorial provides a comprehensive understanding of EIS's principles, methodologies, and applications, catering to both beginners and seasoned practitioners in the field of electrochemical sensors, batteries, fuel cell, biosensors and many others. The tutorial starts with the foundational concepts, including impedance theory and circuit modeling. It gradually explores advanced topics such as experimental setup, data interpretation, and impedance spectroscopy in various electrochemical systems. Through a combination of theoretical insights, practical demonstrations, and case studies, the tutorial provides participants with the skills and knowledge necessary to harness the full potential of EIS in research, development, and industrial applications. 

Pandemics caused by airborne pathogens have been occurring, with devastating impact to human health, as well as national and food security, throughout human history. Despite advances in modern diagnostic and surveillance methods, a new outbreak is still detected through observation of large numbers of sick or dead animals, or of symptomatic individuals at point-of-care. This tutorial will provide a thorough introduction and review to the rapidly evolving field of real-time airborne pathogen sensing. We will review types of pathogens of interest, generation of pathogen-laden bioaerosols, and subsequent transport through air. We will then describe appropriate deposition or precipitation methods, followed by the analysis of the state-of-the art detection systems. We will analyze the available miniaturization technologies, including microfluidics and MEMS, that will enable cost-effective fabrication and wide use of such sensors. Novel techniques, such as pathogen multiplexing or pathogen-agnostic metagenomic techniques will also be described. Finally, we will conclude by providing several use cases of such sensors in agriculture and human health settings. The tutorial will include a 30-min interactive discussion regarding future directions and promising applications of this new technology. 

IEEE Heterogenous Integration Roadmap started to define clearly the nomenclature and meaning related to what we can call “more than Moore” development for microelectronics circuits.