A scoping review and a taxonomy of the use of motion-based technology centered on the end user. A special focus on elderly health

Motion-based technology (MBT) has been applied in the last decades with enormous success in a high number of applications. Its use continues growing and is specially interesting in the health area. Nowadays, its employment is being more and more specialised with respect to the profile of the end user (i.e., child, adolescent/teenager, adult or elderly). This paper first reviews the use of MBT centered in the end user from a global perspective. It also proposes a taxonomy that allows cataloguing the MBT employment directed to the end user. Then, from these results, the paper centers the review on the MBT application aiming to improve the health of elderly. The results highlighted in this paper can help to a better understanding of MBT, especially when it is applied thinking in elderly as the end users.This study is partially funded by the Universidad de Málaga with the national project Bio4Res (PID2021-125184NB-I00) from the Ministerio de Ciencia e Innovaci ́on de Espa ̃na (MCIN). Funding for open access charge: Universidad de Málaga / CBUA

Electronics for Sensors

The aim of this Special Issue is to explore new advanced solutions in electronic systems and interfaces to be employed in sensors, describing best practices, implementations, and applications. The selected papers in particular concern photomultiplier tubes (PMTs) and silicon photomultipliers (SiPMs) interfaces and applications, techniques for monitoring radiation levels, electronics for biomedical applications, design and applications of time-to-digital converters, interfaces for image sensors, and general-purpose theory and topologies for electronic interfaces

Quality of service optimization in solar cells-based energy harvesting wireless sensor networks

In energy harvesting wireless sensor networks, the sensors are able to harvest energy from the environment to recharge their batteries and thus prolong indefinitely their activities. Widely used energy harvesting systems are based on solar cells, which are predictable (i.e., their energy production can be predicted in advance). However, since the energy production of solar cells is not constant during the day, and it is null at night time, these systems require algorithms able to balance the energy consumption and production of the sensors. In this framework, we approach the design of a scheduling algorithm for the sensors that selects among a set of available tasks for the sensors (each assigned with a given quality of service), in order to keeping the sensors energy neutral, i.e., the energy produced during a day exceeds the energy consumed in the same time frame, while improving the overall quality of service. The algorithm solves an optimization problem by using a greedy approach that can be easily implemented on low-power sensors. The simulation results demonstrate that our approach is able to improve the quality of the overall scheduling plan of all networked sensors and that it actually maintains them energy neutral

Optimized Biosignals Processing Algorithms for New Designs of Human Machine Interfaces on Parallel Ultra-Low Power Architectures

The aim of this dissertation is to explore Human Machine Interfaces (HMIs) in a variety of biomedical scenarios. The research addresses typical challenges in wearable and implantable devices for diagnostic, monitoring, and prosthetic purposes, suggesting a methodology for tailoring such applications to cutting edge embedded architectures. The main challenge is the enhancement of high-level applications, also introducing Machine Learning (ML) algorithms, using parallel programming and specialized hardware to improve the performance. The majority of these algorithms are computationally intensive, posing significant challenges for the deployment on embedded devices, which have several limitations in term of memory size, maximum operative frequency, and battery duration. The proposed solutions take advantage of a Parallel Ultra-Low Power (PULP) architecture, enhancing the elaboration on specific target architectures, heavily optimizing the execution, exploiting software and hardware resources. The thesis starts by describing a methodology that can be considered a guideline to efficiently implement algorithms on embedded architectures. This is followed by several case studies in the biomedical field, starting with the analysis of a Hand Gesture Recognition, based on the Hyperdimensional Computing algorithm, which allows performing a fast on-chip re-training, and a comparison with the state-of-the-art Support Vector Machine (SVM); then a Brain Machine Interface (BCI) to detect the respond of the brain to a visual stimulus follows in the manuscript. Furthermore, a seizure detection application is also presented, exploring different solutions for the dimensionality reduction of the input signals. The last part is dedicated to an exploration of typical modules for the development of optimized ECG-based applications

Stand-alone wearable system for ubiquitous real-time monitoring of muscle activation potentials

Wearable technology is attracting most attention in healthcare for the acquisition of physiological signals. We propose a stand-alone wearable surface ElectroMyoGraphy (sEMG) system for monitoring the muscle activity in real time. With respect to other wearable sEMG devices, the proposed system includes circuits for detecting the muscle activation potentials and it embeds the complete real-time data processing, without using any external device. The system is optimized with respect to power consumption, with a measured battery life that allows for monitoring the activity during the day. Thanks to its compactness and energy autonomy, it can be used outdoor and it provides a pathway to valuable diagnostic data sets for patients during their own day-life. Our system has performances that are comparable to state-of-art wired equipment in the detection of muscle contractions with the advantage of being wearable, compact, and ubiquitous

Energy-Efficient Communication in Wireless Networks

This chapter describes the evolution of, and state of the art in, energy‐efficient techniques for wirelessly communicating networks of embedded computers, such as those found in wireless sensor network (WSN), Internet of Things (IoT) and cyberphysical systems (CPS) applications. Specifically, emphasis is placed on energy efficiency as critical to ensuring the feasibility of long lifetime, low‐maintenance and increasingly autonomous monitoring and control scenarios. A comprehensive summary of link layer and routing protocols for a variety of traffic patterns is discussed, in addition to their combination and evaluation as full protocol stacks

Conjoined piezoelectric harvesters and carbon supercapacitors for powering intelligent wireless sensors

To achieve total freedom of location for intelligent wireless sensors (IWS), these need to be autonomous. To achivethis today there is a need of broadband piezoelectric energy harvesting and a long-lasting energy. The Harvester needto be able to provide sufficient amount of energy for the intelligent wireless sensor to perform its task. The energystorage needs to fulfill the requirement of a large number of charge discharge cycles and contain sufficient power forthe intelligent wireless sensor.The biggest issue with piezoelectric energy harvesting today is the bandwidth limitation. Solutions today to achievelarger bandwidth make a tradeoff where the output is decreased. The biggest issue for energy storage today is thelimitation of energy density for supercapacitors and the lack of sufficient life cycles for batteries.This thesis aims to realize piezoelectric energy harvesters with broad bandwidth and maintained power output.Moreover, for energy storage in the form of supercapacitors realize an electrode material that has a high effectivesurface area, good conductivity not dependent on a conductive agent and can be used without a binder. This thesiscover background and history of the two fields, discussion of technologies used and presents solutions for piezoelectricenergy harvesting and carbon based supercapacitor storage.A Backfolded piezoelectric harvester was made of two conjoined piezoelectric cantilevers, one placed on top of abottom cantilever. By the backfolded design this thesis show that by utilizing the extended stress distribution of thebottom cantilever a maintained power output is achieved for both output peaks. By introducing asymmetry where thetop cantilever have 80% length compared with the bottom cantilever the bandwidth was increased. An effectivebandwidth of 70 Hz with voltage output above 2,75 V for 1 g is achieved.To achieve further enhanced bandwidth a piezoelectric energy harvester with selftuning was designed. Theselftuning was achieved by a sliding mass on a beam, which is conjoined, to two piezoelectric cantilevers in abackfolded structure. By introducing length asymmetry, the effective bandwidth was enhanced to 38 Hz with a poweroutput above 15 mW, for 1 g, which is sufficient for an intelligent wireless sensor to start up and transmit data.To utilize the positive output effect from conjoined cantielvers a micro harvester was fabricated. The design wasbased on the same principle as for the backfolded, but for fabrication reasons the design was made in one plane. Theharvester contain two outer cantilevers conjoined to a backfolded middle cantilever. Due to fabrication difficulties,only a mechanical characterization of the harvester was possible. The result from the characterization looks promisingfrom a harvesting point of view, by showing a clear peak that seems to be somewhat broadband.Energy storage for an autonomous wireless intelligent sensor (IWS) needs to be able to charge and discharge duringthe lifetime of the IWS. Therefor the choice fell on supercapacitors instead of batteries. Over time the supercapacitordue to its superior amount of charge and discharge cycles, outperform a battery when energy density is compared.Increasing the energy density for supercapacitors gives the advantage to prolong the providing of power to theIWS. One such electrode material is conjoined carbon nanofibers and carbon nanotubes. The material is not dependenton conductive agents or binders. The effective surface area can be expanded through a denser structure of CNF, wheremore CNT can grow. In combination with activation, which will yield more micropores, hence an increasedcapacitance for the presented synthesized material yielded 91 F/g with an effective surface area of 131 m2.There is many challenges to power an IWS on a gasturbine. This thesis cover challenges like vibrations on cables,placement issues and the charge of a supercapacitor by harvested energy that comes in small chunks. Solutions forthese challenges are offered.The presented work in this thesis shows how the bandwidth for piezoelectric energy harvesters can be broader byasymmetric implementation of conjoined resonators. In addition, the advantages of conjoined carbon electrodematerials to be implemented as electrode material in supercapacitors. Both harvester and storage are intended to beused as energy sources for intelligent wireless sensors

Wearables conquering the workplace of generation Y : the opportunities and risks to integrate wearable technology at work

Purpose - The purpose of this thesis is to investigate the attitude of Generation Y towards Wearable Technology (WT). The investigated gadgets of WT are Fitness trackers, Smart watches, Smart glasses and Smart Clothing. The research investigates the interest of individuals into WT sponsored by the employer and their data-sharing attitude. Design/Methodology - The thesis uses a quantitative, online survey. The survey is threefold. First, individuals were questioned towards their tracking behavior and ownership of WT. Second, the likelihood to purchase WT was compared with the likelihood to request sponsored WT by an employer. Third, the data-sharing attitude of individuals was investigated. The survey was distributed online via Social media and the data gathered via the survey tool Qualtrics. The analysis was conducted with the statistics program SPSS. Findings - First, the proportion of individuals tracking data and the data tracked confirm the interest of individuals to receive personal insights through WT. Second, the likelihood to request WT when sponsored by an employer shows a statistically significant increase for Smart watches, but decrease for Fitness trackers. For owners of WT, the likelihood increased for all four WTs. Third, the data-sharing attitude of individuals highlighted, that Generation Y does not trust the employer’s objective. Research limitations – The main limitation of this research is that it is based on a survey, which only covers a limited number of gadgets. Based on the responses for a single gadget, one derives with implications for the whole category of Wearable Technology. In addition, the topic of data sharing is covered by general questions about WT and not retrieved for each of the four devices. Practical implications - Individuals belonging to Generation Y want to remain the owner of their data and do not trust an employer’s objective. Companies must invest into WTs, which provide a holistic user experience and protect individuals’ data, to convince Generation Y. Social implications -– By providing insights into the thinking of Generation Y, companies can identify risks and opportunities on how to integrate WT at the workplace. Originality – The study focuses on the expectations and concerns of individuals towards WT, in comparison to the numerous studies highlighting the technological features.Objetivo - O objectivo desta tese é investigar a atitude da geração Y face a wearable technology (WT) . Os aparelhos investigados de WT são fitness trackers, smart watches, smart glasses e smart clothing. A pesquisa investiga o interesse dos indivíduos interessados em WT patricionados pela entidade empregadora e a sua atitude de partilha de dados. Metodologia - A tese usa um questionário online, quantitativo. O questionário é tripartido. Primei- ro, indivíduos foram questionados perante o comportamento registado e posse de WT. Seguida- mente, a probabilidade de adquirir WT foi comparsa com a probabilidade de pedir WT patriciona- dos por um empregador. Por fim, a terceira parte investiga os comportamentos de partilha de da- dos. O questionário foi distribuído online através de redes sociais e a data recolhida foi analisada via Qualtrics. A análise foi interpretada através do programa SPSS. Resultados - Primeiro, a proporção de indivíduos a registarem os seus dados e os dados recolhi- dos confiram o interesse dos indivíduos em receber informações pessoais através de WT. Em se- gundo, a probabilidade de requisitar WT quando particionados por um empregador mostra um aumento estatisticamente significativo para Smart watches, no entanto um decréscimo para Fitness trackers. Para os donos de WT a probabilidade aumentou para os quatro tipos de WT. Por último, a atitude perante partilha de dados por parte de indivíduos sublinhou que a Geração Y não confia nos objectivos do empregador. Limitações – A limitação principal desta pesquisa é o facto de ser baseada num questionário, co- brindo um número limitado de aparelhos. Baseadas nas respostas para um aparelho único, é possível derivar as implicações para toda a categoria de WT. Em adição, o tópico de partilha de dados é coberto por questões gerais sobre WT e não para cada um dos quatro aparelhos. Aplicabilidade do trabalho - Indivíduos pertencentes à Geração Y querem permanecer donos dos seus dados e não confiam nos objectivos dos empregadores. De forma a convencer a Gera- ção Y, empresas devem investir em WT que providencie ao utilizador uma experiência holistica e que protege os dados dos indivíduos. Contribuições para a sociedade – Ao providenciar informação sobre a mentalidade da Geração Y, empresas podem identificar riscos e oportunidades em como integrar WT no local de trabalho. Originalidade – Este estudo foca-se nas expectativas e preocupações dos indivíduos em compa- ração aos inúmeros estudos salientando características tecnológicas

Modeling and Simulation Methodologies for Digital Twin in Industry 4.0

The concept of Industry 4.0 represents an innovative vision of what will be the factory of the future. The principles of this new paradigm are based on interoperability and data exchange between dierent industrial equipment. In this context, Cyber- Physical Systems (CPSs) cover one of the main roles in this revolution. The combination of models and the integration of real data coming from the field allows to obtain the virtual copy of the real plant, also called Digital Twin. The entire factory can be seen as a set of CPSs and the resulting system is also called Cyber-Physical Production System (CPPS). This CPPS represents the Digital Twin of the factory with which it would be possible analyze the real factory. The interoperability between the real industrial equipment and the Digital Twin allows to make predictions concerning the quality of the products. More in details, these analyses are related to the variability of production quality, prediction of the maintenance cycle, the accurate estimation of energy consumption and other extra-functional properties of the system. Several tools [2] allow to model a production line, considering dierent aspects of the factory (i.e. geometrical properties, the information flows etc.) However, these simulators do not provide natively any solution for the design integration of CPSs, making impossible to have precise analysis concerning the real factory. Furthermore, for the best of our knowledge, there are no solution regarding a clear integration of data coming from real equipment into CPS models that composes the entire production line. In this context, the goal of this thesis aims to define an unified methodology to design and simulate the Digital Twin of a plant, integrating data coming from real equipment. In detail, the presented methodologies focus mainly on: integration of heterogeneous models in production line simulators; Integration of heterogeneous models with ad-hoc simulation strategies; Multi-level simulation approach of CPS and integration of real data coming from sensors into models. All the presented contributions produce an environment that allows to perform simulation of the plant based not only on synthetic data, but also on real data coming from equipments