Photoplethysmography for Quantitative Assessment of Sympathetic Nerve Activity (SNA) During Cold Stress

The differences in the degree of sympathetic nerve activity (SNA) over cutaneous blood vessels, although known to be more prominent in the periphery than the core vasculature, has not been thoroughly investigated quantitatively. Hence, two studies were carried out to investigate the differences in SNA between the periphery and the core during the cold pressor test (CPT) (right-hand immersion in ice water) and cold exposure (whole body exposed to cold air) using photoplethysmography (PPG). Two methods utilizing PPG, namely differential multi-site PTT measurements and low-frequency spectral analysis were explored for quantitative determination of SNA. Each study involved 12 healthy volunteers, and PPG signals were acquired from the right index finger (RIF), left index finger (LIF) (periphery) and the ear canal (core). During CPT, Pulse Transit Time (PTT) was measured to the respective locations and the mean percentage change in PTT during ice immersion at each location was used as an indicator for the extent of SNA. During cold exposure, the low-frequency spectral analysis was performed on the acquired raw PPGs to extract the power of the sympathetic [low-frequency (LF): 0.04–0.15 Hz] and parasympathetic components [high-frequency (HF): 0.15–0.4 Hz]. The ratio of LF/HF components was then used to quantify the differences in the influence of SNA on the peripheral and core circulation. PTT measured from the EC, and the LIF has dropped by 5 and 7%, respectively during ice immersion. The RIF PTT, on the other hand, has dropped significantly (P < 0.05) by 12%. During the cold exposure, the LF/HF power ratio at the finger has increased to 86.4 during the cold exposure from 19.2 at the baseline (statistically significant P = 0.002). While the ear canal LF/HF ratio has decreased to 1.38 during the cold exposure from 1.62 at baseline (P = 0.781). From these observations, it is evident that differential PTT measurements or low-frequency analysis can be used to quantify SNA. The results also demonstrate the effectiveness of the central auto-regulation during both short and long-term stress stimulus as compared to the periphery

Smart workplaces: a system proposal for stress management

Over the past last decades of contemporary society, workplaces have become the primary source of many health issues, leading to mental problems such as stress, depression, and anxiety. Among the others, environmental aspects have shown to be the causes of stress, illness, and lack of productivity. With the arrival of new technologies, especially in the smart workplaces field, most studies have focused on investigating the building energy efficiency models and human thermal comfort. However, little has been applied to occupants’ stress recognition and well-being overall. Due to this fact, this present study aims to propose a stress management solution for an interactive design system that allows the adapting of comfortable environmental conditions according to the user preferences by measuring in real-time the environmental and biological characteristics, thereby helping to prevent stress, as well as to enable users to cope stress when being stressed. The secondary objective will focus on evaluating one part of the system: the mobile application. The proposed system uses several usability methods to identify users’ needs, behavior, and expectations from the user-centered design approach. Applied methods, such as User Research, Card Sorting, and Expert Review, allowed us to evaluate the design system according to Heuristics Analysis, resulting in improved usability of interfaces and experience. The study presents the research results, the design interface, and usability tests. According to the User Research results, temperature and noise are the most common environmental stressors among the users causing stress and uncomfortable conditions to work in, and the preference for physical activities over the digital solutions for coping with stress. Additionally, the System Usability Scale (SUS) results identified that the system’s usability was measured as “excellent” and “acceptable” with a final score of 88 points out of the 100. It is expected that these conclusions can contribute to future investigations in the smart workplaces study field and their interaction with the people placed there.Nas últimas décadas da sociedade contemporânea, o local de trabalho tem se tornado principal fonte de muitos problemas de saúde mental, como o stress, depressão e ansiedade. Os aspetos ambientais têm se revelado como as causas de stress, doenças, falta de produtividade, entre outros. Atualmente, com a chegada de novas tecnologias, principalmente na área de locais de trabalho inteligentes, a maioria dos estudos tem se concentrado na investigação de modelos de eficiência energética de edifícios e conforto térmico humano. No entanto, pouco foi aplicado ao reconhecimento do stress dos ocupantes e ao bem-estar geral das pessoas. Diante disso, o objetivo principal é propor um sistema de design de gestão do stress para um sistema de design interativo que permita adaptar as condições ambientais de acordo com as preferências de utilizador, medindo em tempo real as características ambientais e biológicas, auxiliando assim na prevenção de stress, bem como ajuda os utilizadores a lidar com o stress quando estão sob o mesmo. O segundo objetivo é desenhar e avaliar uma parte do projeto — o protótipo da aplicação móvel através da realização de testes de usabilidade. O sistema proposto resulta da abordagem de design centrado no utilizador, utilizando diversos métodos de usabilidade para identificar as necessidades, comportamentos e as expectativas dos utilizadores. Métodos aplicados, como Pesquisa de Usuário, Card Sorting e Revisão de Especialistas, permitiram avaliar o sistema de design de acordo com a análise heurística, resultando numa melhoria na usabilidade das interfaces e experiência. O estudo apresenta os resultados da pesquisa, a interface do design e os testes de usabilidade. De acordo com os resultados de User Research, a temperatura e o ruído são os stressores ambientais mais comuns entre os utilizadores, causando stresse e condições menos favoráveis para trabalhar, igualmente existe uma preferência por atividades físicas sobre as soluções digitais na gestão do stresse. Adicionalmente, os resultados de System Usability Scale (SUS) identificaram a usabilidade do sistema de design como “excelente” e “aceitável” com pontuação final de 88 pontos em 100. É esperado que essas conclusões possam contribuir para futuras investigações no campo de estudo dos smart workplaces e sua interação com os utilizadores

In vivo non-invasive monitoring of optically resonant metal nanoparticles using multi-wavelength photoplethysmography

Nanotechnology has recently emerged as a powerful modality in many biomedical applications. In particular, several classes of nanoparticles have been employed as cancer therapy and imaging contrast agents. These particles can have architecture of varying complexity, depending on their specific application. These complex architectures are achieved by various chemical techniques usually performed in specific sequences to add complexity and functionality. One such class of nanoparticle, used in tumor treatment and as contrast agents in several optical imaging techniques, is the plasmon resonant metal nanoparticle. The most common metal used for these particles is gold because of its biocompatibility, lack of cellular toxicity, and simple surface chemistry. These particles have specific optical properties in the near infrared spectrum making them ideal for modern cancer therapy and optical imaging. Two examples of these particles are gold nanoshells and gold nanorods, both of which are highly absorptive and scattering at near infrared wavelengths. It is for this reason that they are often employed in photo thermal ablation of tumors using near infrared light. In this type of tumor treatment, the particles are injected intravenously and accumulate in the tumor. After accumulation, a near infrared laser is used to heat the particles and destroy the tumor. These gold nanoparticles must be modified with biocompatible stealthing compounds before they can be injected. This is because of the high efficiency of the body\u27s reticuloendotheial system, which will quickly eliminate materials foreign through cellular phagocytosis. Although techniques for quality control in manufacturing these nanoparticles are used to confirm proper surface modification, their in vivo behavior is very difficult to predict. It is for this reason that real time feedback in nanoparticle therapy is an urgent need and will greatly improve its efficacy. This dissertation reports the development of a non-invasive optical system capable of reporting the in vivo vascular concentration of these nanoparticles in near real time. The device, termed the pulse photometer, utilizes a technique similar to that used in pulse oximetry. This technique is photoplethysmography, which has many medical applications. One of these is determining the optical characteristics of pulsatile arterial blood, which are affected after the injection of these optically resonant particles. Several prototypes of this are presented in this dissertation. The culmination of this work is the prototype III pulse photometer capable of concurrent nanoparticle monitoring and oximetry. Final testing of this prototype revealed its ability to accurately determine the vascular optical density of gold nanorods compared to ex vivo spectrophotometry, a technique also verified in this dissertation, by statistical Bland-Altman analysis

Physiological and behavior monitoring systems for smart healthcare environments: a review

Healthcare optimization has become increasingly important in the current era, where numerous challenges are posed by population ageing phenomena and the demand for higher quality of the healthcare services. The implementation of Internet of Things (IoT) in the healthcare ecosystem has been one of the best solutions to address these challenges and therefore to prevent and diagnose possible health impairments in people. The remote monitoring of environmental parameters and how they can cause or mediate any disease, and the monitoring of human daily activities and physiological parameters are among the vast applications of IoT in healthcare, which has brought extensive attention of academia and industry. Assisted and smart tailored environments are possible with the implementation of such technologies that bring personal healthcare to any individual, while living in their preferred environments. In this paper we address several requirements for the development of such environments, namely the deployment of physiological signs monitoring systems, daily activity recognition techniques, as well as indoor air quality monitoring solutions. The machine learning methods that are most used in the literature for activity recognition and body motion analysis are also referred. Furthermore, the importance of physical and cognitive training of the elderly population through the implementation of exergames and immersive environments is also addressedinfo:eu-repo/semantics/publishedVersio

SAGA: Smart gateway for adaptive environments

The development of adaptive environments has the main objective of providing well-being to an individual, improving the environmental conditions of indoor environments and facilitating/automating any activity. In order to implement such systems, the use of devices capable of intercommunication and acquisition of environment-related parameters around the user is essential. Using wireless sensor networks, it is possible to monitor the various quality indices of indoor environments that can be used to develop strategies to improve quality of life of the users in personalized way. In this dissertation, a system based on a wireless sensor network that analyses and improves the environmental quality of indoor spaces, as well as evaluating the health status of an individual is presented. The system acquires and acts upon air quality and illumination quality-related parameters, as well as physiological data of a user, using sensor nodes and actuators distributed throughout the environment. Several wireless communication protocols have been implemented to enable intercommunication between the several elements present in the sensor network, such as actuators, sensor nodes and a coordinating / gateway node. Several warning mechanisms have been configured to alert the user to the presence of factors that may endanger their health, namely the presence of pollutants and thermal conditions that may trigger respiratory distress. In order to provide real-time system control including additional warning mechanisms, data analysis, a dedicated web application has been developed for this system. The user can control the environment according with his own needs and preferences through profiles configuration. The whole process of system development, hardware, software, experimental tests and contributions are included in this dissertation.A criação de ambientes adaptativos tem o principal objetivo de providenciar o bem-estar a um indivíduo, melhorar as condições do ambiente em seu redor e de facilitar/automatizar qualquer atividade. De forma a implementar tais sistemas, a utilização de dispositivos com capacidade de intercomunicação e de recolha de parâmetros relacionados com o ambiente em redor do utilizador é essencial. Com a utilização de redes de sensores sem fios, é possível monitorizar os diversos índices de qualidade de um ambiente interior e dessa forma melhorar a qualidade de vida. Nesta dissertação será apresentado um sistema baseado numa rede de sensores sem fios que permite analisar e melhorar a qualidade ambiental de espaços interiores e avaliar o estado de saúde de um indivíduo. O sistema adquire e atua sobre parâmetros relacionados com a qualidade do ar e qualidade de iluminação, assim como dados fisiológicos de um utilizador, através da utilização de nós de sensores e atuadores distribuídos pelo ambiente. Foram implementados diversos protocolos de comunicação sem fios para possibilitar a intercomunicação com outros elementos da rede, nomeadamente o nó coordenador/gateway. Foram configurados diversos mecanismos de alerta de forma a avisar o utilizador para a presença de fatores que possam colocar em risco a sua saúde, nomeadamente a presença de poluentes e condições térmicas que possam desencadear desconforto respiratório. De forma a proporcionar uma análise de dados em tempo real, controlo do sistema e dispor de mecanismos de alerta adicionais, foi desenvolvida uma aplicação Web dedicada a este sistema. Através desta, o utilizador poderá tornar o ambiente adaptável às suas características e de acordo com as suas preferências, através da configuração de perfis. Todo o processo de desenvolvimento do sistema, hardware, software, testes experimentais e contribuições serão incluídos nesta dissertação

Wireless Pressure Ulcer Prevention Device

Pressure ulcers are a common problem in current hospital settings. This project created a system to detect the early onset of pressure ulcers and alert a caregiver. Three different physiological factors, known to contribute to the formation of pressure ulcers, can be continuously measured via a disposable adhesive patch and wirelessly transmitted to a computer interface. The user interface instructs a clinician to input additional physiological factors, not locally measured, which indicate the risk of local ulcer formation

Accurate and Robust Heart Rate Sensor Calibration on Smartwatches using Deep Learning

Heart rate (HR) monitoring has been the foundation of many researches and applications in the field of health care, sports and fitness, and physiology. With the development of affordable non- invasive optical heart rate monitoring technology, continuous monitoring of heart rate and related physiological parameters is increasingly possible. While this allows continuous access to heart rate information, its potential is severely constrained by the inaccuracy of the optical sensor that provides the signal for deriving heart rate information. Among all the factors influencing the sensor performance, hand motion is a particularly significant source of error. In this thesis, we first quantify the robustness and accuracy of the wearable heart rate monitor under everyday scenario, demonstrating its vulnerability to different kinds of motions. Consequently, we developed DeepHR, a deep learning based calibration technique, to improve the quality of heart rate measurements on smart wearables. DeepHR associates the motion features captured by accelerometer and gyroscope on the wearable with a reference sensor, such as a chest-worn HR monitor. Once pre-trained, DeepHR can be deployed on smart wearables to correct the errors caused by motion. Through rigorous and extensive benchmarks, we demonstrate that DeepHR significantly improves the accuracy and robustness of HR measurements on smart wearables, being superior to standard fully connected deep neural network models. In our evaluation, DeepHR is capable of generalizing across different activities and users, demonstrating that having a general pre-trained and pre-deployed model for various individual users is possible

Sensing with Earables: A Systematic Literature Review and Taxonomy of Phenomena

Earables have emerged as a unique platform for ubiquitous computing by augmenting ear-worn devices with state-of-the-art sensing. This new platform has spurred a wealth of new research exploring what can be detected on a wearable, small form factor. As a sensing platform, the ears are less susceptible to motion artifacts and are located in close proximity to a number of important anatomical structures including the brain, blood vessels, and facial muscles which reveal a wealth of information. They can be easily reached by the hands and the ear canal itself is affected by mouth, face, and head movements. We have conducted a systematic literature review of 271 earable publications from the ACM and IEEE libraries. These were synthesized into an open-ended taxonomy of 47 different phenomena that can be sensed in, on, or around the ear. Through analysis, we identify 13 fundamental phenomena from which all other phenomena can be derived, and discuss the different sensors and sensing principles used to detect them. We comprehensively review the phenomena in four main areas of (i) physiological monitoring and health, (ii) movement and activity, (iii) interaction, and (iv) authentication and identification. This breadth highlights the potential that earables have to offer as a ubiquitous, general-purpose platform