Analysis of Wireless Body-Centric Medical Sensors for Remote Healthcare

Aquesta tesi aborda el problema de trobar solucions confortables, de baixa potència i sense fils per aplicacions mèdiques. La tesi tracta els avantatges i les limitacions de tres tecnologies de comunicació diferents per la mesura de paràmetres del cos i mètodes per redissenyar sensors per avaluacions òptimes centrades en el cos. La tecnologia RFID es considera una de les solucions més influents per superar el problema del consum d'energia limitat, a causa de la presència de molts sensors connectats. També s'ha estudiat la tecnologia Bluetooth de baixa energia per resoldre els problemes de seguretat i la distància de lectura que, en general, representen el coll d'ampolla de RFID pels sensors de cos. Els dispositius analògics poden reduir dràsticament les necessitats d'energia a causa dels sensors i les comunicacions, considerant pocs elements i un mètode de transmissió simple. S'estudia un mètode de comunicació completament passiu, basat en FSS, que permet una distància de lectura raonable amb capacitats de detecció precises i confiables, que s'ha discutit en aquesta tesi. L'objectiu d'aquesta tesi és investigar múltiples tecnologies sense fils per dispositius portàtils per identificar solucions adequades per aplicacions particulars en el camp mèdic. El primer objectiu és demostrar la facilitat d'ús de les tecnologies econòmiques sense bateria com un indicador útil de paràmetres fisiopatològics mitjançant la investigació de les propietats de les etiquetes RFID. A més a més, s'ha abordat un aspecte més complex respecte a l'ús de petits components passius com sensors sense fils per trastorns del son. Per últim, un altre objectiu de la tesi és el desenvolupament d'un sistema completament autònom que utilitzi tecnologia BLE per obtenir propietats avançades mantenint baix tant el consum com el preuEsta tesis aborda el problema de encontrar soluciones confortables, inalámbricas y de baja potencia para aplicaciones médicas. La tesis discute las ventajas y limitaciones de tres tecnologías de comunicación diferentes para la medición en el cuerpo y los métodos para elegir y remodelar los sensores para evaluaciones óptimas centradas en el cuerpo. La tecnología RFID se considera una de las soluciones más influyentes para superar el consumo de energía limitado debido a la presencia de muchos sensores conectados. Además, la baja energía de Bluetooth se ha estudiado se ha estudiado la tecnologia Bluetooth de baja energia para resolver los problemas de seguridad y la distancia de lectura que, en general, representan el cuello de botella de la RFID para los sensores de cuerpo. Los dispositivos analógicos pueden reducir drásticamente las necesidades de energía debido a los sensores y las comunicaciones, considerando pocos elementos y un método de transmisión simple. Se estudia un método de comunicación completamente pasivo, basado en FSS, que permite una distancia de lectura razonable con capacidades de detección precisas y confiables, que se ha discutido en esta tesis. El objetivo de esta tesis es investigar múltiples tecnologías inalámbricas para dispositivos portátiles para identificar soluciones adecuadas para aplicaciones particulares en campos médicos. El primer objetivo es demostrar la facilidad de uso de las tecnologías económicas sin batería como un indicador útil de dichos parámetros fisiopatológicos mediante la investigación de las propiedades de las etiquetas RFID. Además, se ha abordado un aspecto más complejo con respecto al uso de pequeños componentes pasivos como sensores inalámbricos para enfermedades del sueño. Por último, un resultado de la tesis es desarrollar un sistema completamente autónomo que utilice la tecnología BLE para obtener propiedades avanzadas que mantengan la baja potencia y un precio bajo.This thesis addresses the problem of comfortable, low powered and, wireless solutions for specific body-worn sensing. The thesis discusses advantages and limitations of three different communication technologies for on body measurement and investigate methods to reshape sensors for optimum body-centric assessments. The RFID technology is considered one of the most influential solutions to overcome the limitated power consumption due to the presence of many sensors connected. Further, the Bluetooth low energy has been studied to solve security problems and reading distance that overall represent the bottleneck of the RFID for the body-worn sensors. Analog devices can drastically reduce the energy needs due to the sensors and the communications, considering few elements and a simple transmitting method. An entirely passive communication method, based on FSS is studied, enabling a reasonable reading distance with precise and reliable sensing capabilities, which has been discussed in this thesis. The objective of this thesis is to investigate multiple wireless technologies for wearable devices to identify suitable solutions for particular applications in medical fields. The first objective is to demonstrate the usability of the inexpensive battery-less technologies as a useful indicator of such a physio-pathological parameters by investigating the properties of the RFID tags. Furthermore, a more complex aspect regards the use of small passive components as wireless sensors for sleep diseases has been addressed. Lastly, an outcome of the thesis is to develop an entirely autonomous system using the BLE technology to obtain advanced properties keeping low power and a low price

Doppler radar remote sensing of respiratory function

Doppler radar remote sensing of torso kinematics can provide an indirect measure of cardiopulmonary function. Motion at the human body surface due to heart and lung activity has been successfully used to characterize such measures as respiratory rate and depth, obstructive sleep apnea, and even the identity of an individual subject. For a sedentary subject, Doppler radar can track the periodic motion of the portion of the body moving as a result of the respiratory cycle as distinct from other extraneous motions that may occur, to provide a spatial temporal displacement pattern that can be combined with a mathematical model to indirectly assess quantities such as tidal volume, and paradoxical breathing. Furthermore, it has been demonstrated that even healthy respiratory function results in distinct motion patterns between individuals that vary as a function of relative time and depth measures over the body surface during the inhalation/exhalation cycle. Potentially, the biomechanics that results in different measurements between individuals can be further exploited to recognize pathology related to lung ventilation heterogeneity and other respiratory diagnostics

High-Resolution Indoor Sensing Using Channel State Information of WiFi Networks

Indoor sensing is becoming increasingly important over time as it can be effectively utilized in many applications from digital health care systems to indoor safety and security systems. In particular, implementing sensing operations using existing infrastructures improves our experience and well-being, and exhibits unique advantages. The physical layer channel state information for wireless fidelity (WiFi) communications carries rich information about scatters in the propagation environment; hence, we exploited this information to enable detailed recognition of human behaviours in this study. Comprehensive calibration and filtering techniques were developed to alleviate the redundant responses embedded in the channel state information (CSI) data due to static objects and accidental events. Accurate information on breathing rate, heartbeat and angle of arrival of the incoming signal at the receiver side was inferred from the available CSI data. The method and procedure developed can be extended for sensing or imaging the environment utilizing wireless communication networks

Exploração de radar para reconhecimento de gestos

Communication disorders have a notable negative impact on people’s lives, leading to isolation, depression and loss of independence. Over the years, many different approaches to attenuate these problems were proposed, although most come with noticeable drawbacks. Lack of versatility, intrusive solutions or the need to carry a device around are some of the problems that these solutions encounter. Radars have seen an increase in use over the past few years and even spreading to different areas such as the automotive and health sectors. This technology is non-intrusive, not sensitive to changes in environmental conditions such as lighting, and does not intrude on the user’s privacy unlike cameras. In this dissertation and in the scope of the APH-ALARM project, the author tests the radar in a gesture recognition context to support communication in the bedroom scenario. In this scenario, the user is someone with communication problems, lying in their bed trying to communicate with a family member inside or outside the house. The use of gestures allows the user to have assistance communicating and helps express their wants or needs. To recognize the gestures executed by the user, it is necessary to capture the movement. To demonstrate the capabilities of the technology, a proof of concept system was implemented, which captures the data, filters and transforms it into images used as input for a gesture classification model. To evaluate the solution, we recorded ten repetitions of five arm gestures executed by four people. A subject independent solution proved to be more challenging when compared to a subject dependent solution, where all datasets but one achieved a median accuracy above 70% with most going over 90%.Os problemas de comunicação têm um efeito nocivo nas vidas das pessoas como isolamento, depressão e perda de independência. Ao longo dos anos, várias abordagens para atenuar estes problemas foram propostas, sendo que a maioria tem desvantagens. Falta de versatilidade, soluções intrusivas ou a necessidade de andar com um dispositivo são alguns dos problemas destas soluções. O uso de radares tem visto um aumento nos últimos anos, chegando até áreas variadas como o setor de saúde ou automóvel. Este tipo de solução é não intrusiva, não é sensível a mudanças das condições ambientais como luz e não invade a privacidade do utilizador como o uso de câmaras. Nesta dissertação e no âmbito do projeto APH-ALARM, testou-se um radar no contexto do reconhecimento de gestos para apoio à comunicação no cenário do quarto. Neste cenário, o utilizador é alguém com problemas de comunicação, que se encontra deitado na sua cama e precisa de comunicar com um familiar dentro ou fora de casa. O uso de gestos permite ao utilizador ter algum apoio durante a comunicação e ajuda o mesmo a expressar as suas necessidades. Para reconhecer os gestos feitos pelo utilizador, é necessário capturar o movimento humano. Para demonstrar as capacidades da tecnologia para este contexto, foi implementada uma prova de conceito de um sistema que captura os dados do radar e de seguida os filtra, converte-os em imagens e usa as mesmas como entrada de um modelo para classificação de gestos. Para avaliar a solução proposta, foram recolhidos dados de quatro pessoas enquanto realizavam dez repetições de cinco gestos diferentes com um dos braços. Uma solução independente do utilizador mostrou ser um caso mais desafiante quando comparada com uma solução dependente do utilizador, em que todos os datasets excepto um tem um acerto médio superior a 70% em que a maioria deles supera os 90%.Mestrado em Engenharia de Computadores e Telemátic

A review of the state of the art in non-contact sensing for covid-19

COVID-19, caused by SARS-CoV-2, has resulted in a global pandemic recently. With no approved vaccination or treatment, governments around the world have issued guidance to their citizens to remain at home in efforts to control the spread of the disease. The goal of controlling the spread of the virus is to prevent strain on hospitals. In this paper, we focus on how non-invasive methods are being used to detect COVID-19 and assist healthcare workers in caring for COVID-19 patients. Early detection of COVID-19 can allow for early isolation to prevent further spread. This study outlines the advantages and disadvantages and a breakdown of the methods applied in the current state-of-the-art approaches. In addition, the paper highlights some future research directions, which need to be explored further to produce innovative technologies to control this pandemic

Advanced sensing techniques for intelligent human activity recognition using machine learning

No abstract available