Non-Invasive Ambient Intelligence in Real Life: Dealing with Noisy Patterns to Help Older People

This paper aims to contribute to the field of ambient intelligence from the perspective of real environments, where noise levels in datasets are significant, by showing how machine learning techniques can contribute to the knowledge creation, by promoting software sensors. The created knowledge can be actionable to develop features helping to deal with problems related to minimally labelled datasets. A case study is presented and analysed, looking to infer high-level rules, which can help to anticipate abnormal activities, and potential benefits of the integration of these technologies are discussed in this context. The contribution also aims to analyse the usage of the models for the transfer of knowledge when different sensors with different settings contribute to the noise levels. Finally, based on the authors’ experience, a framework proposal for creating valuable and aggregated knowledge is depicted.This research was partially funded by Fundación Tecnalia Research & Innovation, and J.O.-M. also wants to recognise the support obtained from the EU RFCS program through project number 793505 ‘4.0 Lean system integrating workers and processes (WISEST)’ and from the grant PRX18/00036 given by the Spanish Secretaría de Estado de Universidades, Investigación, Desarrollo e Innovación del Ministerio de Ciencia, Innovación y Universidades

Aerospace Medicine and Biology: A continuing bibliography with indexes

This bibliography lists 253 reports, articles, and other documents introduced into the NASA scientific and technical information system in October 1975

Radar Sensing in Assisted Living: An Overview

This paper gives an overview of trends in radar sensing for assisted living. It focuses on signal processing and classification, looking at conventional approaches, deep learning and fusion techniques. The last section shows examples of classification in human activity recognition and medical applications, e.g. breathing disorder and sleep stages recognition

Wearable technology: role in respiratory health and disease

In the future, diagnostic devices will be able to monitor a patient's physiological or biochemical parameters continuously, under natural physiological conditions and in any environment through wearable biomedical sensors. Together with apps that capture and interpret data, and integrated enterprise and cloud data repositories, the networks of wearable devices and body area networks will constitute the healthcare's Internet of Things. In this review, four main areas of interest for respiratory healthcare are described: pulse oximetry, pulmonary ventilation, activity tracking and air quality assessment. Although several issues still need to be solved, smart wearable technologies will provide unique opportunities for the future or personalised respiratory medicine

Development of Novel Fiber Optic Humidity Sensors and Their Derived Applications

The main focus of this thesis is on the design and development of novel fiber optic devices for relative humidity (RH) sensing with emphasis on high sensitivity, a wide humidity range, low temperature dependence, fast response time and good stability.Novel RH sensors based on fiber bends are fabricated by coating the surface of the buffer stripped bent fiber with selected hygroscopic materials such as Polyethylene oxide or Agarose. It is shown that the Polyethylene oxide coated device has a high sensitivity in a narrow RH range while the Agarose coated fiber bend shows a linear RH sensitivity in a wide RH range. Both of these sensors demonstrate a fast response (in the order of milliseconds) to RH variations. The limitations of fiber bend based humidity sensors are also discussed in the thesis. A novel RH sensor based on a reflection type photonic crystal fiber interferometer (PCFI) is presented which does not rely on the use of any hygroscopic material. The operating principle of a PCFI sensor based on the adsorption and desorption of water vapour at the silica-air interface within the PCF capillaries is discussed. The demonstrated sensor shows a good RH sensitivity in the higher RH range. Furthermore this RH sensor is almost temperature independent and can also be used in a high temperature and high pressure environment for humidity sensing.In order to improve the sensitivity of a reflection type PCFI over a wider RH range an alternative sensor is developed by infiltrating the microholes of the PCF with the hygroscopic material Agarose. The demonstrated novel sensor has a good sensitivity, a fast response time and a compact size. The temperature dependence of the device is also investigated. A novel hybrid device based on Agarose infiltrated PCFI interacting with a fiber Bragg grating is also presented which can simultaneously measure RH and temperature.A novel RH sensor based on a transmission type photonic crystal fiber interferometer coated with Agarose is also presented and discussed. This structure is used to study the effect of Agarose coating thickness in such a sensor on the RH sensitivity. It is demonstrated that the RH sensitivity of the sensor has a significant dependence on the thickness of the coating. An experimental method is also demonstrated to select an optimum coating thickness to achieve the highest sensitivity for a given RH sensing range. The sensor with the highest demonstrated sensitivity shows a linear response in the RH ranges of 40-80 % and 80-95 % with a sensitivity of 0.57 nm/%RH and 1.43 nm/%RH respectively.Finally, a comparison of the four RH sensing devices is presented, based on their size, operating range, RH sensitivity, temperature dependence and response time, in the context of selecting suitable devices for end-user applications. Two examples of applications are presented: dew sensing and breathing monitoring. The reflection type PCFI which does not use any hygroscopic material is selected for dew sensing and the dew response of the device is presented and discussed. Finally a novel breathing sensor based on the Agarose infiltrated PCFI is developed, which due to its immunity to interference from electric and magnetic fields, is suitable for breath monitoring of patients during medical procedures such as a magnetic resonance imaging scan

Development of a Breath Sampler and proof of concept

Treballs Finals de Grau d'Enginyeria Biomèdica. Facultat de Medicina i Ciències de la Salut. Universitat de Barcelona. Curs: 2020-2021. Tutor/Director: Directori Tutor: Antonio Pardo MartínezIn the last few decades, there has been a pervading interest in non invasive technologies for diagnosis, monitoring as well as for treatment in the medical field. As part of this trend, breath analysis has emerged, and although very promising, there is a main issue this field’s development faces, the lack of reproducibility and reliability of protocols since there’s no standardization in the sampling process. This project aims to develop a Breath Sampler focused on achieving a protocolized sampling methodology that allows the collection of the fraction of exhaled air that has been in contact with the alveoli and therefore is rich in metabolites. To do so, different improvements of hardware and software are implemented on a first Breath Sampler prototype and a proof of concept is carried out to verify that itoperates as intended

Towards disappearing user interfaces for ubiquitous computing: human enhancement from sixth sense to super senses

The enhancement of human senses electronically is possible when pervasive computers interact unnoticeably with humans in Ubiquitous Computing. The design of computer user interfaces towards “disappearing” forces the interaction with humans using a content rather than a menu driven approach, thus the emerging requirement for huge number of non-technical users interfacing intuitively with billions of computers in the Internet of Things is met. Learning to use particular applications in Ubiquitous Computing is either too slow or sometimes impossible so the design of user interfaces must be naturally enough to facilitate intuitive human behaviours. Although humans from different racial, cultural and ethnic backgrounds own the same physiological sensory system, the perception to the same stimuli outside the human bodies can be different. A novel taxonomy for Disappearing User Interfaces (DUIs) to stimulate human senses and to capture human responses is proposed. Furthermore, applications of DUIs are reviewed. DUIs with sensor and data fusion to simulate the Sixth Sense is explored. Enhancement of human senses through DUIs and Context Awareness is discussed as the groundwork enabling smarter wearable devices for interfacing with human emotional memories

PhysioGait: Context-Aware Physiological Context Modeling for Person Re-identification Attack on Wearable Sensing

Person re-identification is a critical privacy breach in publicly shared healthcare data. We investigate the possibility of a new type of privacy threat on publicly shared privacy insensitive large scale wearable sensing data. In this paper, we investigate user specific biometric signatures in terms of two contextual biometric traits, physiological (photoplethysmography and electrodermal activity) and physical (accelerometer) contexts. In this regard, we propose PhysioGait, a context-aware physiological signal model that consists of a Multi-Modal Siamese Convolutional Neural Network (mmSNN) which learns the spatial and temporal information individually and performs sensor fusion in a Siamese cost with the objective of predicting a person's identity. We evaluated PhysioGait attack model using 4 real-time collected datasets (3-data under IRB #HP-00064387 and one publicly available data) and two combined datasets achieving 89% - 93% accuracy of re-identifying persons.Comment: Accepted in IEEE MSN 2022. arXiv admin note: substantial text overlap with arXiv:2106.1190

NILM techniques for intelligent home energy management and ambient assisted living: a review

The ongoing deployment of smart meters and different commercial devices has made electricity disaggregation feasible in buildings and households, based on a single measure of the current and, sometimes, of the voltage. Energy disaggregation is intended to separate the total power consumption into specific appliance loads, which can be achieved by applying Non-Intrusive Load Monitoring (NILM) techniques with a minimum invasion of privacy. NILM techniques are becoming more and more widespread in recent years, as a consequence of the interest companies and consumers have in efficient energy consumption and management. This work presents a detailed review of NILM methods, focusing particularly on recent proposals and their applications, particularly in the areas of Home Energy Management Systems (HEMS) and Ambient Assisted Living (AAL), where the ability to determine the on/off status of certain devices can provide key information for making further decisions. As well as complementing previous reviews on the NILM field and providing a discussion of the applications of NILM in HEMS and AAL, this paper provides guidelines for future research in these topics.Agência financiadora: Programa Operacional Portugal 2020 and Programa Operacional Regional do Algarve 01/SAICT/2018/39578 Fundação para a Ciência e Tecnologia through IDMEC, under LAETA: SFRH/BSAB/142998/2018 SFRH/BSAB/142997/2018 UID/EMS/50022/2019 Junta de Comunidades de Castilla-La-Mancha, Spain: SBPLY/17/180501/000392 Spanish Ministry of Economy, Industry and Competitiveness (SOC-PLC project): TEC2015-64835-C3-2-R MINECO/FEDERinfo:eu-repo/semantics/publishedVersio