123 research outputs found

    Self-adjustable domain adaptation in personalized ECG monitoring integrated with IR-UWB radar

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    To enhance electrocardiogram (ECG) monitoring systems in personalized detections, deep neural networks (DNNs) are applied to overcome individual differences by periodical retraining. As introduced previously [4], DNNs relieve individual differences by fusing ECG with impulse radio ultra-wide band (IR-UWB) radar. However, such DNN-based ECG monitoring system tends to overfit into personal small datasets and is difficult to generalize to newly collected unlabeled data. This paper proposes a self-adjustable domain adaptation (SADA) strategy to prevent from overfitting and exploit unlabeled data. Firstly, this paper enlarges the database of ECG and radar data with actual records acquired from 28 testers and expanded by the data augmentation. Secondly, to utilize unlabeled data, SADA combines self organizing maps with the transfer learning in predicting labels. Thirdly, SADA integrates the one-class classification with domain adaptation algorithms to reduce overfitting. Based on our enlarged database and standard databases, a large dataset of 73200 records and a small one of 1849 records are built up to verify our proposal. Results show SADA\u27s effectiveness in predicting labels and increments in the sensitivity of DNNs by 14.4% compared with existing domain adaptation algorithms

    Design and Implementation of a Low‐Power Wireless Respiration Monitoring Sensor

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    Wireless devices for monitoring of respiration activities can play a major role in advancing modern home-based health care applications. Existing methods for respiration monitoring require special algorithms and high precision filters to eliminate noise and other motion artifacts. These necessitate additional power consuming circuitry for further signal conditioning. This dissertation is particularly focused on a novel approach of respiration monitoring based on a PVDF-based pyroelectric transducer. Low-power, low-noise, and fully integrated charge amplifiers are designed to serve as the front-end amplifier of the sensor to efficiently convert the charge generated by the transducer into a proportional voltage signal. To transmit the respiration data wirelessly, a lowpower transmitter design is crucial. This energy constraint motivates the exploration of the design of a duty-cycled transmitter, where the radio is designed to be turned off most of the time and turned on only for a short duration of time. Due to its inherent duty-cycled nature, impulse radio ultra-wideband (IR-UWB) transmitter is an ideal candidate for the implementation of a duty-cycled radio. To achieve better energy efficiency and longer battery lifetime a low-power low-complexity OOK (on-off keying) based impulse radio ultra-wideband (IR-UWB) transmitter is designed and implemented using standard CMOS process. Initial simulation and test results exhibit a promising advancement towards the development of an energy-efficient wireless sensor for monitoring of respiration activities

    Wireless body sensor networks for health-monitoring applications

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    This is an author-created, un-copyedited version of an article accepted for publication in Physiological Measurement. The publisher is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record is available online at http://dx.doi.org/10.1088/0967-3334/29/11/R01

    A lightweight sensing platform for monitoring sleep quality and posture: a simulated validation study

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    Background The prevalence of self-reported shoulder pain in the UK has been estimated at 16%. This has been linked with significant sleep disturbance. It is possible that this relationship is bidirectional, with both symptoms capable of causing the other. Within the field of sleep monitoring, there is a requirement for a mobile and unobtrusive device capable of monitoring sleep posture and quality. This study investigates the feasibility of a wearable sleep system (WSS) in accurately detecting sleeping posture and physical activity. Methods Sixteen healthy subjects were recruited and fitted with three wearable inertial sensors on the trunk and forearms. Ten participants were entered into a ‘Posture’ protocol; assuming a series of common sleeping postures in a simulated bedroom. Five participants completed an ‘Activity’ protocol, in which a triphasic simulated sleep was performed including awake, sleep and REM phases. A combined sleep posture and activity protocol was then conducted as a ‘Proof of Concept’ model. Data were used to train a posture detection algorithm, and added to activity to predict sleep phase. Classification accuracy of the WSS was measured during the simulations. Results The WSS was found to have an overall accuracy of 99.5% in detection of four major postures, and 92.5% in the detection of eight minor postures. Prediction of sleep phase using activity measurements was accurate in 97.3% of the simulations. The ability of the system to accurately detect both posture and activity enabled the design of a conceptual layout for a user-friendly tablet application. Conclusions The study presents a pervasive wearable sensor platform, which can accurately detect both sleeping posture and activity in non-specialised environments. The extent and accuracy of sleep metrics available advances the current state-of-the-art technology. This has potential diagnostic implications in musculoskeletal pathology and with the addition of alerts may provide therapeutic value in a range of areas including the prevention of pressure sores

    Bio-Radar Applications for Remote Vital Signs Monitoring

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    Nowadays, most vital signs monitoring techniques used in a medical context and/or daily life routines require direct contact with skin, which can become uncomfortable or even impractical to be used regularly. Radar technology has been appointed as one of the most promising contactless tools to overcome these hurdles. However, there is a lack of studies that cover a comprehensive assessment of this technology when applied in real-world environments. This dissertation aims to study radar technology for remote vital signs monitoring, more specifically, in respiratory and heartbeat sensing. Two off-the-shelf radars, based on impulse radio ultra-wideband and frequency modu lated continuous wave technology, were customized to be used in a small proof of concept experiment with 10 healthy participants. Each subject was monitored with both radars at three different distances for two distinct conditions: breathing and voluntary apnea. Signals processing algorithms were developed to detect and estimate respiratory and heartbeat parameters, assessed using qualitative and quantitative methods. Concerning respiration, a minimum error of 1.6% was found when radar respiratory peaks signals were directly compared with their reference, whereas a minimum mean absolute error of 0.3 RPM was obtained for the respiration rate. Concerning heartbeats, their expression in radar signals was not as clear as the respiration ones, however a minimum mean absolute error of 1.8 BPM for heartbeat was achieved after applying a novel selective algorithm developed to validate if heart rate value was estimated with reliability. The results proved the potential for radars to be used in respiratory and heartbeat contactless sensing, showing that the employed methods can be already used in some mo tionless situations. Notwithstanding, further work is required to improve the developed algorithms in order to obtain more robust and accurate systems.Atualmente, a maioria das tĂ©cnicas usadas para a monitorização de sinais vitais em contexto mĂ©dicos e/ou diĂĄrio requer contacto direto com a pele, o que poderĂĄ tornar-se incĂłmodo ou atĂ© mesmo inviĂĄvel em certas situaçÔes. A tecnologia radar tem vindo a ser apontada como uma das mais promissoras ferramentas para medição de sinais vitais Ă  distĂąncia e sem contacto. Todavia, sĂŁo necessĂĄrios mais estudos que permitam avaliar esta tecnologia quando aplicada a situaçÔes mais reais. Esta dissertação tem como objetivo o estudo da tecnologia radar aplicada no contexto de medição remota de sinais vitais, mais concretamente, na medição de atividade respiratĂłria e cardĂ­aca. Dois aparelhos radar, baseados em tecnologia banda ultra larga por rĂĄdio de impulso e em tecnologia de onda continua modulada por frequĂȘncia, foram configurados e usados numa prova de conceito com 10 participantes. Cada sujeito foi monitorizado com cada um dos radar em duas situaçÔes distintas: respirando e em apneia voluntĂĄria. Algorit mos de processamento de sinal foram desenvolvidos para detetar e estimar parĂąmetros respiratĂłrios e cardĂ­acos, avaliados atravĂ©s de mĂ©todos qualitativos e quantitativos. Em relação Ă  respiração, o menor erro obtido foi de 1,6% quando os sinais de radar respiratĂłrios foram comparados diretamente com os sinais de referĂȘncia, enquanto que, um erro mĂ©dio absoluto mĂ­nimo de 0,3 RPM foi obtido para a estimação da frequĂȘncia respiratĂłria via radar. A expressĂŁo cardĂ­aca nos sinais radar nĂŁo se revelou tĂŁo evidente como a respiratĂłria, no entanto, um erro mĂ©dio absoluto mĂ­nimo de 1,8 BPM foi obtido para a estimação da frequĂȘncia cardĂ­aca apĂłs a aplicação de um novo algoritmo seletivo, desenvolvido para validar a confiança dos valores obtidos. Os resultados obtidos provaram o potencial do uso de radares na medição de atividade respiratĂłria e cardĂ­aca sem contacto, sendo esta tecnologia viĂĄvel de ser implementada em situaçÔes onde nĂŁo existe muito movimento. NĂŁo obstante, os algoritmos desenvolvidos devem ser aperfeiçoados no futuro de forma a obter sistemas mais robustos e precisos

    An Ultrasonic Contactless Sensor for Breathing Monitoring

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    International audienceThe monitoring of human breathing activity during a long period has multiple fundamental applications in medicine. In breathing sleep disorders such as apnea, the diagnosis is based on events during which the person stops breathing for several periods during sleep. In polysomnography, the standard for sleep disordered breathing analysis, chest movement and airflow are used to monitor the respiratory activity. However, this method has serious drawbacks. Indeed, as the subject should sleep overnight in a laboratory and because of sensors being in direct contact with him, artifacts modifying sleep quality are often observed. This work investigates an analysis of the viability of an ultrasonic device to quantify the breathing activity, without contact and without any perception by the subject. Based on a low power ultrasonic active source and transducer, the device measures the frequency shift produced by the velocity difference between the exhaled air flow and the ambient environment, i.e., the Doppler effect. After acquisition and digitization, a specific signal processing is applied to separate the effects of breath from those due to subject movements from the Doppler signal. The distance between the source and the sensor, about 50 cm, and the use of ultrasound frequency well above audible frequencies, 40 kHz, allow monitoring the breathing activity without any perception by the subject, and therefore without any modification of the sleep quality which is very important for sleep disorders diagnostic applications. This work is patented (patent pending 2013-7-31 number FR.13/57569). OPE

    Contact and remote breathing rate monitoring techniques: a review

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    ABSTRACT: Breathing rate monitoring is a must for hospitalized patients with the current coronavirus disease 2019 (COVID-19). We review in this paper recent implementations of breathing monitoring techniques, where both contact and remote approaches are presented. It is known that with non-contact monitoring, the patient is not tied to an instrument, which improves patients’ comfort and enhances the accuracy of extracted breathing activity, since the distress generated by a contact device is avoided. Remote breathing monitoring allows screening people infected with COVID-19 by detecting abnormal respiratory patterns. However, non-contact methods show some disadvantages such as the higher set-up complexity compared to contact ones. On the other hand, many reported contact methods are mainly implemented using discrete components. While, numerous integrated solutions have been reported for non-contact techniques, such as continuous wave (CW) Doppler radar and ultrawideband (UWB) pulsed radar. These radar chips are discussed and their measured performances are summarized and compared

    Wellness, Fitness, and Lifestyle Sensing Applications

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