289 research outputs found
Motion Artifact Reduction in Impedance Plethysmography Signal
The research related to designing portable monitoring devices for physiological signals has been at its peak in the last decade or two. One of the main obstacles in building such devices is the effect of the subject\u27s movements on the quality of the signal. There have been numerous studies addressing the problem of removing motion artifact from the electrocardiogram (ECG) and photoplethysmography (PPG) signals in the past few years. However, no such study exists for the Impedance Plethysmography (IP) signal. The IP signal can be used to monitor respiration in mobile devices. However, it is very susceptible to motion artifact. The main aim of this dissertation is to develop adaptive and non-adaptive filtering algorithms to address the problem of motion artifact reduction from the IP signal
Novel Methods for Weak Physiological Parameters Monitoring.
M.S. Thesis. University of HawaiÊ»i at MÄnoa 2017
The feasibility of the Emfit movement sensor as an automated screening tool for sleep apnea in the ischemic stroke patients
Stroke is a common cause of death and a major reason for disability. Stroke survivors can have very difficult symptoms and require very intensive and expensive rehabilitation. Sleep disordered breathing, sleep apnea, is common among stroke patients, it's a high risk factor for recurrent stroke and untreated sleep apnea has a negative influence on the stroke recovery.
All stroke patients are recommended to be measured for sleep apnea, but the lack of resources don't allow it. Therefore there is a need for a screening tool to find the stroke patients who need the measurement most and who benefit the most of the treatment of the sleep apnea.
We studied the possibility to use the Emfit movement sensor combined with a pulse oximeter as a screening tool. The Emfit movement sensor doesn't have connections to the patient, therefore it wouldn't require lots of resources to set up the measurement and there are no contacts that can cause interference during the measurement. The automatic scoring of the measurement would remove the need for an expert to manually score every measurement.
The test subjects were measured at the same night using both the Emfit movement sensor and a conventional respiratory polygraphy device. The Emfit movement sensor and the standard respiratory polygraphy measurements were scored using Noxturnal's automatic analysis tool and the results were compared. The results were also compared to the manual scoring of the standard respiratory polygraphy.
The Emfit movement sensor measurement slightly overestimates the apnea hypopnea index, as does the automatically scored standard respiratory polygraphy too. The automatic analysis ability to detect correctly the duration and timing of a respiratory event in the Emfit movement sensor measurement seems to depend on the amount of noise in the measurement. Our study indicates that the Emfit movement sensor has potential to be used as a screening tool for sleep apnea in the ischemic stroke patients, but the automatic analysis still needs improvements to provide more accurate results
NASA contributions to - Cardiovascular monitoring
NASA contributions to cardiovasular monitorin
Adding liveness detection to the hand geometry scanner
In today\u27s dynamic society, the efficiency of the Biometric Systems has an increasing tendency to replace the classic but obsolete keys and passwords. Hand Geometry Readers are popular biometrics used for Access and Control applications. One of their weaknesses is vulnerability to spoofing using fake hands (latex, play-doh or dead-hands).;The objective of this thesis is to design a feature to be added to the Hand Geometry Scanner in order to detect vitality in the hand, reducing spoofing possibilities.;This thesis demonstrates how the Hand Reader was successfully spoofed and shows the implementation of the live detection feature through an inexpensive but efficient electronic design.;The method used for detection is Photo-Plethysmography. The Reflectance Sensor built is of original conception. After amplifying, filtering and processing the sensor\u27s signal, a message is displayed onto an LCD, concerning the liveness of the hand and the pulse rate
Assessment of trends in the cardiovascular system from time interval measurements using physiological signals obtained at the limbs
Cardiovascular diseases are an increasing source of concern in modern societies due to their increasing prevalence and high impact on the lives of many people. Monitoring cardiovascular parameters in ambulatory scenarios is an emerging approach that can provide better medical access to patients while decreasing the costs associated to the treatment of these diseases.
This work analyzes systems and methods to measure time intervals between the electrocardiogram (ECG), impedance plethysmogram (IPG), and the ballistocardiogram (BCG), which can be obtained at the limbs in ambulatory scenarios using simple and cost-effective systems, to assess cardiovascular intervals of interest, such as the pulse arrival time (PAT), pulse transit time (PTT), or the pre-ejection period (PEP).
The first section of this thesis analyzes the impact of the signal acquisition system on the uncertainty in timing measurements in order to establish the design specifications for systems intended for that purpose. The minimal requirements found are not very demanding yet some common signal acquisition systems do not fulfill all of them while other capabilities typically found in signal acquisition systems could be downgraded without worsening the timing uncertainty. This section is also devoted to the design of systems intended for timing measurements in ambulatory scenarios according to the specifications previously established. The systems presented have evolved from the current state-of-the-art and are designed for adequate performance in timing measurements with a minimal number of active components.
The second section is focused on the measurement of time intervals from the IPG measured from limb to limb, which is a signal that until now has only been used to monitor heart rate. A model to estimate the contributions to the time events in the measured waveform of the different body segments along the current path from geometrical properties of the large arteries is proposed, and the simulation under blood pressure changes suggests that the signal is sensitive to changes in proximal sites of the current path rather than in distal sites. Experimental results show that the PAT to the hand-to-hand IPG, which is obtained from a novel four-electrode handheld system, is correlated to changes in the PEP whereas the PAT to the foot-to-foot IPG shows good performance in assessing changes in the femoral PAT. Therefore, limb-to-limb IPG measurements significantly increase the number of time intervals of interest that can be measured at the limbs since the signals deliver information from proximal sites complementary to that of other measurements typically performed at distal sites.
The next section is devoted to the measurement of time intervals that involve different waves of the BCG obtained in a standing platform and whose origin is still under discussion. From the relative timing of other physiological signals, it is hypothesized that the IJ interval of the BCG is sensitive to variations in the PTT. Experimental results show that the BCG I wave is a better surrogate of the cardiac ejection time than the widely-used J wave, which is also supported by the good correlation found between the IJ interval and the aortic PTT. Finally, the novel time interval from the BCG I wave to the foot of the IPG measured between feet, which can be obtained from the same bathroom scale than the BCG, shows good performance in assessing the aortic PAT. The results presented reinforce the role of the BCG as a tool for ambulatory monitoring since the main time intervals targeted in this thesis can be obtained from the timing of its waves.
Even though the methods described were tested in a small group of subjects, the results presented in this work show the feasibility and potential of several time interval measurements between the proposed signals that can be performed in ambulatory scenarios, provided the systems intended for that purpose fulfill some minimal design requirements.Les malalties cardiovasculars sĂłn una tema de preocupaciĂł creixent en societats modernes, degut a lâaugment de la seva prevalença i l'elevat impacte en les vides dels pacients que les sofreixen. La mesura i monitoratge de parĂ metres cardiovasculars en entorns ambulatoris Ă©s una prĂ ctica emergent que facilita lâaccĂ©s als serveis mĂšdics i permet reduir drĂ sticament els costos associats al tractament d'aquestes malalties. En aquest treball sâanalitzen sistemes i mĂštodes per la mesura dâintervals temporals entre lâelectrocardiograma (ECG), el pletismograma dâimpedĂ ncia (IPG) i el balistocardiograma (BCG), que es poden obtenir de les extremitats i en entorns ambulatoris a partir de sistemes de baix cost, per tal dâavaluar intervals cardiovasculars dâinterĂšs com el pulse arrival time (PAT), pulse transit time (PTT) o el pre-ejection period (PEP). En la primera secciĂł d'aquesta tesi sâanalitza lâimpacte del sistema dâadquisiciĂł del senyal en la incertesa de mesures temporals, per tal dâestablir els requeriments mĂnims que sâhan de complir en entorns ambulatoris. Tot i que els valors obtinguts de lâanĂ lisi no sĂłn especialment exigents, alguns no sĂłn assolits en diversos sistemes habitualment utilitzats mentre que altres solen estar sobredimensionats i es podrien degradar sense augmentar la incertesa en mesures temporals. Aquesta secciĂł tambĂ© inclou el disseny i proposta de sistemes per la mesura dâintervals en entorns ambulatoris dâacord amb les especificacions anteriorment establertes, a partir de lâestat de lâart i amb lâobjectiu de garantir un correcte funcionament en entorns ambulatoris amb un nombre mĂnim dâelements actius per reduir el cost i el consum. La segona secciĂł es centra en la mesura dâintervals temporals a partir de lâIPG mesurat entre extremitats, que fins al moment nomĂ©s sâha fet servir per mesurar el ritme cardĂac. Es proposa un model per estimar la contribuciĂł de cada segment arterial per on circula el corrent a la forma dâona obtinguda a partir de la geometria i propietats fĂsiques de les artĂšries, i les simulacions suggereixen que la senyal entre extremitats Ă©s mĂ©s sensible a canvis en arteries proximals que en distals. Els resultats experimentals mostren que el PAT al hand-to-hand IPG, obtingut a partir dâun innovador sistema handheld de quatre elĂšctrodes, estĂ fortament correlacionat amb els canvis de PEP, mentre que el PAT al foot-to-foot IPG estĂ correlat amb els canvis en PAT femoral. ConseqĂŒentment, lâILG entre extremitats augmenta de manera significativa els intervals dâinterĂšs que es poden obtenir en extremitats degut a que proporciona informaciĂł complementĂ ria a les mesures que habitualment sâhi realitzen. La tercera secciĂł estĂ dedicada a la mesura dâintervals que inclouen les ones del BCG vertical obtingut en plataformes, de les que encara seân discuteix lâorigen. A partir de la posiciĂł temporal relativa respecte altres ones fisiolĂČgiques, sâhipostatitza que lâinterval IJ del BCG es sensible a variacions del PTT. Els resultats experimentals mostren que la ona I del BCG Ă©s un millor indicador de lâejecciĂł cardĂaca que el pic J, tot i que aquest Ă©s el mĂ©s utilitzat habitualment, degut a la bona correlaciĂł entre lâinterval IJ i el PTT aĂČrtic. Finalment, es presenta un mĂštode alternatiu per la mesura del PTT aĂČrtic a partir de lâinterval entre el pic I del BCG i el peu del foot-to-foot IPG, que es pot obtenir de la mateixa plataforma que el BCG i incrementa la robustesa de la mesura. Els resultats presentats reforcen el paper del BCG com a en mesures en entorns ambulatoris, ja que els principals intervals objectiu dâaquesta tesi es poden obtenir a partir de les seves ones. Tot i que els mĂštodes descrits han estat provats en grups petits de subjectes saludables, els resultats mostren la viabilitat i el potencial de diversos intervals temporals entre les senyals proposades que poden Ă©sser realitzats en entorns ambulatoris, sempre que els sistemes emprats compleixin els requisits mĂnims de disseny.Postprint (published version
Advanced sensors technology survey
This project assesses the state-of-the-art in advanced or 'smart' sensors technology for NASA Life Sciences research applications with an emphasis on those sensors with potential applications on the space station freedom (SSF). The objectives are: (1) to conduct literature reviews on relevant advanced sensor technology; (2) to interview various scientists and engineers in industry, academia, and government who are knowledgeable on this topic; (3) to provide viewpoints and opinions regarding the potential applications of this technology on the SSF; and (4) to provide summary charts of relevant technologies and centers where these technologies are being developed
Characterization and processing of novel neck photoplethysmography signals for cardiorespiratory monitoring
Epilepsy is a neurological disorder causing serious brain seizures that severely affect the patients' quality of life. Sudden unexpected death in epilepsy (SUDEP), for which no evident decease reason is found after post-mortem examination, is a common cause of mortality. The mechanisms leading to SUDEP are uncertain, but, centrally mediated apneic respiratory dysfunction, inducing dangerous hypoxemia, plays a key role. Continuous physiological monitoring appears as the only reliable solution for SUDEP prevention. However, current seizure-detection systems do not show enough sensitivity and present a high number of intolerable false alarms. A wearable system capable of measuring several physiological signals from the same body location, could efficiently overcome these limitations. In this framework, a neck wearable apnea detection device (WADD), sensing airflow through tracheal sounds, was designed. Despite the promising performance, it is still necessary to integrate an oximeter sensor into the system, to measure oxygen saturation in blood (SpO2) from neck photoplethysmography (PPG) signals, and hence, support the apnea detection decision.
The neck is a novel PPG measurement site that has not yet been thoroughly explored, due to numerous challenges. This research work aims to characterize neck PPG signals, in order to fully exploit this alternative pulse oximetry location, for precise cardiorespiratory biomarkers monitoring.
In this thesis, neck PPG signals were recorded, for the first time in literature, in a series of experiments under different artifacts and respiratory conditions. Morphological and spectral characteristics were analyzed in order to identify potential singularities of the signals. The most common neck PPG artifacts critically corrupting the signal quality, and other breathing states of interest, were thoroughly characterized in terms of the most discriminative features. An algorithm was further developed to differentiate artifacts from clean PPG signals. Both, the proposed characterization and classification model can be useful tools for researchers to denoise neck PPG signals and exploit them in a variety of clinical contexts. In addition to that, it was demonstrated that the neck also offered the possibility, unlike other body parts, to extract the Jugular Venous Pulse (JVP) non-invasively.
Overall, the thesis showed how the neck could be an optimum location for multi-modal monitoring in the context of diseases affecting respiration, since it not only allows the sensing of airflow related signals, but also, the breathing frequency component of the PPG appeared more prominent than in the standard finger location. In this context, this property enabled the extraction of relevant features to develop a promising algorithm for apnea detection in near-real time.
These findings could be of great importance for SUDEP prevention, facilitating the investigation of the mechanisms and risk factors associated to it, and ultimately reduce epilepsy mortality.Open Acces
Adaptive motion artefact reduction in respiration and ECG signals for wearable healthcare monitoring systems
Wearable healthcare monitoring systems (WHMSs) have received significant interest from both academia and industry with the advantage of non-intrusive and ambulatory monitoring. The aim of this paper is to investigate the use of an adaptive filter to reduce motion artefact (MA) in physiological signals acquired by WHMSs. In our study, a WHMS is used to acquire ECG, respiration and triaxial accelerometer (ACC) signals during incremental treadmill and cycle ergometry exercises. With these signals, performances of adaptive MA cancellation are evaluated in both respiration and ECG signals. To achieve effective and robust MA cancellation, three axial outputs of the ACC are employed to estimate the MA by a bank of gradient adaptive Laguerre lattice (GALL) filter, and the outputs of the GALL filters are further combined with time-varying weights determined by a Kalman filter. The results show that for the respiratory signals, MA component can be reduced and signal quality can be improved effectively (the power ratio between the MA-corrupted respiratory signal and the adaptive filtered signal was 1.31 in running condition, and the corresponding signal quality was improved from 0.77 to 0.96). Combination of the GALL and Kalman filters can achieve robust MA cancellation without supervised selection of the reference axis from the ACC. For ECG, the MA component can also be reduced by adaptive filtering. The signal quality, however, could not be improved substantially just by the adaptive filter with the ACC outputs as the reference signals.Municipal Science & Technology Commission. Beijing Natural Science Foundation (Grants 3102028 and 3122034)General Logistics Science Foundation (Grant CWS11C108)National Institutes of Health (U.S.) (National Institute of General Medical Sciences (U.S.). Grant R01- EB001659)National Institutes of Health (U.S.) (National Institute for Biomedical Imaging and Bioengineering (U.S.) Cooperative Agreement U01- EB-008577
Multidimensional embedded MEMS motion detectors for wearable mechanocardiography and 4D medical imaging
Background: Cardiovascular diseases are the number one cause of death. Of these deaths, almost 80% are due to coronary artery disease (CAD) and cerebrovascular disease. Multidimensional microelectromechanical systems (MEMS) sensors allow measuring the mechanical movement of the heart muscle offering an entirely new and innovative solution to evaluate cardiac rhythm and function. Recent advances in miniaturized motion sensors present an exciting opportunity to study novel device-driven and functional motion detection systems in the areas of both cardiac monitoring and biomedical imaging, for example, in computed tomography (CT) and positron emission tomography (PET).
Methods: This Ph.D. work describes a new cardiac motion detection paradigm and measurement technology based on multimodal measuring tools â by tracking the heartâs kinetic activity using micro-sized MEMS sensors â and novel computational approaches â by deploying signal processing and machine learning techniquesâfor detecting cardiac pathological disorders. In particular, this study focuses on the capability of joint gyrocardiography (GCG) and seismocardiography (SCG) techniques that constitute the mechanocardiography (MCG) concept representing the mechanical characteristics of the cardiac precordial surface vibrations.
Results: Experimental analyses showed that integrating multisource sensory data resulted in precise estimation of heart rate with an accuracy of 99% (healthy, n=29), detection of heart arrhythmia (n=435) with an accuracy of 95-97%, ischemic disease indication with approximately 75% accuracy (n=22), as well as significantly improved quality of four-dimensional (4D) cardiac PET images by eliminating motion related inaccuracies using MEMS dual gating approach. Tissue Doppler imaging (TDI) analysis of GCG (healthy, n=9) showed promising results for measuring the cardiac timing intervals and myocardial deformation changes.
Conclusion: The findings of this study demonstrate clinical potential of MEMS motion sensors in cardiology that may facilitate in time diagnosis of cardiac abnormalities. Multidimensional MCG can effectively contribute to detecting atrial fibrillation (AFib), myocardial infarction (MI), and CAD. Additionally, MEMS motion sensing improves the reliability and quality of cardiac PET imaging.Moniulotteisten sulautettujen MEMS-liiketunnistimien kÀyttö sydÀnkardiografiassa sekÀ lÀÀketieteellisessÀ 4D-kuvantamisessa
Tausta: SydÀn- ja verisuonitaudit ovat yleisin kuolinsyy. NÀistÀ kuolemantapauksista lÀhes 80% johtuu sepelvaltimotaudista (CAD) ja aivoverenkierron hÀiriöistÀ. Moniulotteiset mikroelektromekaaniset jÀrjestelmÀt (MEMS) mahdollistavat sydÀnlihaksen mekaanisen liikkeen mittaamisen, mikÀ puolestaan tarjoaa tÀysin uudenlaisen ja innovatiivisen ratkaisun sydÀmen rytmin ja toiminnan arvioimiseksi. Viimeaikaiset teknologiset edistysaskeleet mahdollistavat uusien pienikokoisten liiketunnistusjÀrjestelmien kÀyttÀmisen sydÀmen toiminnan tutkimuksessa sekÀ lÀÀketieteellisen kuvantamisen, kuten esimerkiksi tietokonetomografian (CT) ja positroniemissiotomografian (PET), tarkkuuden parantamisessa.
MenetelmÀt: TÀmÀ vÀitöskirjatyö esittelee uuden sydÀmen kineettisen toiminnan mittaustekniikan, joka pohjautuu MEMS-anturien kÀyttöön. Uudet laskennalliset lÀhestymistavat, jotka perustuvat signaalinkÀsittelyyn ja koneoppimiseen, mahdollistavat sydÀmen patologisten hÀiriöiden havaitsemisen MEMS-antureista saatavista signaaleista. TÀssÀ tutkimuksessa keskitytÀÀn erityisesti mekanokardiografiaan (MCG), joihin kuuluvat gyrokardiografia (GCG) ja seismokardiografia (SCG). NÀiden tekniikoiden avulla voidaan mitata kardiorespiratorisen jÀrjestelmÀn mekaanisia ominaisuuksia.
Tulokset: Kokeelliset analyysit osoittivat, ettÀ integroimalla usean sensorin dataa voidaan mitata syketiheyttÀ 99% (terveillÀ n=29) tarkkuudella, havaita sydÀmen rytmihÀiriöt (n=435) 95-97%, tarkkuudella, sekÀ havaita iskeeminen sairaus noin 75% tarkkuudella (n=22). LisÀksi MEMS-kaksoistahdistuksen avulla voidaan parantaa sydÀmen 4D PET-kuvan laatua, kun liikeepÀtarkkuudet voidaan eliminoida paremmin. Doppler-kuvantamisessa (TDI, Tissue Doppler Imaging) GCG-analyysi (terveillÀ, n=9) osoitti lupaavia tuloksia sydÀnsykkeen ajoituksen ja intervallien sekÀ sydÀnlihasmuutosten mittaamisessa.
PÀÀtelmÀ: TÀmÀn tutkimuksen tulokset osoittavat, ettÀ kardiologisilla MEMS-liikeantureilla on kliinistÀ potentiaalia sydÀmen toiminnallisten poikkeavuuksien diagnostisoinnissa. Moniuloitteinen MCG voi edistÀÀ eteisvÀrinÀn (AFib), sydÀninfarktin (MI) ja CAD:n havaitsemista. LisÀksi MEMS-liiketunnistus parantaa sydÀmen PET-kuvantamisen luotettavuutta ja laatua
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