14 research outputs found
Respiratory Sound Analysis for the Evidence of Lung Health
Significant changes have been made on audio-based technologies over years in several different fields along with healthcare industry. Analysis of Lung sounds is a potential source of noninvasive, quantitative information along with additional objective on the status of the pulmonary system. To do that medical professionals listen to sounds heard over the chest wall at different positions with a stethoscope which is known as auscultation and is important in diagnosing respiratory diseases. At times, possibility of inaccurate interpretation of respiratory sounds happens because of clinician’s lack of considerable expertise or sometimes trainees such as interns and residents misidentify respiratory sounds. We have built a tool to distinguish healthy respiratory sound from non-healthy ones that come from respiratory infection carrying patients. The audio clips were characterized using Linear Predictive Cepstral Coefficient (LPCC)-based features and the highest possible accuracy of 99.22% was obtained with a Multi-Layer Perceptron (MLP)- based classifier on the publicly available ICBHI17 respiratory sounds dataset [1] of size 6800+ clips. The system also outperformed established works in literature and other machine learning techniques. In future we will try to use larger dataset with other acoustic techniques along with deep learning-based approaches and try to identify the nature and severity of infection using respiratory sounds
Measurement and analysis of breath sounds
Existing breath sound measurement systems and possible new methods have been critically investigated. The frequency response of each part of the measurement system has been studied. Emphasis has been placed on frequency response of acoustic sensors; especially, a method to study a diaphragm type air-coupler in contact use has been proposed. Two new methods of breath sounds measurement have been studied: laser Doppler vibrometer and mobile phones. It has been shown that these two methods can find applications in breath sounds measurement, however there are some restrictions.
A reliable automatic wheeze detection algorithm based on auditory modelling has been developed. That is the human’s auditory system is modelled as a bank of band pass filters, in which the bandwidths are frequency dependent. Wheezes are treated as signals additive to normal breath sounds (masker). Thus wheeze is detectable when it is above the masking threshold. This new algorithm has been validated using simulated and real data. It is superior to previous algorithms, being more reliable to detect wheezes and less prone to mistakes.
Simulation of cardiorespiratory sounds and wheeze audibility tests have been developed. Simulated breath sounds can be used as a training tool, as well as an evaluation method. These simulations have shown that, under certain circumstance, there are wheezes but they are inaudible. It is postulated that this could also happen in real measurements. It has been shown that simulated sounds with predefined characteristics can be used as an objective method to evaluate automatic algorithms.
Finally, the efficiency and necessity of heart sounds reduction procedures has been investigated. Based on wavelet decomposition and selective synthesis, heart sounds can be reduced with a cost of unnatural breath sounds. Heart sound reduction is shown not to be necessary if a time-frequency representation is used, as heart sounds have a fixed pattern in the time-frequency plane
Multichannel analysis of normal and continuous adventitious respiratory sounds for the assessment of pulmonary function in respiratory diseases
Premi extraordinari doctorat UPC curs 2015-2016, àmbit d’Enginyeria IndustrialRespiratory sounds (RS) are produced by turbulent airflows through the airways and are
inhomogeneously transmitted through different media to the chest surface, where they can be recorded
in a non-invasive way. Due to their mechanical nature and airflow dependence, RS are affected by
respiratory diseases that alter the mechanical properties of the respiratory system. Therefore, RS provide
useful clinical information about the respiratory system structure and functioning.
Recent advances in sensors and signal processing techniques have made RS analysis a more objective
and sensitive tool for measuring pulmonary function. However, RS analysis is still rarely used in clinical
practice. Lack of a standard methodology for recording and processing RS has led to several different
approaches to RS analysis, with some methodological issues that could limit the potential of RS analysis
in clinical practice (i.e., measurements with a low number of sensors, no controlled airflows, constant
airflows, or forced expiratory manoeuvres, the lack of a co-analysis of different types of RS, or the use
of inaccurate techniques for processing RS signals).
In this thesis, we propose a novel integrated approach to RS analysis that includes a multichannel
recording of RS using a maximum of five microphones placed over the trachea and the chest surface,
which allows RS to be analysed at the most commonly reported lung regions, without requiring a large
number of sensors. Our approach also includes a progressive respiratory manoeuvres with variable
airflow, which allows RS to be analysed depending on airflow. Dual RS analyses of both normal RS
and continuous adventitious sounds (CAS) are also proposed. Normal RS are analysed through the RS
intensity–airflow curves, whereas CAS are analysed through a customised Hilbert spectrum (HS),
adapted to RS signal characteristics.
The proposed HS represents a step forward in the analysis of CAS. Using HS allows CAS to be fully
characterised with regard to duration, mean frequency, and intensity. Further, the high temporal and
frequency resolutions, and the high concentrations of energy of this improved version of HS, allow CAS
to be more accurately characterised with our HS than by using spectrogram, which has been the most
widely used technique for CAS analysis.
Our approach to RS analysis was put into clinical practice by launching two studies in the Pulmonary
Function Testing Laboratory of the Germans Trias i Pujol University Hospital for assessing pulmonary
function in patients with unilateral phrenic paralysis (UPP), and bronchodilator response (BDR) in
patients with asthma. RS and airflow signals were recorded in 10 patients with UPP, 50 patients with
asthma, and 20 healthy participants.
The analysis of RS intensity–airflow curves proved to be a successful method to detect UPP, since we
found significant differences between these curves at the posterior base of the lungs in all patients whereas no differences were found in the healthy participants. To the best of our knowledge, this is the
first study that uses a quantitative analysis of RS for assessing UPP.
Regarding asthma, we found appreciable changes in the RS intensity–airflow curves and CAS features
after bronchodilation in patients with negative BDR in spirometry. Therefore, we suggest that the
combined analysis of RS intensity–airflow curves and CAS features—including number, duration, mean
frequency, and intensity—seems to be a promising technique for assessing BDR and improving the
stratification of BDR levels, particularly among patients with negative BDR in spirometry.
The novel approach to RS analysis developed in this thesis provides a sensitive tool to obtain objective
and complementary information about pulmonary function in a simple and non-invasive way. Together
with spirometry, this approach to RS analysis could have a direct clinical application for improving the
assessment of pulmonary function in patients with respiratory diseases.Los sonidos respiratorios (SR) se generan con el paso del flujo de aire a través de las vías respiratorias y se transmiten de forma no homogénea hasta la superficie torácica. Dada su naturaleza mecánica, los SR se ven afectados en gran medida por enfermedades que alteran las propiedades mecánicas del sistema respiratorio. Por lo tanto, los SR proporcionan información clínica relevante sobre la estructura y el funcionamiento del sistema respiratorio. La falta de una metodología estándar para el registro y procesado de los SR ha dado lugar a la aparición de diferentes estrategias de análisis de SR con ciertas limitaciones metodológicas que podrían haber restringido el potencial y el uso de esta técnica en la práctica clínica (medidas con pocos sensores, flujos no controlados o constantes y/o maniobras forzadas, análisis no combinado de distintos tipos de SR o uso de técnicas poco precisas para el procesado de los SR). En esta tesis proponemos un método innovador e integrado de análisis de SR que incluye el registro multicanal de SR mediante un máximo de cinco micrófonos colocados sobre la tráquea yla superficie torácica, los cuales permiten analizar los SR en las principales regiones pulmonares sin utilizar un número elevado de sensores . Nuestro método también incluye una maniobra respiratoria progresiva con flujo variable que permite analizar los SR en función del flujo respiratorio. También proponemos el análisis combinado de los SR normales y los sonidos adventicios continuos (SAC), mediante las curvas intensidad-flujo y un espectro de Hilbert (EH) adaptado a las características de los SR, respectivamente. El EH propuesto representa un avance importante en el análisis de los SAC, pues permite su completa caracterización en términos de duración, frecuencia media e intensidad. Además, la alta resolución temporal y frecuencial y la alta concentración de energía de esta versión mejorada del EH permiten caracterizar los SAC de forma más precisa que utilizando el espectrograma, el cual ha sido la técnica más utilizada para el análisis de SAC en estudios previos. Nuestro método de análisis de SR se trasladó a la práctica clínica a través de dos estudios que se iniciaron en el laboratorio de pruebas funcionales del hospital Germans Trias i Pujol, para la evaluación de la función pulmonar en pacientes con parálisis frénica unilateral (PFU) y la respuesta broncodilatadora (RBD) en pacientes con asma. Las señales de SR y flujo respiratorio se registraron en 10 pacientes con PFU, 50 pacientes con asma y 20 controles sanos. El análisis de las curvas intensidad-flujo resultó ser un método apropiado para detectar la PFU , pues encontramos diferencias significativas entre las curvas intensidad-flujo de las bases posteriores de los pulmones en todos los pacientes , mientras que en los controles sanos no encontramos diferencias significativas. Hasta donde sabemos, este es el primer estudio que utiliza el análisis cuantitativo de los SR para evaluar la PFU. En cuanto al asma, encontramos cambios relevantes en las curvas intensidad-flujo yen las características de los SAC tras la broncodilatación en pacientes con RBD negativa en la espirometría. Por lo tanto, sugerimos que el análisis combinado de las curvas intensidad-flujo y las características de los SAC, incluyendo número, duración, frecuencia media e intensidad, es una técnica prometedora para la evaluación de la RBD y la mejora en la estratificación de los distintos niveles de RBD, especialmente en pacientes con RBD negativa en la espirometría. El método innovador de análisis de SR que se propone en esta tesis proporciona una nueva herramienta con una alta sensibilidad para obtener información objetiva y complementaria sobre la función pulmonar de una forma sencilla y no invasiva. Junto con la espirometría, este método puede tener una aplicación clínica directa en la mejora de la evaluación de la función pulmonar en pacientes con enfermedades respiratoriasAward-winningPostprint (published version
Discrimination between healthy subjects and patients with pulmonary emphysema by detection of abnormal respiration
In this paper, we propose a robust classification strategy for distinguishing between a healthy subject and a patient with pulmonary emphysema on the basis of lung sounds. A symptom of pulmonary emphysema is that almost all lung sounds include some abnormal (i.e., adventitious) sounds. However, the great variety of possible adventitious sounds and noises at auscultation makes high-accuracy detection difficult. To overcome this difficulty, our strategy is to adopt a two-step classification approach based on the detection of "confident abnormal respiration." In the first step, hidden Markov models and bigram models are used for acoustic features and the occurrence of acoustic segments in each abnormal respiratory period, respectively, to calculate two kinds of stochastic likelihoods: the highest likelihood for a segment sequence to be abnormal respiration and the likelihood for normal respiration. In the second step, the patients are identified on the basis of the detection of confident abnormal respiration, which is when difference between these two likelihoods is larger than a predefined threshold. Our strategy achieved the highest classification rate of 88.7% between healthy subjects and patients among three basic classification strategies, which shows the validity of our approach.ICASSP 2011 - 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) : Prague, Czech Republic, 2011.05.22-2011.05.2
Algoritmos de procesado de señal basados en Non-negative Matrix Factorization aplicados a la separación, detección y clasificación de sibilancias en señales de audio respiratorias monocanal
La auscultación es el primer examen clínico que un médico lleva a cabo para evaluar el estado del sistema respiratorio, debido a que es un método no invasivo, de bajo coste, fácil de realizar y seguro para el paciente. Sin embargo, el diagnóstico que se deriva de la auscultación sigue siendo un diagnóstico subjetivo que se encuentra condicionado a la habilidad, experiencia y entrenamiento de cada médico en la escucha e interpretación de las señales de audio respiratorias. En consecuencia, se producen un alto porcentaje de diagnósticos erróneos que ponen en riesgo la salud de los pacientes e incrementan el coste asociado a los centros de salud. Esta Tesis propone nuevos métodos basados en Non-negative Matrix Factorization aplicados a la separación, detección y clasificación de sonidos sibilantes para proporcionar una vía de información complementaria al médico que ayude a mejorar la fiabilidad del diagnóstico emitido por el especialista. Auscultation is the first clinical examination that a physician performs to evaluate the condition of the respiratory system, because it is a non-invasive, low-cost, easy-to-perform and safe method for the patient. However, the diagnosis derived from auscultation remains a subjective diagnosis that is conditioned by the ability, experience and training of each physician in the listening and interpretation of respiratory audio signals. As a result, a high percentage of misdiagnoses are produced that endanger the health of patients and increase the cost associated with health centres. This Thesis proposes new methods based on Non-negative Matrix Factorization applied to separation, detection and classification of wheezing sounds in order to provide a complementary information pathway to the physician that helps to improve the reliability of the diagnosis made by the doctor.Tesis Univ. Jaén. Departamento INGENIERÍA DE TELECOMUNICACIÓ
A framework for automated heart and lung sound analysis using a mobile telemedicine platform
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 246-261).Many resource-poor communities across the globe lack access to quality healthcare,due to shortages in medical expertise and poor availability of medical diagnostic devices. In recent years, mobile phones have become increasingly complex and ubiquitous. These devices present a tremendous opportunity to provide low-cost diagnostics to under-served populations and to connect non-experts with experts. This thesis explores the capture of cardiac and respiratory sounds on a mobile phone for analysis, with the long-term aim of developing intelligent algorithms for the detection of heart and respiratory-related problems. Using standard labeled databases, existing and novel algorithms are developed to analyze cardiac and respiratory audio data. In order to assess the algorithms' performance under field conditions, a low-cost stethoscope attachment is constructed and data is collected using a mobile phone. Finally, a telemedicine infrastructure and work-flow is described, in which these algorithms can be deployed and trained in a large-scale deployment.by Katherine L. Kuan.M.Eng
Microfluidic methods for single cell analysis in clinically relevant samples
Single cell protein analysis has the potential to comprehensively profile cellular
heterogeneity advancing the understanding of cell function, disease progression and drug
development. Although it is a possible contributor to the discovery of novel therapy, the protein
mapping on the individual cell basis is complex and poses challenges. For example, cancer is
a heterogeneous disease which analysis using conventional bulk methods can potentially
conceal a dangerous population like Circulating Tumour Cells (CTCs). Analysis of CTCs can
only be reliably attained using single cell technologies. The Microfluidic Affinity Capture
(MAC) chip is a tool that was developed in our group to study cellular heterogeneity by
measuring protein abundance in single cells. Another problem in analysing cancer cells is the
difficulty in obtaining samples in a non-invasive manner. This thesis reports on attempts to
obtain, concentrate and analyse CTCs from blood using a composite MAC-based device.
The ability to analyse single cells has advantages beyond the potential for analysing
heterogeneity. Chronic Obstructive Pulmonary Disease (COPD) is a heterogeneous illness that
is characterised by a chronic inflammation. Although the immune response in COPD requires
investigation, it is complicated by a lack of biomarkers and methods to non-invasively collect
samples. The ability to obtain and effectively analyse precious and scarce biomaterial from
lungs, is greatly advantageous for both diagnosis and tracking of COPD. Here, we report on a
workflow to achieve this using sputum from negative control volunteers and COPD+ patients.
Also, we describe the establishment of a novel MAC chip assay targeting FOXO3 protein
which is involved in regulation of processes like tumour suppression, inflammation and
senescence. Therefore, it has a biomarker potential to monitor and study diseases like cancer
and COPD. We developed the protocol to analyse Forkhead box 3 (FOXO3) protein expression
in nasal cells from healthy donor samples that were retrieved with a non-invasive tool
(NASAM, nasal synthetic absorptive matrix). Nasal cavity is a front line of exposure to inhaled
pernicious substances and, it is speculated to reflect anomalous bioprocesses in lungs preceding
respiratory disease development and progression. This study provides the first-time
quantification of FOXO3 protein in single cells from nasal samples. This work shows the
analytical capacity of the MAC chip to study cellular heterogeneity and quantify important
biomarkers in single cells of clinically relevant material.Open Acces
Occupational respiratory diseases
Shipping list no.: 87-222-P."September 1986."S/N 017-033-00425-1 Item 499-F-2Also available via the World Wide Web.Includes bibliographies and index
Designing sound : procedural audio research based on the book by Andy Farnell
In
procedural
media,
data
normally
acquired
by
measuring
something,
commonly
described
as
sampling,
is
replaced
by
a
set
of
computational
rules
(procedure)
that
defines
the
typical
structure
and/or
behaviour
of
that
thing.
Here,
a
general
approach
to
sound
as
a
definable
process,
rather
than
a
recording,
is
developed.
By
analysis
of
their
physical
and
perceptual
qualities,
natural
objects
or
processes
that
produce
sound
are
modelled
by
digital
Sounding
Objects
for
use
in
arts
and
entertainments.
This
Thesis
discusses
different
aspects
of
Procedural
Audio
introducing
several
new
approaches
and
solutions
to
this
emerging
field
of
Sound
Design.Em
Media
Procedimental,
os
dados
os
dados
normalmente
adquiridos
através
da
medição
de
algo
habitualmente
designado
como
amostragem,
são
substituídos
por
um
conjunto
de
regras
computacionais
(procedimento)
que
definem
a
estrutura
típica,
ou
comportamento,
desse
elemento.
Neste
caso
é
desenvolvida
uma
abordagem
ao
som
definível
como
um
procedimento
em
vez
de
uma
gravação.
Através
da
análise
das
suas
características
físicas
e
perceptuais
,
objetos
naturais
ou
processos
que
produzem
som,
são
modelados
como
objetos
sonoros
digitais
para
utilização
nas
Artes
e
Entretenimento.
Nesta
Tese
são
discutidos
diferentes
aspectos
de
Áudio
Procedimental,
sendo
introduzidas
várias
novas
abordagens
e
soluções
para
o
campo
emergente
do
Design
Sonoro