A physical approach to the automated classification of clinical percussion sounds

Pantea, M. A.; Maev, Roman Gr.; Malyarenko, Eugene; Baylor, Alfred E.

doi:10.1121/1.3665985

Cited by 11 publications

(10 citation statements)

References 24 publications

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“…Since first computer-aided studies of percussion sounds [23] new approaches to computerized analysis biophysical processes involved in percussion chest vibrations [24] as well as detection of lesions in the lung [25] and pleura [26] came into study. A physical approach to chest percussion demonstrated a clinical value [27,28].…”

Section: Forced Vibrationsmentioning

confidence: 99%

Biophysics of Chest Vibrations

Dyachenko¹

2017

J Apl Theol

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The purpose of this mini-review is to outline diversity of chest wall vibrations, specify biomechanical peculiarities and point out a few problems crucial for development of diagnostic and therapeutic applications of chest wall vibrations. The review considers two types of chest wall vibrations: spontaneous, induced by breathing, and forced (or artificial), induced by external vibration forces. Spontaneous vibrations emerge in airways and lung tissues due to vortexes, flatter and stress relaxation in pulmonary parenchyma. The vibrations propagate in lung to the chest wall and could be registered by a stethoscope at the chest wall surface as respiratory sounds. Another type of vibrations emerges due to heart contraction and become apparent at the chest wall surface as heart sounds. Respiratory and heart sounds are used for diagnostics of respiratory and heart diseases. Computerized respiratory sounds analysis (CRSA) is a new technique emerged last years and based on respiratory acoustics and biomedical engineering. Forced vibrations are the lung and chest wall vibrations induced by external vibrations effecting airways orifice and/or chest wall. Diagnostic and therapeutic forced vibrations differ in both frequency and amplitude. Diagnostic vibrations imposed at the airway orifice include forced oscillatory technique, estimation of airway cross-section by analysis of acoustic pulse response measurements. Stress and deformation oscillations used for diagnostic techniques usually are small to avoid any mechanical nonlinearity. Diagnostic vibrations imposed at the chest surface include a special kind of forced oscillatory technique with pressure oscillation around the entire chest and a technique of percussions imposed locally to the areas of interest on the chest wall. Elastic waves propagate in airways, pulmonary parenchyma and chest wall during vibrations. Peculiarities of elastic waves propagation in these structures are discussed. A high sound or low ultrasound window presents new emerging perspective area for biomedical engineering aimed to develop a technique for lung sound/ultrasound imaging. There are a few kinds of therapeutic forced vibrations aimed to enhance airway sputum removal if the production of sputum is too large due to decease.

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Section: Forced Vibrationsmentioning

confidence: 99%

Biophysics of Chest Vibrations

Dyachenko¹

2017

J Apl Theol

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“…The majority of preceding work attempting the objective classification of percussion sounds is based on the timedomain and Fourier spectral analysis [2,4]. Spectral peaks correspond to individual oscillation modes, while their width is a direct measure of damping.…”

Section: Introductionmentioning

confidence: 99%

Time-Frequency Analysis of Clinical Percussion Signals Using Matrix Pencil Method

Bhuiyan

Malyarenko²,

Pantea

et al. 2015

Journal of Electrical and Computer Engineering

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This paper discusses time-frequency analysis of clinical percussion signals produced by tapping over human chest or abdomen with a neurological hammer and recorded with an air microphone. The analysis of short, highly damped percussion signals using conventional time-frequency distributions (TFDs) meets certain difficulties, such as poor time-frequency localization, cross terms, and masking of the lower energy features by the higher energy ones. The above shortcomings lead to inaccurate and ambiguous representation of the signal behavior in the time-frequency plane. This work describes an attempt to construct a TF representation specifically tailored to clinical percussion signals to achieve better resolution of individual components corresponding to physical oscillation modes. Matrix Pencil Method (MPM) is used to decompose the signal into a set of exponentially damped sinusoids, which are then plotted in the time-frequency plane. Such representation provides better visualization of the signal structure than the commonly used frequency-amplitude plots and facilitates tracking subtle changes in the signal for diagnostic purposes. The performance of our approach has been verified on both ideal and real percussion signals. The MPM-based time-frequency analysis appears to be a better choice for clinical percussion signals than conventional TFDs, while its ability to visualize damping has immediate practical applications.

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“…The nature of medical percussions presents a few obvious initial choices. The harmonic nature of percussive signals has been analysed in previous studies [6]- [8] and EDS decompositions have been used in the past to exploit this.…”

Section: Atomic Dictionariesmentioning

confidence: 99%

“…Non-linear spectral fitting procedures have been able to approximate various percussions using 1-3 damped harmonics. Unfortunately, these types of fits are difficult to implement with automated procedures due to the complexity of the method and the requirement for semi-empirical fitting parameters to be used [6]. The Matrix Pencil Method (MPM) has also be shown to be a method capable of decomposing percussions into a sum of EDS components that is much more resilient to noise than spectral fitting procedures and is an easily automated algorithm [7].…”

Section: Introductionmentioning

confidence: 99%

“…The majority of the preceding work attempting to objectively classify percussion sounds is based on Fourier analysis methods [5]. Previous investigations by our group [6]- [8] have shown that medical percussion signals are well suited to decomposition into a sum of exponentially damped sinusoids (EDS). Non-linear spectral fitting procedures have been able to approximate various percussions using 1-3 damped harmonics.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of Clinical Percussion Signals Using Matching Pursuit

Dech¹,

Bhuiyan²,

Gr³

2015

IJCEE

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Abstract:Clinical percussion is a method of eliciting sounds from the body by tapping with either a percussion hammer or fingers to determine the area under the perused is air filled, fluid filled, or solid, and is used in clinical examinations to assess the condition of the thorax or abdomen. Successful diagnosis today is still highly subjective and dependent's on physician skill, experience and require quite surrounding areas. An automated system capable of delivering standardized percussion analysis would remove these limitations on the technique and allow for its usage by those without such specialized training and years of necessary experience. For this to be possible, efficient and informative signal processing algorithms must be employed. In this investigation, clinical percussions from healthy volunteers taken by trained medical professionals were analysed via the matching pursuit (MP) algorithm. Various types of possible dictionaries are discussed comparing their efficiency and convergence behaviour. Noise filtering methods are discussed and a noise reduction method based on MP analysis results is presented.MP is also compared to other methods for representing clinical percussions with regards to informativeness and efficiency. MP is ( log ) which is more efficient than current methods which have a complexity of at least ( 3 ).

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A physical approach to the automated classification of clinical percussion sounds

Cited by 11 publications

References 24 publications

Biophysics of Chest Vibrations

Biophysics of Chest Vibrations

Time-Frequency Analysis of Clinical Percussion Signals Using Matrix Pencil Method

Analysis of Clinical Percussion Signals Using Matching Pursuit

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