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Auscultation of the lung is an inexpensive, noninvasive and easy-to-perform tool. It is an important part of the physical examination and is help ful to distinguish physiological respiratory sounds from pathophysiological events. Computerized lung sound analysis is a powerful tool for optimizing and quantifying electronic auscultation based on the specific lung sound spectral characteristics. The automatic analysis of respiratory sounds assumes that physiological and pathological sounds are reliably analyzed based on special algorithms. The development of automated long-term lungsound monitors enables objective assessment of different respiratory symptoms., (© Georg Thieme Verlag KG Stuttgart · New York.)

Particularly in young children the diagnosis of asthma is difficult and mostly based on clinical symptoms like wheezing, cough and dyspnea. Children with nocturnal wheezing often suffer from a low quality of sleep and impaired sense of well-being during the day. Physicians recommend that parents record the frequency of asthma attacks or symptoms to help manage their children's disease. The lack of an appropriate method for standardized and objective monitoring makes asthma management difficult. The aim of this paper is to present a new method for automated wheeze and cough detection and analysis. The mobile LEOSound recording and analysing system described here should help improve diagnosis and monitoring of asthma symptoms in children., (© Georg Thieme Verlag KG Stuttgart · New York.)

A portable system for auscultation and lung sound analysis has been developed, including the original electronic stethoscope coupled with mobile devices and special algorithms for the automated analysis of pulmonary sound signals. It's planned that the developed system will be used for monitoring of health status of patients with various pulmonary diseases.

Automatic detection of pig wasting diseases is an important issue in the management of group-housed pigs. Further, respiratory diseases are one of the main causes of mortality among pigs and loss of productivity in intensive pig farming. In this study, we propose an efficient data mining solution for the detection and recognition of pig wasting diseases using sound data in audio surveillance systems. In this method, we extract the Mel Frequency Cepstrum Coefficients (MFCC) from sound data with an automatic pig sound acquisition process, and use a hierarchical two-level structure: the Support Vector Data Description (SVDD) and the Sparse Representation Classifier (SRC) as an early anomaly detector and a respiratory disease classifier, respectively. Our experimental results show that this new method can be used to detect pig wasting diseases both economically (even a cheap microphone can be used) and accurately (94% detection and 91% classification accuracy), either as a standalone solution or to complement known methods to obtain a more accurate solution.

Background: Respiratory flow detection with the aim of detecting sleep-related breathing disorders plays a major role in polysomnography. Due to the fact that pneumotachographs are too bulky and not suitable for measurements during sleep, the ThorAKUSTIK system has been developed. By attaching a noise sensor right next to larynx, it determines the respiratory flow in an acoustic way., Methods: The ThorAKUSTIK system as well as a pneumotachograph were applied simultaneously. The correlation between those two methods has been calculated., Patients: We investigated twenty male subjects. All of them were non-smokers., Results: The ThorAKUSTIK-System showed a highly positive correlation (r = 0.89 to 0.91; p < 0.01) and was able to measure the respiratory flow in a reliable way., Conclusions: The ThorAKUSTIK-System allows a long-term live monitoring and has the potential to be used in several clinical departments. Larger studies are necessary to verify the application in the clinical routine., (© Georg Thieme Verlag KG Stuttgart · New York.)

This study proposes a novel interface for sensing swallowing activities (based on the sound produced when swallowing) that is mounted on the back of the neck. Recently, owing to the aging of the population, the number of dysphagia patients has been increasing. Although various types of diacrisis and dysphagia testing methodologies already exist, several problems remain. For example, the videofluorography methodology requires extensive preparation; it presents risks of aspiration and demands knowledge about diacrisis, and it must be performed in a medical facility. This study introduces a wearable sensing system that can be used in daily life. As it gives direct, real-time information regarding swallowing movements, this device is also aimed at being used for rehabilitation purposes. The proposed system uses a new evaluation technique that is based on the duration of the swallowing action.

Background: Cough is one of the main symptoms of advanced lung disease. However, the efficacy of currently available treatment remains unsatisfactory. Research into the new antitussives requires an objective assessment of cough., Methods: The aim of the study was to test the feasibility of a new automatic portable cough analyser and assess the correlation between subjective and objective evaluations of cough in 13 patients with chronic cough. The patients' individual histories, a cough symptom score and a numeric cough scale (1-10) were used as a subjective evaluation of cough and a computerized audio-timed recorder was used to measure the frequency of coughing., Results: The pre-clinical validation has shown that an automated cough analyser is an accurate and reliable tool for the ambulatory assessment of chronic cough. In the clinical part of the experiment for the daytime, subjective cough scoring correlated with the number of all cough incidents recorded by the cough analyser (r = 0.63; p = 0.022) and the number of cough incidents per hour (r = 0.60; p = 0.03). However, there was no relation between cough score and the time spent coughing per hour (r = 0.48; p = 0.1). As assessed for the night-time period, no correlation was found between subjective cough scoring and the number of incidents per hour (r = 0.29; p = 0.34) or time spent coughing (r = 0.26; p = 0.4)., Conclusion: An automated cough analyser seems to be a feasible tool for the ambulatory monitoring of cough. There is a moderate correlation between subjective and objective assessments of cough during the daytime, whereas the discrepancy in the evaluation of night-time coughing might suggest that subjective analysis is unreliable.

Cough is considered an early sign of many respiratory diseases. Recently, there has been increased interest in measuring, analyzing, and characterizing the acoustical properties of a cough. In most cases the main focus of those studies was to distinguish between involuntary coughs and ambient sounds over a specified time period. The objective of this study was to develop a system to measure high fidelity voluntary cough sounds to detect lung diseases. To further augment the analysis capability of the system, a non-invasive flow measurement was also incorporated into the design. One of the main design considerations was to increase the fidelity of the recorded sound characteristics by increasing the signal to noise ratio of cough sounds and to minimize acoustical reflections from the environment. To accomplish this goal, a system was designed with a mouthpiece connected to a cylindrical tube. A microphone was attached near the mouthpiece so that its diaphragm was tangent to the inner surface of the cylinder. A pneumotach at the end of the tube measured the airflow generated by the cough. The system was terminated with an exponential horn to minimize sound reflections. Custom software was developed to read, process, display, record, and analyze cough sound and airflow characteristics. The system was optimized by comparing acoustical reflections and total signal to background noise ratios across different designs. Cough measurements were also collected from volunteer subjects to assess the viability of the system. Results indicate that analysis of cough characteristics has the potential to detect lung disease.

Background: Distinction between normal and abnormal respiratory sounds is important for accurate diagnosis., Current Data: This paper describes the state of the art, scientific publications and ongoing research related to the respiratory sounds. The study includes a description of the various techniques that are being used to record auscultatory sounds and a physical description of known pathological sounds (wheezes and crackles) for which automatic detection tools have been developed., Viewpoints: The next stage will include exploiting all the qualities of the sounds. This augmentation of the spectrum studied, linked to signal analysis techniques, will allow the definition of new characteristic markers.

It is now widely accepted that crackles are associated with different pulmonary pathologies and different efforts have been done to detect and to extract them. Consequently, due to the difficulty for their characterization, the selection of an adequate time-frequency representation (TFR) for the analysis of their time-frequency dynamics is important. Traditionally, normal and abnormal lung sounds have been analyzed by the Spectrogram (SP). However, this analysis tool has certain disadvantages when one deals with nonstationary signals. As an effort to point out the appropriate analysis tool for crackles, this paper shows the performance of the Hilbert-Huang spectrum (HHS) for the analysis of fine and coarse crackles, simulated and real ones. The HHS allowed to analyze the evolving time-frequency of crackle sounds straightforward with good resolution compared with SP. Beside this enhanced time-frequency course, HHS could be useful to establish a signature to detect and separate fine from coarse crackles in order to screen pathologies and their progress during medication.

This paper analyzes the main challenges associated with noninvasive, continuous, wearable, and long-term breathing monitoring. The characteristics of an acoustic breathing signal from a miniature sensor are studied in the presence of sources of noise and interference artifacts that affect the signal. Based on these results, an algorithm has been devised to detect breathing. It is possible to implement the algorithm on a single integrated circuit, making it suitable for a miniature sensor device. The algorithm is tested in the presence of noise sources on five subjects and shows an average success rate of 91.3% (combined true positives and true negatives).

The objective monitoring of cough for extended periods of time has long been recognized as an important step towards a better understanding of this symptom, and a better management of chronic cough patients. In this paper, we present a system for the automatic analysis of 24-h, continuous, ambulatory recordings of cough. The system uses audio recordings from a miniature microphone and the detection algorithm is based on statistical models of the time-spectral characteristics of cough sounds. We validated the system against manual counts obtained by a trained observer on 40 ambulatory recordings and our results show a median sensitivity value of 85.7%, median positive predictive value of 94.7% and median false positive rate of 0.8 events/h. An analysis application was developed, with a graphical user interface, allowing the use of the system in clinical settings by technical or medical staff. The result of the analysis of a recording session is presented as a concise, graphical-based report. The modular nature of the system interface facilitates its enhancement with the integration of further modules.

Changes in normal lung sounds are an important sign of pathophysiological processes in the bronchial system and lung tissue. For the diagnosis of bronchial asthma, coughing and wheezing are important symptoms that indicate the existence of obstruction. In particular, nocturnal long-term acoustic monitoring and assessment make sense for qualitative and quantitative detection and documentation. Previous methods used for lung function diagnosis require active patient cooperation that is not possible during sleep. We developed a mobile device based on the CORSA standard that allows the recording of respiratory sounds throughout the night. To date, we have recorded 133 patients with different diagnoses (80 male, 53 female), of whom 38 were children. In 68 of the patients we could detect cough events and in 87 we detected wheezing. The recording method was tolerated by all participating adults and children. Our mobile system allows non-invasive and cooperation-independent nocturnal monitoring of acoustic symptoms in the domestic environment, especially at night, when most ailments occur.

We evaluated the acoustic frequency response of endotracheal tubes (ETs) to assess their effect on respiratory system sound transmission studies. White noise 150-3300 Hz was introduced into 4.0-, 6.0-, and 8.0-mm ETs and recorded at their proximal and distal ends. Four tubes of each size were studied at their original and normalized lengths, in straight and bent configurations, and at circuit pressures from 0 to 20 cmH2O. The characteristics of the sound transmission were compared using an analysis of variance for repeated measures. The average transmission amplitude varied directly with tube diameter. The position of peaks and troughs on the amplitude frequency distribution depended on tube length but not on tube diameter. The angle of the phase-frequency plot correlated well with the length of the tube and was independent of its diameter. A 90 degrees bend in the tube had no effect on its sound transmission. Increasing the circuit pressure above ambient modified the frequency response only if volume changes occurred in the test lung. When used to conduct sound into the respiratory system an ET affects the incident signal predictably depending on its length and diameter but not on its curvature or circuit pressure.

Recent advances in sensor technology for muscle activity monitoring have resulted in the development of a coupled microphone-accelerometer sensor pair for physiological acousti signal recording. This sensor can be used to eliminate interfering sources in practical settings where the contamination of an acoustic signal by ambient noise confounds detection but cannot be easily removed [e.g., mechanomyography (MMG), swallowing sounds, respiration, and heart sounds]. This paper presents a mathematical model for the coupled microphone-accelerometer vibration sensor pair, specifically applied to muscle activity monitoring (i.e., MMG) and noise discrimination in externally powered prostheses for below-elbow amputees. While the model provides a simple and reliable source separation technique for MMG signals, it can also be easily adapted to other aplications where the recording of low-frequency (< 1 kHz) physiological vibration signals is required.

Transorbital sound recordings were obtained from 21 patients with intracranial tumours, 28 patients with intracranial aneurysms and 20 control patients. The group of patients with tumours consisted of 12 patients with gliomas, of whom 6 had low-grade gliomas and 6 had high-grade gliomas, and 9 patients with meningiomas. All patients with gliomas, including the subgroup of patients with low-grade gliomas, as well as patients with aneurysms, had significantly different sound recordings in comparison to control patients. Recordings from glioma patients did not differ significantly from recordings of aneurysm patients. Radiological evaluation of the tumours was performed in order to establish which tumour characteristics were associated with abnormal sound recordings. It was found that the type of tumour, i.e., histology or malignancy grade, was a significant associated factor, whereas other tumour characteristics such as size, mass effect and amount of oedema were not. In conclusion, patients with specific types of intracranial tumours produced abnormal sounds which could not be distinguished from abnormal sounds recorded in patients with aneurysms. These results may be important for the interpretation of sounds recorded for the detection of intracranial pathology, especially for aneurysm screening.

TMJ clicking sound is a sign worth noticing as prodromal symptoms of TMJ dysfunction. Therefore, a solution of its characteristics is an important matter to grasp the diagnosis of stomatognathic function and progress of the disease. We try to systematize the procedure from picking-up TMJ sound to convertion of frequency and then investigate picking-up method and the measurement apparatus, because we need a quantitation of acoustical components of clicking sound to examine the influence of hearing ability due to TMJ dysfunction. The following were obtained: 1. Low frequency noise is reduced by using headgear with microphone located in a external ear. 2. We pick up continuous 30 TMJ sounds three times in separate days. The waveforms of each set are approximately similar. 3. Each peak frequency and pattern of power spectrum examined three times show high correspondence. 4. The range of maximum peak frequencies in all subjects are from 0 to 0.8 KHz.