New developments in the objective assessment of cough

Acoustic Analysis of Voluntary Coughs, Throat Clearings, and Induced Reflexive Coughs in a Healthy Population

Cough efficacy is considered a reliable predictor of the aspiration risk in head and neck cancer patients with radiation-associated dysphagia. Currently, coughing is assessed perceptually or aerodynamically. The goal of our research is to develop methods of acoustic cough analysis. In this study, we examined in a healthy population the acoustical differences between three protective maneuvers: voluntary cough, voluntary throat clearing, and induced reflexive cough. Forty healthy participants were included in this study. Voluntary cough, voluntary throat clearing, and reflexive cough samples were recorded and analyzed acoustically. Temporal acoustic features were the following: the slope and curvature of the amplitude contour, as well as the average, slope, and curvature of the sample entropy and kurtosis contours of the recorded signal. Spectral features were the relative energy in the frequency bands (0-400 Hz, 400-800 Hz, 800-1600 Hz, 1600 Hz-3200 Hz, > 3200 Hz) as well as the weighted spectral energy. Results showed that, compared to a voluntary cough, a throat clearing starts with a weaker onset pulse and involves oscillations from the onset to the offset (concave curvature of the amplitude contour, p < 0.05), lower average (p < 0.05), and slope (p < 0.05) as well as lower convex curvature (p < 0.05) of the kurtosis contour. An induced reflexive cough starts with a higher and briefer onset burst and includes higher frication noise (larger convexity of the curvature of the amplitude and kurtosis contours (p < 0.05)) compared to a voluntary cough. The conclusion is that voluntary coughs are acoustically significantly different from voluntary throat clearings and induced reflexive coughs.

Therapeutic principles and unmet needs in the treatment of cough in pediatric patients: review and expert survey

BACKGROUND

There are evidence gaps in the management of pediatric cough, particularly for acute pediatric cough. This study had two aims: to identify therapeutic principles and unmet needs in the treatment of cough in pediatric patients (internationally), and to consider the evidence required to address these unmet needs.

METHODS

A MEDLINE/PubMed database search was performed to identify articles describing therapeutic principles in the treatment of pediatric cough. An online survey of international pediatric cough experts was conducted, with questions on the definitions, diagnosis, treatment, and unmet needs in pediatric cough management.

RESULTS

Cough guidelines have differing definitions of pediatric patients (≤12-18 years), acute pediatric cough (< 2-3 weeks), and chronic pediatric cough (> 4-8 weeks). Similarly, among 18 experts surveyed, definitions varied for pediatric patients (≤10-21 years), acute pediatric cough (< 3-5 days to < 6 weeks), and chronic pediatric cough (> 2-8 weeks). Guidelines generally do not recommend over-the-counter or prescription cough medicines in acute pediatric cough, due to lack of evidence. In the expert survey, participants had differing opinions on which medicines were most suitable for treating acute pediatric cough, and noted that effective treatments are lacking for cough-related pain and sleep disruption. Overall, guidelines and experts agreed that chronic pediatric cough requires diagnostic investigations to identify the underlying cough-causing disease and thereby to guide treatment. There are unmet needs for new effective and safe treatments for acute pediatric cough, and for randomized controlled trials of existing treatments. Safety is a particular concern in this vulnerable patient population. There is also a need for better understanding of the causes, phenotypes, and prevalence of pediatric cough, and how this relates to its diagnosis and treatment.

CONCLUSIONS

Whereas pediatric cough guidelines largely align with regard to the diagnosis and treatment of chronic cough, there is limited evidence-based guidance for the management of acute cough. There is a need for harmonization of pediatric cough management, and the development of standard guidelines suitable for all regions and patient circumstances.

Enabling effective breathing sound analysis for automated diagnosis of lung diseases

With the emergence of the COVID-19 pandemic, early diagnosis of lung diseases has attracted growing attention. Generally, monitoring the breathing sound is the traditional means for assessing the status of a patient's respiratory health through auscultation; for that a stethoscope is one of the clinical tools used by physicians for diagnosis of lung disease and anomalies. On the other hand, recent technological advances have made telehealth systems a practical and effective option for health status assessment and remote patient monitoring. The interest in telehealth solutions have further grown with the COVID-19 pandemic. These telehealth systems aim to provide increased safety and help to cope with the massive growth in healthcare demand. Particularly, employing acoustic sensors to collect breathing sound would enable real-time assessment and instantaneous detection of anomalies. However, existing work focuses on autonomous determination of respiratory rate which is not suitable for anomaly detection due to inability to deal with noisy data recording. This paper presents a novel approach for effective breathing sound analysis. We promote a new segmentation mechanism of the captured acoustic signals to identify breathing cycles in recorded sound signals. A scoring scheme is applied to qualify the segment based on the targeted respiratory illness by the overall breathing sound analysis. We demonstrate the effectiveness of our approach via experiments using published COPD datasets.

Making cough count in tuberculosis care

Cough assessment is central to the clinical management of respiratory diseases, including tuberculosis (TB), but strategies to objectively and unobtrusively measure cough are lacking. Acoustic epidemiology is an emerging field that uses technology to detect cough sounds and analyze cough patterns to improve health outcomes among people with respiratory conditions linked to cough. This field is increasingly exploring the potential of artificial intelligence (AI) for more advanced applications, such as analyzing cough sounds as a biomarker for disease screening. While much of the data are preliminary, objective cough assessment could potentially transform disease control programs, including TB, and support individual patient management. Here, we present an overview of recent advances in this field and describe how cough assessment, if validated, could support public health programs at various stages of the TB care cascade.

A new method for objectively evaluating nocturnal cough in adults

BACKGROUND

For the management of cough diseases in adults, an objective method of evaluating nocturnal cough is required.

METHODS

In Study 1, a cough monitoring system was evaluated using 25 adult volunteers. In Study 2, the cough monitoring system was validated using 20 samples from 10 adult patients with cough diseases obtained overnight. In hospitalized patients, our original cough monitoring system with a microphone and accelerometer was used. At the same time, coughs were recorded using a video camera with digital sound recording. The number of coughs in each 8-h video-audio recording was counted manually by three trained observers. All cough data were printed out, and the basal number of cough events, using both the printed-out data and video-audio recordings, were then calculated by three observers.

RESULTS

In Study 1, the cough monitoring system demonstrated good agreement with the number of coughs counted by examiners (sensitivity 99.2%, specificity 98.9%). In Study 2, there was significant agreement in the counts of natural coughs between our system and the video-audio method (p < 0.0001) and between our system and the basal cough events (p < 0.0001).

CONCLUSIONS

Our method demonstrated excellent agreement with the video-audio recording method in adults and is considered extremely useful for the objective monitoring of overnight cough in adult patients with cough diseases.

Past and Trends in Cough Sound Acquisition, Automatic Detection and Automatic Classification: A Comparative Review

Cough is a very common symptom and the most frequent reason for seeking medical advice. Optimized care goes inevitably through an adapted recording of this symptom and automatic processing. This study provides an updated exhaustive quantitative review of the field of cough sound acquisition, automatic detection in longer audio sequences and automatic classification of the nature or disease. Related studies were analyzed and metrics extracted and processed to create a quantitative characterization of the state-of-the-art and trends. A list of objective criteria was established to select a subset of the most complete detection studies in the perspective of deployment in clinical practice. One hundred and forty-four studies were short-listed, and a picture of the state-of-the-art technology is drawn. The trend shows an increasing number of classification studies, an increase of the dataset size, in part from crowdsourcing, a rapid increase of COVID-19 studies, the prevalence of smartphones and wearable sensors for the acquisition, and a rapid expansion of deep learning. Finally, a subset of 12 detection studies is identified as the most complete ones. An unequaled quantitative overview is presented. The field shows a remarkable dynamic, boosted by the research on COVID-19 diagnosis, and a perfect adaptation to mobile health.

Investigating the Relationship between Cough Detection and Sampling Frequency for Wearable Devices

Cough detection can provide an important marker to monitor chronic respiratory conditions. However, manual techniques which require human expertise to count coughs are both expensive and time-consuming. Recent Automatic Cough Detection Algorithms (ACDAs) have shown promise to meet clinical monitoring requirements, but only in recent years they have made their way to non-clinical settings due to the required portability of sensing technologies and the extended duration of data recording. More precisely, these ACDAs operate at high sampling frequencies, which leads to high power consumption and computing requirements, making these difficult to implement on a wearable device. Additionally, reproducibility of their performance is essential. Unfortunately, as the majority of ACDAs were developed using private clinical data, it is difficult to reproduce their results. We, hereby, present an ACDA that meets clinical monitoring requirements and reliably operates at a low sampling frequency. This ACDA is implemented using a convolutional neural network (CNN), and publicly available data. It achieves a sensitivity of 92.7%, a specificity of 92.3%, and an accuracy of 92.5% using a sampling frequency of just 750 Hz. We also show that a low sampling frequency allows us to preserve patients' privacy by obfuscating their speech, and we analyze the trade-off between speech obfuscation for privacy and cough detection accuracy.Clinical relevance-This paper presents a new cough detection technique and preliminary analysis on the trade-off between detection accuracy and obfuscation of speech for privacy. These findings indicate that, using a publicly available dataset, we can sample signals at 750 Hz while still maintaining a sensitivity above 90%, suggested to be sufficient for clinical monitoring [1].

Assessment of cough in head and neck cancer patients at risk for dysphagia-An overview

BACKGROUND

This literature review explores the terminology, the neurophysiology, and the assessment of cough in general, in the framework of dysphagia and regarding head and neck cancer patients at risk for dysphagia. In the dysphagic population, cough is currently assessed perceptually during a clinical swallowing evaluation or aerodynamically.

RECENT FINDINGS

Recent findings have shown intra and inter-rater disagreements regarding perceptual scoring of cough. Also, aerodynamic measurements are impractical in a routine bedside assessment. Coughing, however, is considered to be a clinically relevant sign of aspiration and dysphagia in head and cancer patients treated with concurrent chemoradiotherapy.

CONCLUSION

This article surveys the literature regarding the established cough assessment and stresses the need to implement innovative methods for assessing cough in head and neck cancer patients treated with concurrent chemoradiotherapy at risk for dysphagia.

A novel automatic cough frequency monitoring system combining a triaxial accelerometer and a stretchable strain sensor

Objective evaluations of cough frequency are considered important for assessing the clinical state of patients with respiratory diseases. However, cough monitors with audio recordings are rarely used in clinical settings. Issues regarding privacy and background noise with audio recordings are barriers to the wide use of these monitors; to solve these problems, we developed a novel automatic cough frequency monitoring system combining a triaxial accelerator and a stretchable strain sensor. Eleven healthy adult volunteers and 10 adult patients with cough were enrolled. The participants wore two devices for 30 min for the cough measurements. An accelerator was attached to the epigastric region, and a stretchable strain sensor was worn around their neck. When the subjects coughed, these devices displayed specific waveforms. The data from all the participants were categorized into a training dataset and a test dataset. Using a variational autoencoder, a machine learning algorithm with deep learning, the components of the test dataset were automatically judged as being a “cough unit” or “non-cough unit”. The sensitivity and specificity in detecting coughs were 92% and 96%, respectively. Our cough monitoring system has the potential to be widely used in clinical settings without any concerns regarding privacy or background noise.

The present and future of cough counting tools

The widespread use of cough counting tools has, to date, been limited by a reliance on human input to determine cough frequency. However, over the last two decades advances in digital technology and audio capture have reduced this dependence. As a result, cough frequency is increasingly recognised as a measurable parameter of respiratory disease. Cough frequency is now the gold standard primary endpoint for trials of new treatments for chronic cough, has been investigated as a marker of infectiousness in tuberculosis (TB), and used to demonstrate recovery in exacerbations of chronic obstructive pulmonary disease (COPD). This review discusses the principles of automatic cough detection and summarises key currently and recently used cough counting technology in clinical research. It additionally makes some predictions on future directions in the field based on recent developments. It seems likely that newer approaches to signal processing, the adoption of techniques from automatic speech recognition, and the widespread ownership of mobile devices will help drive forward the development of real-time fully automated ambulatory cough frequency monitoring over the coming years. These changes should allow cough counting systems to transition from their current status as a niche research tool in chronic cough to a much more widely applicable method for assessing, investigating and understanding respiratory disease.

Automatic Recognition, Segmentation, and Sex Assignment of Nocturnal Asthmatic Coughs and Cough Epochs in Smartphone Audio Recordings: Observational Field Study

Background

Asthma is one of the most prevalent chronic respiratory diseases. Despite increased investment in treatment, little progress has been made in the early recognition and treatment of asthma exacerbations over the last decade. Nocturnal cough monitoring may provide an opportunity to identify patients at risk for imminent exacerbations. Recently developed approaches enable smartphone-based cough monitoring. These approaches, however, have not undergone longitudinal overnight testing nor have they been specifically evaluated in the context of asthma. Also, the problem of distinguishing partner coughs from patient coughs when two or more people are sleeping in the same room using contact-free audio recordings remains unsolved.

Objective

The objective of this study was to evaluate the automatic recognition and segmentation of nocturnal asthmatic coughs and cough epochs in smartphone-based audio recordings that were collected in the field. We also aimed to distinguish partner coughs from patient coughs in contact-free audio recordings by classifying coughs based on sex.

Methods

We used a convolutional neural network model that we had developed in previous work for automated cough recognition. We further used techniques (such as ensemble learning, minibatch balancing, and thresholding) to address the imbalance in the data set. We evaluated the classifier in a classification task and a segmentation task. The cough-recognition classifier served as the basis for the cough-segmentation classifier from continuous audio recordings. We compared automated cough and cough-epoch counts to human-annotated cough and cough-epoch counts. We employed Gaussian mixture models to build a classifier for cough and cough-epoch signals based on sex.

Results

We recorded audio data from 94 adults with asthma (overall: mean 43 years; SD 16 years; female: 54/94, 57%; male 40/94, 43%). Audio data were recorded by each participant in their everyday environment using a smartphone placed next to their bed; recordings were made over a period of 28 nights. Out of 704,697 sounds, we identified 30,304 sounds as coughs. A total of 26,166 coughs occurred without a 2-second pause between coughs, yielding 8238 cough epochs. The ensemble classifier performed well with a Matthews correlation coefficient of 92% in a pure classification task and achieved comparable cough counts to that of human annotators in the segmentation of coughing. The count difference between automated and human-annotated coughs was a mean –0.1 (95% CI –12.11, 11.91) coughs. The count difference between automated and human-annotated cough epochs was a mean 0.24 (95% CI –3.67, 4.15) cough epochs. The Gaussian mixture model cough epoch–based sex classification performed best yielding an accuracy of 83%.

Conclusions

Our study showed longitudinal nocturnal cough and cough-epoch recognition from nightly recorded smartphone-based audio from adults with asthma. The model distinguishes partner cough from patient cough in contact-free recordings by identifying cough and cough-epoch signals that correspond to the sex of the patient. This research represents a step towards enabling passive and scalable cough monitoring for adults with asthma.

Discrimination between respiratory and non-respiratory sound waveforms in dogs using acoustic wave recordings: An objective metric of cough

Cough is an important respiratory protective mechanism, which when persistent also contributes to disease pathology. It is therefore both a marker for and a target of therapeutic intervention. In dogs, assessment of cough is subjective, generally based on owner's perceptions of clinical signs. In humans, acoustic cough monitoring provides objective data on cough frequency by examining acoustic waveforms. We hypothesized that healthy mesocephalic dogs would demonstrate characteristic cough waveforms which could be distinguished from other acoustic behaviors (AB); whine, bark, growl, lick, drink, chew and throat-clear. Data were obtained from 10 healthy employee-owned dogs. Acoustic behaviors were recorded using a CTA-laryngeal-microphone and analyzed using RavenPro bioacoustics software for nine objective acoustic parameters (AP). Similarity between AB were assessed using a one-way analysis of similarity (ANOSIM) with a P<0.001 significance level. Inter- and intra-group statistical analysis was performed using a one-way ANOVA on ranks with P<0.05 significance level. With the exception of throat-clear, cough was dissimilar to every other evaluated AB (P<0.0001), with significant differences in one or more of the analyzed waveform parameters (P<0.001 for each). No between-subject differences were identified between cough and throat-clear groups for any parameter. All other behaviors showed statistically significant within-group variation (P<0.001). Cough and throat-clear (a clinically similar mechanism to protect the airways) have repeatable acoustic features that are distinguishable from other common AB and are consistent between dogs. Acoustic monitoring may provide an objective means for evaluating cough frequency and intensity in dogs with respiratory disease and assessing response to therapeutic intervention.

A Machine Hearing System for Robust Cough Detection Based on a High-Level Representation of Band-Specific Audio Features

Cough is a protective reflex conveying information on the state of the respiratory system. Cough assessment has been limited so far to subjective measurement tools or uncomfortable (i.e., non-wearable) cough monitors. This limits the potential of real-time cough monitoring to improve respiratory care.

OBJECTIVE

This paper presents a machine hearing system for audio-based robust cough segmentation that can be easily deployed in mobile scenarios.

METHODS

Cough detection is performed in two steps. First, a short-term spectral feature set is separately computed in five predefined frequency bands: [0, 0.5), [0.5, 1), [1, 1.5), [1.5, 2), and [2, 5.5125] kHz. Feature selection and combination are then applied to make the short-term feature set robust enough in different noisy scenarios. Second, high-level data representation is achieved by computing the mean and standard deviation of short-term descriptors in 300 ms long-term frames. Finally, cough detection is carried out using a support vector machine trained with data from different noisy scenarios. The system is evaluated using a patient signal database which emulates three real-life scenarios in terms of noise content.

RESULTS

The system achieves 92.71% sensitivity, 88.58% specificity, and 90.69% Area Under Receiver Operating Charcteristic (ROC) curve (AUC), outperforming state-of-the-art methods.

CONCLUSION

Our research outcome paves the way to create a device for cough monitoring in real-life situations.

SIGNIFICANCE

Our proposal is aligned with a more comfortable and less disruptive patient monitoring, with benefits for patients (allows self-monitoring of cough symptoms), practitioners (e.g., assessment of treatments or better clinical understanding of cough patterns), and national health systems (by reducing hospitalizations).

Color spectrographic respiratory monitoring from the external ear canal

The need for simple and reliable means of respiratory monitoring has existed since the beginnings of medicine. In the present study, we describe the use of color spectrographic analysis of breathing sounds recorded from the external ear canal as a candidate technology to meet this need. A miniature electret microphone was modified with the addition of an adapter to allow it to be placed comfortably in the external ear canal. The amplified signal was then connected to a real-time color spectrogram program running on a laptop personal computer utilizing the Windows operating system. Based on the results obtained, we hypothesize that the real-time display of color spectrogram breathing patterns locally or at a central monitoring station may turn out to be a useful means of respiratory monitoring in patients at increased risk of respiratory depression or other respiratory problems. Finally, we conducted a statistical analysis that suggests that significant spectrogram differences may exist among some groups investigated in the study.

Efficient computation of image moments for robust cough detection using smartphones

Health Monitoring apps for smartphones have the potential to improve quality of life and decrease the cost of health services. However, they have failed to live up to expectation in the context of respiratory disease. This is in part due to poor objective measurements of symptoms such as cough. Real-time cough detection using smartphones faces two main challenges namely, the necessity of dealing with noisy input signals, and the need of the algorithms to be computationally efficient, since a high battery consumption would prevent patients from using them. This paper proposes a robust and efficient smartphone-based cough detection system able to keep the phone battery consumption below 25% (16% if only the detector is considered) during 24 h use. The proposed system efficiently calculates local image moments over audio spectrograms to feed an optimized classifier for final cough detection. Our system achieves 88.94% sensitivity and 98.64% specificity in noisy environments with a 5500× speed-up and 4× battery saving compared to the baseline implementation. Power consumption is also reduced by a minimum factor of 6 compared to existing optimized systems in the literature.

Robust Detection of Audio-Cough Events Using Local Hu Moments

Telehealth has shown potential to improve access to healthcare cost-effectively in respiratory illness. However, it has failed to live up to expectation, in part because of poor objective measures of symptoms such as cough events, which could lead to early diagnosis or prevention. Considering the burden that these conditions constitute for national health systems, an effort is needed to foster telehealth potential by developing low-cost technology for efficient monitoring and analysis of cough events. This paper proposes the use of local Hu moments as a robust feature set for automatic cough detection in smartphone-acquired audio signals. The final system feeds a k-nearest-neighbor classifier with the extracted features. To properly evaluate the system in a diversity of noisy backgrounds, we contaminated real cough audio data with a variety of sounds including noise from both indoor and outdoor environments and noncough events (sneeze, laugh, speech, etc.). The created database allows flexible settings of signal-to-noise ratio levels between background sounds and events (cough and noncough). This evaluation was complemented using real patient data from an outpatient clinic. The system is able to detect cough events with high sensitivity (up to 88.51%) and specificity (up to 99.77%) in a variety of noisy environments, overcoming other state-of-the-art audio features. Our proposal paves the way for ubiquitous cough monitoring with minimal disruption in daily activities.

Measurement of Cough Aerodynamics in Healthy Adults

IMPORTANCE

Cough is a critical human reflex and also among the most frequent symptoms in medicine. Despite the prevalence of disordered cough in laryngeal pathologies, comprehensive and quantitative evaluation of cough in these patients is lacking.

OBJECTIVE

Herein we seek to establish normative values for cough aerodynamics to provide a population standard for reference in future studies.

DESIGN, SETTING, AND PARTICIPANTS

Healthy subjects were recruited from an outpatient clinic to perform voluntary cough. Subjects were instructed on the technique for maximal voluntary cough production with measurements recorded on pneumotachograph. Fifty-two subjects were studied, including 29 women and 23 men with a mean age of 51.6 and 52.3 years, respectively. Main Outcomes and Measures: Cough peak airflow, peak pressure, and expiratory rise time. Results were stratified by age, gender, and height.

RESULTS

Peak airflow demonstrated significant differences across age, gender, and height, with flow increasing according to increasing height. Peak cough pressure also increased with height and was significantly greater in males versus females. Expiratory rise time, the time from glottal opening to peak airflow, did not vary with age or height but was statistically significantly longer in women.

CONCLUSIONS

Cough aerodynamics can be readily measured objectively in the outpatient setting. Expiratory rise time, peak flow, and peak pressure are important aspects of each cough epoch. Normative data provided herein can be used for future studies of patients with laryngotracheal disorders, and these cough parameters may prove to be simple, accessible, and repeatable outcome measures.

Cough frequency monitors: can they discriminate patient from environmental coughs?

BACKGROUND

Objective cough frequency measurements are increasingly applied in clinical research. Technological advances enable automated detection and counting of cough events from sound recordings of many hours' duration. A possible limitation of sound-based cough frequency measurement is the contamination of recordings by environmental coughs (coughs from persons other than the patient). This study aimed to investigate the accuracy of a sound-based cough monitor for detecting and discriminating patient cough from environmental cough.

METHODS

As part of a stroke trial (ISRCTN40298220), patients on a hospital ward underwent 15-minute recordings using the Leicester Cough Monitor (LCM), a sound-based cough monitor ('semi-automated counts'). Participants and other persons in the environment were prompted to cough. An observer present in the room recorded the number of patient and environmental coughs ('live counts'). LCM counts were also compared against a manual cough count, the most commonly used gold standard to determine accuracy ('manual sound counts' from listening to recordings), by a blinded assessor who cross-referenced timed cough events from the respective methods. Data for automated, manual and live cough counts were analyzed using agreement statistics.

RESULTS

On sound recordings from five patients, there were 65 patient coughs and 78 environmental coughs (manual counts). Absolute agreement for patient cough count between all three measurement methods (LCM automated, live, and manual sound counts) was high, with intra-class correlation coefficient of 0.94 [95% confidence intervals (CI): 0.74, 0.99]. The proportion of exact agreements for patient cough between LCM and manual count was 0.92, and kappa was 0.84 (95% CI: 0.75, 0.93). The LCM showed sensitivity of 0.94 (95% CI: 0.84, 0.98), specificity of 0.91 (95% CI: 0.82, 0.96), positive predictive value of 0.90 (95% CI: 0.79, 0.95) and negative predictive value of 0.95 (95% CI: 0.86, 0.98) for detecting patient coughs.

CONCLUSIONS

This preliminary study supports the validity of the cough monitor for detecting and discriminating patient from environmental cough. Further validation is recommended, to describe the level of accuracy with greater precision.

Protocol for studying cough frequency in people with pulmonary tuberculosis

INTRODUCTION

Cough is a key symptom of tuberculosis (TB) as well as the main cause of transmission. However, a recent literature review found that cough frequency (number of coughs per hour) in patients with TB has only been studied once, in 1969. The main aim of this study is to describe cough frequency patterns before and after the start of TB treatment and to determine baseline factors that affect cough frequency in these patients. Secondarily, we will evaluate the correlation between cough frequency and TB microbiological resolution.

METHODS

This study will select participants with culture confirmed TB from 2 tertiary hospitals in Lima, Peru. We estimated that a sample size of 107 patients was sufficient to detect clinically significant changes in cough frequency. Participants will initially be evaluated through questionnaires, radiology, microscopic observation drug susceptibility broth TB-culture, auramine smear microscopy and cough recordings. This cohort will be followed for the initial 60 days of anti-TB treatment, and throughout the study several microbiological samples as well as 24 h recordings will be collected. We will describe the variability of cough episodes and determine its association with baseline laboratory parameters of pulmonary TB. In addition, we will analyse the reduction of cough frequency in predicting TB cure, adjusted for potential confounders.

ETHICS AND DISSEMINATION

Ethical approval has been obtained from the ethics committees at each participating hospital in Lima, Peru, Asociación Benéfica PRISMA in Lima, Peru, the Universidad Peruana Cayetano Heredia in Lima, Peru and Johns Hopkins University in Baltimore, USA. We aim to publish and disseminate our findings in peer-reviewed journals. We also expect to create and maintain an online repository for TB cough sounds as well as the statistical analysis employed.

Evaluating the Validity of an Automated Device for Asthma Monitoring for Adolescents: Correlational Design

BACKGROUND

Symptom monitoring is a cornerstone of asthma self-management. Conventional methods of symptom monitoring have fallen short in producing objective data and eliciting patients' consistent adherence, particularly in teen patients. We have recently developed an Automated Device for Asthma Monitoring (ADAM) using a consumer mobile device as a platform to facilitate continuous and objective symptom monitoring in adolescents in vivo.

OBJECTIVE

The objectives of the study were to evaluate the validity of the device using spirometer data, fractional exhaled nitric oxide (FeNO), existing measures of asthma symptoms/control and health care utilization data, and to examine the sensitivity and specificity of the device in discriminating asthma cases from nonasthma cases.

METHODS

A total of 84 teens (42 teens with a current asthma diagnosis; 42 without asthma) aged between 13 and 17 years participated in the study. All participants used ADAM for 7 consecutive days during which participants with asthma completed an asthma diary two times a day. ADAM recorded the frequency of coughing for 24 hours throughout the 7-day trial. Pearson correlation and multiple regression were used to examine the relationships between ADAM data and asthma control, quality of life, and health care utilization at the time of the 7-day trial and 3 months later. A receiver operating characteristic (ROC) curve analysis was conducted to examine sensitivity and specificity based on the area under the curve (AUC) as an indicator of the device's capacity to discriminate between asthma versus nonasthma cases.

RESULTS

ADAM data (cough counts) were negatively associated with forced expiratory volume in first second of expiration (FEV1) (r=-.26, P=.05), forced vital capacity (FVC) (r=-.31, P=.02), and overall asthma control (r=-.41, P=.009) and positively associated with daily activity limitation (r=.46, P=.01), nighttime (r=.40, P=.02) and daytime symptoms (r=.38, P=.02), and health care utilization (r=.61, P<.001). Device data were also a significant predictor of asthma control (β=-.48, P=.003), quality of life (β=-.55, P=.001), and health care utilization (β=.74, P=.004) after 3 months. The ROC curve analysis for the presence of asthma diagnosis had an AUC of 0.71 (95% CI 0.58-0.84), which was significantly different from chance (χ(2) 1=9.7, P=.002), indicating the device's discriminating capacity. The optimal cutoff value of the device was 0.56 with a sensitivity of 51.3% and a specificity of 72.7%.

CONCLUSIONS

This study demonstrates validity of ADAM as a symptom-monitoring device in teens with asthma. ADAM data reflect the current status of asthma control and predict asthma morbidity and quality of life for the near future. A monitoring device such as ADAM can increase patients' awareness of the patterns of cough for early detection of worsening asthma and has the potential for preventing serious and costly future consequences of asthma.

A new method for objectively evaluating childhood nocturnal cough

OBJECTIVE

Cough is so common that the best method for evaluating nocturnal cough in children is required.

METHODS

We developed a cough monitoring system by evaluating 50 child volunteers, and validated the cough monitor in 20 samples from 10 children with cough overnight. Coughs were recorded using a video camera and digital sound recording. At the same time, our system with microphone and accelerometer was used. The number of coughs in each eight hour video-audio recording was counted manually by three trained observers, and all cough data were printed out and the defined cough events, using both these printed-out data and video-audio recordings, were then calculated by three observers.

RESULTS

The cough monitoring system demonstrated excellent agreement between the number of coughs counted by volunteers, and those counted by cough monitoring system (sensitivity 98.8%, specificity 97.8%). Also, there was significant agreement in the counts of coughs between the video-audio method and our system (P < 0.0001), and between the defined cough events and our system (P < 0.0001).

CONCLUSIONS

Our method demonstrated well agreement with the video-audio recording method in children, and is considered to be highly useful for the objective monitoring of overnight cough in children with respiratory diseases.

Targeting TRP channels for chronic cough: from bench to bedside

Cough is currently the most common reason for patients to visit a primary care physician in the UK, yet it remains an unmet medical need. Current therapies have limited efficacy or have potentially dangerous side effects. Under normal circumstances, cough is a protective reflex to clear the lungs of harmful particles; however, in disease, cough can become excessive, dramatically impacting patients' lives. In many cases, this condition is linked to inflammatory diseases such as asthma and chronic obstructive pulmonary disease (COPD), but can also be refractory to treatment and idiopathic in nature. Therefore, there is an urgent need to develop therapies, and targeting the sensory afferent arm of the reflex which initiates the cough reflex may uncover novel therapeutic targets. The cough reflex is initiated following activation of ion channels present on vagal sensory afferents. These ion channels include the transient receptor potential (TRP) family of cation-selective ion channels which act as cellular sensors and respond to changes in the external environment. Many direct activators of TRP channels, including arachidonic acid derivatives, a lowered airway pH, changes in temperature, and altered airway osmolarity are present in the diseased airway where responses to challenge agents which activate airway sensory nerve activity are known to be enhanced. Furthermore, the expression of some TRP channels is increased in airway disease. Together, this makes them promising targets for the treatment of chronic cough. This review will cover the current understanding of the role of the TRP family of ion channels in the activation of airway sensory nerves and cough, focusing on four members, transient receptor potential vanilloid (TRPV) 1, transient receptor potential ankyrin (TRPA) 1, TRPV4, and transient receptor potential melastatin (TRPM) 8 as these represent the channels where most information has been gathered with relevance to the airways. We will describe recent data and highlight the possible therapeutic utility of specific TRP channel antagonists as antitussives in the clinic.

Concordance and discriminatory power of cough measurement devices for individuals with Parkinson disease

BACKGROUND

Dysphagia and aspiration pneumonia are two causes of morbidity in Parkinson disease (PD). In PD, impaired airway clearance can lead to penetration of foreign material, resulting in a high prevalence of aspiration pneumonia and death. This study examines three different devices for measurement of peak airflow during voluntary cough in healthy control subjects and those with PD. Two simple and low-cost devices for measuring peak cough airflow were compared with the "gold standard" pneumotachograph.

METHODS

Thirty-five healthy control subjects and 35 individuals with PD produced voluntary cough at three perceived strengths (weak, moderate, and strong cough) for each of the three devices.

RESULTS

A significant difference in mean peak cough airflow was demonstrated for disease (F[1,56] = 4.0, P &lt; .05) and sex (F[1,56] = 9.59, P &lt; .003) across devices. The digital and analog meters were comparable to the gold standard demonstrating no significant difference (statistical) by device (digital vs analog) in receiver operating characteristic curve analysis. Both devices were discriminative of the presence of PD.

CONCLUSIONS

The analog and digital peak airflow meters are suitable alternatives to the gold standard pneumotachograph due to their low cost, portability, ease of use, and high sensitivity relative to normative peak cough airflows. Voluntary cough airflow measures may serve as a noninvasive means of screening for aspiration risk in target populations. Additionally, quantification of cough strength through use of predetermined limens for weak, moderate, and strong cough may assist clinicians in better describing and tracking cough strength as a contributing factor to aspiration risk.

Detecting paroxysmal coughing from pertussis cases using voice recognition technology

Background

Pertussis is highly contagious; thus, prompt identification of cases is essential to control outbreaks. Clinicians experienced with the disease can easily identify classic cases, where patients have bursts of rapid coughing followed by gasps, and a characteristic whooping sound. However, many clinicians have never seen a case, and thus may miss initial cases during an outbreak. The purpose of this project was to use voice-recognition software to distinguish pertussis coughs from croup and other coughs.

Methods

We collected a series of recordings representing pertussis, croup and miscellaneous coughing by children. We manually categorized coughs as either pertussis or non-pertussis, and extracted features for each category. We used Mel-frequency cepstral coefficients (MFCC), a sampling rate of 16 KHz, a frame Duration of 25 msec, and a frame rate of 10 msec. The coughs were filtered. Each cough was divided into 3 sections of proportion 3-4-3. The average of the 13 MFCCs for each section was computed and made into a 39-element feature vector used for the classification. We used the following machine learning algorithms: Neural Networks, K-Nearest Neighbor (KNN), and a 200 tree Random Forest (RF). Data were reserved for cross-validation of the KNN and RF. The Neural Network was trained 100 times, and the averaged results are presented.

Results

After categorization, we had 16 examples of non-pertussis coughs and 31 examples of pertussis coughs. Over 90% of all pertussis coughs were properly classified as pertussis. The error rates were: Type I errors of 7%, 12%, and 25% and Type II errors of 8%, 0%, and 0%, using the Neural Network, Random Forest, and KNN, respectively.

Conclusion

Our results suggest that we can build a robust classifier to assist clinicians and the public to help identify pertussis cases in children presenting with typical symptoms.

Impact of laryngopharyngeal and gastroesophageal reflux on asthma control in children

OBJECTIVE

A prospective study was carried out to determine the sensitivity and specificity of reflux symptoms and laryngeal findings to diagnose laryngopharyngeal reflux (LPR) and gastro-esophageal reflux (GER) in children with asthma by comparing the results of double probe pH monitorization and to determine the difference between controlled and uncontrolled asthma in terms of GER and LPR coexistence.

METHODS

A total of 50 patients (23 girls, mean age 10.8±0.4 years) with mild to moderate persistent asthma were included in this study. The patients were divided in two groups according to the asthma control status as controlled (n=27) vs. uncontrolled asthma (n=23). All patients completed the reflux symptom questionnaire and then they underwent flexible fiberoptic laryngoscopy and 24h double probe (pharyngeal and esophageal) pH monitorization. Laryngopharyngeal and gastroesophageal reflux were defined according to the double probe pH meter results.

RESULTS

The prevalences of LPR and GER were 70% and 46% in asthmatic patients, respectively. The reflux symptom score and LPR disease index were not useful to predict LPR or GER. There was no association between asthma control status and LPR and GER. Vocal nodule seems to be a valuable sign to evaluate LPR in asthmatic children.

CONCLUSIONS

The reflux symptom score and LPR disease index do not seem reliable to diagnose LPR and GER in children with asthma. The frequency of LPR and GER are independent of asthma control, atopy and long acting beta agonist usage.

Data reduction for cough studies using distribution of audio frequency content

Background

Recent studies suggest that objectively quantifying coughing in audio recordings offers a novel means to understand coughing and assess treatments. Currently, manual cough counting is the most accurate method for quantifying coughing. However, the demand of manually counting cough records is substantial, demonstrating a need to reduce record lengths prior to counting whilst preserving the coughs within them. This study tested the performance of an algorithm developed for this purpose.

Methods

20 subjects were recruited (5 healthy smokers and non-smokers, 5 chronic cough, 5 chronic obstructive pulmonary disease and 5 asthma), fitted with an ambulatory recording system and recorded for 24 hours. The recordings produced were divided into 15 min segments and counted. Periods of inactive audio in each segment were removed using the median frequency and power of the audio signal and the resulting files re-counted.

Results

The median resultant segment length was 13.9 s (IQR 56.4 s) and median 24 hr recording length 62.4 min (IQR 100.4). A median of 0.0 coughs/h (IQR 0.0-0.2) were erroneously removed and the variability in the resultant cough counts was comparable to that between manual cough counts. The largest error was seen in asthmatic patients, but still only 1.0% coughs/h were missed.

Conclusions

These data show that a system which measures signal activity using the median audio frequency can substantially reduce record lengths without significantly compromising the coughs contained within them.

Validation of an automated cough detection algorithm for tracking recovery of pulmonary tuberculosis patients

Background

A laboratory-free test for assessing recovery from pulmonary tuberculosis (TB) would be extremely beneficial in regions of the world where laboratory facilities are lacking. Our hypothesis is that analysis of cough sound recordings may provide such a test. In the current paper, we present validation of a cough analysis tool.

Methodology/Principal Findings

Cough data was collected from a cohort of TB patients in Lima, Peru and 25.5 hours of recordings were manually annotated by clinical staff. Analysis software was developed and validated by comparison to manual scoring. Because many patients cough in bursts, coughing was characterized in terms of cough epochs. Our software correctly detects 75.5% of cough episodes with a specificity of 99.6% (comparable to past results using the same definition) and a median false positive rate of 4 false positives/hour, due to the noisy, real-world nature of our dataset. We then manually review detected coughs to eliminate false positives, in effect using the algorithm as a pre-screening tool that reduces reviewing time to roughly 5% of the recording length. This cough analysis approach provides a foundation to support larger-scale studies of coughing rates over time for TB patients undergoing treatment.

Cough detection algorithm for monitoring patient recovery from pulmonary tuberculosis

In regions of the world where tuberculosis (TB) poses the greatest disease burden, the lack of access to skilled laboratories is a significant problem. A lab-free method for assessing patient recovery during treatment would be of great benefit, particularly for identifying patients who may have drug-resistant tuberculosis. We hypothesize that cough analysis may provide such a test. In this paper we describe algorithm development in support of a pilot study of TB patient coughing. We describe several approaches to event detection and classification, and show preliminary data which suggest that cough count decreases after the start of treatment in drug-responsive patients. Our eventual goal is development of a low-cost ambulatory cough analysis system that will help identify patients with drug-resistant tuberculosis.

GERD-related cough: pathophysiology and diagnostic approach

Chronic cough is a common problem resulting in significant impairment of quality of life. Along with cough variant asthma and nasal disease, gastroesophageal reflux is considered one of three main causes of cough. Despite this, acid suppression therapy is often far from effective. This review aims to explore whether reflux can lead to cough, the circumstances in which this is most likely to occur, and the potential mechanisms linking these processes. Particular mechanisms to be explored include laryngopharyngeal reflux, microaspiration, and neuronal cross-organ sensitization. Finally, diagnostic approaches are considered.

Cough: an unmet clinical need

Cough is among the most common complaints for which patients worldwide seek medical attention. Thus, the evaluation and treatment of cough result in tremendous financial expenditure and consumption of health care resources. Yet, despite the clinical significance of cough, research efforts aimed at improving diagnostic capabilities and developing more effective therapeutic agents have been, to date, disappointing in their limited scope and outcomes. Acute cough due to the common cold represents the most common type of cough. Currently, available medications for the symptomatic management of acute cough are inadequate due to lack of proven efficacy and/or their association with undesirable or intolerable side effects at anti-tussive doses. Subacute cough, often representing a prolonged post-viral response, is typically refractory to standard anti-tussive therapy. Few clinical trials have evaluated therapeutic options for subacute cough. Diagnostic challenges facing the clinician in the management of chronic cough include the determination of whether symptoms of upper airway cough syndrome (formerly, postnasal drip syndrome) or gastro-oesophageal reflux disease are indeed the underlying cause of cough. Chronic, refractory unexplained (formerly, idiopathic) cough must be distinguished from cough that has not been fully evaluated and treated according to current guideline recommendations. Eagerly awaited are new safe and effective anti-tussive agents for use when cough suppression is desired, regardless of underlying aetiology of cough, as well as practical, validated ambulatory cough counters to aid clinical assessment and future research in the field of cough.

Monitoring chronic cough: current and future techniques

Coughing produces a characteristic sound that is readily recognized by the human ear and provides the opportunity to objectively quantify coughing through acoustic recordings. The development of digital recording technologies has facilitated such recordings over the extended time periods needed to capture symptom episodes. However, the manual counting of coughs by listening to long recordings is time-consuming, laborious and restricts usage to research studies. This article outlines the challenges in recording, analyzing and quantifying cough sounds and describes the systems under development. Progress is being made towards automated algorithms to identify and count cough sounds; however, current systems have only been tested over short time periods and in limited patient groups. Further work is required to achieve broadly applicable accurate cough monitoring systems.

Extraesophageal manifestations of gastroesophageal reflux disease: real or imagined?

PURPOSE OF REVIEW

Extraesophageal reflux disease is a common clinical presentation to gastroenterology as well as ear, nose and throat, allergy, and asthma clinics. The diagnosis and management of this condition is challenging. We review the current dilemma in this area and discuss the latest studies which help guide our therapies for patients with suspected extraesophageal reflux.

RECENT FINDINGS

Diagnostic approach to patients with extraesophageal reflux disease involved the use of insensitive tools, which have hampered the ability to correctly identify patients at risk. Empiric trial using proton pump inhibitors is still the recommended initial approach to those suspected of having reflux as the cause for extraesophageal symptoms such as asthma, chronic cough, or laryngitis. Diagnostic testing should be reserved to those unresponsive to therapy. Most recent studies suggest that ambulatory impedance/pH monitoring performed on therapy may be most likely to help exclude reflux as the cause for persistent symptoms. Recent randomized placebo-controlled studies on chronic laryngitis, cough, and asthma have been disappointing in showing benefit of acid suppressive therapy.

SUMMARY

Gastroduodenal reflux may cause symptoms such as chronic cough, asthma, or laryngitis. However, we are currently limited in our diagnostic ability to identify the subgroup of patients who might respond to acid suppressive therapy. Impedance/pH monitoring may be a step in the right direction; however, outcome studies are needed to better understand the role of acid or nonacid reflux in patients with extraesophageal symptoms.

Assessing efficacy of therapy for cough

An antitussive agent should reduce the amount of coughing experienced by the patient sufficiently for the patient to appreciate an improvement in cough severity and regard the improvement as sufficient to outweigh any adverse effects or risks associated with the treatment. In recent years the development of objective cough counting devices and cough-specific quality of life tools have vastly improved our ability to appropriately assess the effectiveness of anti-tussive agents and hopefully will lead to the development of safe and effective treatments in the future. This article summarizes current knowledge of methodologies available for assessing cough therapies, the patient groups to study, and the design of clinical trials.

A system for recording high fidelity cough sound and airflow characteristics

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.

Cough, basic science, and the clinician

Cough is a major cause of disability and distress worldwide. In June 2007, the First American Cough Conference was held in New York City and covered a spectrum of topics of interest to the basic scientist as well as the clinician. The conference was organized by Dr. Peter Dicpinigaitis and its proceedings are published in the February Supplement of LUNG. This supplement consists of a series of articles that provide a valuable overview of recent advances in our understanding of mechanism, etiology, and treatment of cough and constitute an adjunct to the guidelines recently published by the American College of Chest Physicians, the British Thorax Society, the European Respiratory Society, and the Japanese Respiratory Society.