Detection and classification of adventitious acoustic lung sounds plays an important role in diagnosing, monitoring, controlling and, caring the patients with lung diseases. Such systems can be presented as different platforms like medical devices, standalone software or smartphone application. Ubiquity of smartphones and widespread use of the corresponding applications make such a device an attractive platform for hosting the detection and classification systems for adventitious lung sounds. In this paper, the smartphone-based systems for automatic detection and classification of the adventitious lung sounds are surveyed. Such adventitious sounds include cough, wheeze, crackle and, snore. Relevant sounds related to abnormal respiratory activities are considered as well. The methods are shortly described and the analyzing algorithms are explained. The analysis includes detection and/or classification of the sound events. A summary of the main surveyed methods together with the classification parameters and used features for the sake of comparison is given. Existing challenges, open issues and future trends will be discussed as well.

Cough and wheezing are the predominant symptoms of acute bronchitis. Hitherto, the evaluation of respiratory symptoms was limited to subjective methods such as questionnaires. The main objective of this study was to objectively determine the time course of cough and wheezing in children with acute bronchitis. The impact of nocturnal cough on parent’s quality of life was assessed as secondary outcome. In 36 children (2–8 years), the frequency of nocturnal cough and wheezing was recorded during three nights by automated lung sound monitoring. Additionally, parents completed symptom logs, i.e., the Bronchitis Severity Score (BSS), as well as the Parent-proxy Children’s Acute Cough-specific Quality of Life Questionnaire (PAC-QoL). During the first night, patients had 34.4 ± 52.3 (mean ± SD) cough epochs, which were significantly reduced in night 5 (13.5 ± 26.5; p < 0.001) and night 9 (12.8 ± 28.1; p < 0.001). Twenty-two patients had concomitant wheezing, which declined within the observation period as well. All subjective parameters (BSS, Cough log and PAC-QoL) were found to be significantly correlated with the objectively assessed cough parameters. Conclusion: Long-term recording of cough and wheezing offers a useful opportunity to objectively evaluate the time course of respiratory symptoms in children with acute bronchitis. To assess putative effects of pharmacotherapy on nocturnal bronchitis symptoms, future studies in more homogeneous patient groups are needed. What is Known: • Cough and wheezing are the predominant symptoms of acute bronchitis. • There is a diagnostic gap in long-term assessment of these respiratory symptoms, which needs to be closed to optimize individual therapies. What is New: • Long-term recording of nocturnal cough and wheezing allows for objective evaluation of respiratory symptoms in children with acute bronchitis and provides a tool to validate the efficacy of symptomatic bronchitis therapies.

Knee acoustic emissions provide information about joint health and loading in motion. As the reproducibility of knee acoustic emissions by vibroarthrography is yet unknown, we evaluated the intrasession and interday reliability of knee joint sounds. In 19 volunteers (25.6 ± 2.0 years, 11 female), knee joint sounds were recorded by two acoustic sensors (16,000 Hz; medial tibial plateau, patella). All participants performed four sets standing up/sitting down (five repetitions each). For measuring intrasession reliability, we used a washout phase of 30 min between the first three sets, and for interday reliability we used a washout phase of one week between sets 3 and 4. The mean amplitude (dB) and median power frequency (Hz, MPF) were analyzed for each set. Intraclass correlation coefficients (ICCs (2,1)), standard errors of measurement (SEMs), and coefficients of variability (CVs) were calculated. The intrasession ICCs ranged from 0.85 to 0.95 (tibia) and from 0.73 to 0.87 (patella). The corresponding SEMs for the amplitude were ≤1.44 dB (tibia) and ≤2.38 dB (patella); for the MPF, SEMs were ≤13.78 Hz (tibia) and ≤14.47 Hz (patella). The intrasession CVs were ≤0.06 (tibia) and ≤0.07 (patella) (p < 0.05). The interday ICCs ranged from 0.24 to 0.33 (tibia) and from 0 to 0.82 (patella) for both the MPF and amplitude. The interday SEMs were ≤4.39 dB (tibia) and ≤6.85 dB (patella) for the amplitude and ≤35.39 Hz (tibia) and ≤15.64 Hz (patella) for the MPF. The CVs were ≤0.14 (tibia) and ≤0.08 (patella). Knee joint sounds were highly repeatable within a single session but yielded inconsistent results for the interday reliability.

Purpose: Chronic cough is one of the main symptoms of COPD. Ambulatory objective monitoring provides novel insights into the determinants and characteristics of nighttime cough in COPD. Materials and methods: Nighttime cough was monitored objectively by LEOSound lung sound monitor in patients with stable COPD II–IV. In 30 patients, with 10 patients in each stage group, nighttime cough was analyzed for epoch frequency, epoch severity (epoch length and coughs per epoch), and pattern (productive or nonproductive). Results: Cough was found in all patients ranging from 1 to 294 events over the recording period. In 29 patients, cough epochs were monitored, ranging from 1 to 75 epochs. The highest amount of cough epochs was found in patients with COPD stage III. Active smokers had significantly more productive cough epochs (61%) than nonsmokers (24%). Conclusion: We found a high rate of nighttime cough epochs in patients with COPD, especially in those in stage III. Productive cough was predominantly found in patients with persistent smoking. LEOSound lung sound monitor offers a practical and valuable opportunity to evaluate cough objectively.

In recent decades, great progress has been made in the contactless detection of infant and child respiratory motion. Systematic camera errors and disturbing environmental influences can have a strong impact on the signal quality of depth cameras. The prevalence of respiratory diseases in children and the central role that respiratory activity plays in the treatment of these conditions necessitate a robust and non-intrusive way of quantifying nocturnal respiratory activity in children. The aim of our study was to assess the robustness of various depth cameras (Microsoft Kinect V2, PMD CamBoard pico flexx, PMD CamBoard pico monstar, ORBBEC Astra Pro, Intel RealSense D435) regarding ambient factors typically found during the use in clinical and home settings. We investigated the influence of viewing angles, reflectivity and IR light on the signal quality. By correlating depth images with respiratory - belt signals, our analyses show that three cameras achieved adequate performance and might be considered for use in contactless assessment of infant or child respiration. Several cameras failed under some of the ambient conditions which are likely to be encountered in real life settings. Therefore, a careful camera selection regarding environmental influences is pivotal.

Because of their resilience, Time-of-Flight (ToF) cameras are now essential components in scientific and industrial settings. This paper outlines the essential factors for modeling 3D ToF cameras, with specific emphasis on analyzing the phenomenon known as “wiggling”. Through our investigation, we demonstrate that wiggling not only causes systematic errors in distance measurements, but also introduces periodic fluctuations in statistical measurement uncertainty, which compounds the dependence on the signal-to-noise ratio (SNR). Armed with this knowledge, we developed a new 3D camera model, which we then made computationally tractable. To illustrate and evaluate the model, we compared measurement data with simulated data of the same scene. This allowed us to individually demonstrate various effects on the signal-to-noise ratio, reflectivity, and distance.