An ensemble learning approach to digital corona virus preliminary screening from cough sounds.

This work develops a robust classifier for a COVID-19 pre-screening model from crowdsourced cough sound data. The crowdsourced cough recordings contain a variable number of coughs, with some input sound files more informative than the others. Accurate detection of COVID-19 from the sound datasets requires overcoming two main challenges (i) the variable number of coughs in each recording and (ii) the low number of COVID-positive cases compared to healthy coughs in the data. We use two open datasets of crowdsourced cough recordings and segment each cough recording into non-overlapping coughs. The segmentation enriches the original data without oversampling by splitting the original cough sound files into non-overlapping segments. Splitting the sound files enables us to increase the samples of the minority class (COVID-19) without changing the feature distribution of the COVID-19 samples resulted from applying oversampling techniques. Each cough sound segment is transformed into six image representations for further analyses. We conduct extensive experiments with shallow machine learning, Convolutional Neural Network (CNN), and pre-trained CNN models. The results of our models were compared to other recently published papers that apply machine learning to cough sound data for COVID-19 detection. Our method demonstrated a high performance using an ensemble model on the testing dataset with area under receiver operating characteristics curve = 0.77, precision = 0.80, recall = 0.71, F1 measure = 0.75, and Kappa = 0.53. The results show an improvement in the prediction accuracy of our COVID-19 pre-screening model compared to the other models.

Reduction of roadway noise in a coastal city underwater soundscape during COVID-19 confinement.

Confinement due to the COVID-19 pandemic drastically reduced human activities. Underwater soundscape variations are discussed in this study, comparing a typical and confinement day in a coastal lagoon near a popular tourist city in Mexico. Recording devices were located at 2 m in depth and 430 m away from the main promenade-a two-way avenue for light vehicle traffic-where main tourist infrastructure is located. The nearby marine environment is habitat to birds and dolphins as well as fish and invertebrates of commercial importance. Medium and small boats usually transit the area. The main underwater sound level reduction was measured at low frequencies (10-2000 Hz) because of the decrease in roadway noise. Vessel traffic also decreased by almost three quarters, although the level reduction due to this source was less noticeable. As typical day levels in the roadway noise band can potentially mask fish sounds and affect other low frequency noise-sensitive marine taxa, this study suggests that comprehensive noise analysis in coastal marine environments should consider the contribution from nearby land sources.

Influence of Protective Face Coverings on the Speech Recognition of Cochlear Implant Patients.

OBJECTIVES: The objectives were to characterize the effects of wearing face coverings on: 1) acoustic speech cues, and 2) speech recognition of patients with hearing loss who listen with a cochlear implant. METHODS: A prospective cohort study was performed in a tertiary referral center between July and September 2020. A female talker recorded sentences in three conditions: no face covering, N95 mask, and N95 mask plus a face shield. Spectral differences were analyzed between speech produced in each condition. The speech recognition in each condition for twenty-three adult patients with at least 6 months of cochlear implant use was assessed. RESULTS: Spectral analysis demonstrated preferential attenuation of high-frequency speech information with the N95 mask plus face shield condition compared to the other conditions. Speech recognition did not differ significantly between the uncovered (median 90% [IQR 89%-94%]) and N95 mask conditions (91% [IQR 86%-94%]; P = .253); however, speech recognition was significantly worse in the N95 mask plus face shield condition (64% [IQR 48%-75%]) compared to the uncovered (P < .001) or N95 mask (P < .001) conditions. CONCLUSIONS: The type and combination of protective face coverings used have differential effects on attenuation of speech information, influencing speech recognition of patients with hearing loss. In the face of the COVID-19 pandemic, there is a need to protect patients and clinicians from spread of disease while maximizing patient speech recognition. The disruptive effect of wearing a face shield in conjunction with a mask may prompt clinicians to consider alternative eye protection, such as goggles, in appropriate clinical situations. LEVEL OF EVIDENCE: 3 Laryngoscope, 131:E2038-E2043, 2021.

CIoTVID: Towards an Open IoT-Platform for Infective Pandemic Diseases such as COVID-19.

The factors affecting the penetration of certain diseases such as COVID-19 in society are still unknown. Internet of Things (IoT) technologies can play a crucial role during the time of crisis and they can provide a more holistic view of the reasons that govern the outbreak of a contagious disease. The understanding of COVID-19 will be enriched by the analysis of data related to the phenomena, and this data can be collected using IoT sensors. In this paper, we show an integrated solution based on IoT technologies that can serve as opportunistic health data acquisition agents for combating the pandemic of COVID-19, named CIoTVID. The platform is composed of four layers-data acquisition, data aggregation, machine intelligence and services, within the solution. To demonstrate its validity, the solution has been tested with a use case based on creating a classifier of medical conditions using real data of voice, performing successfully. The layer of data aggregation is particularly relevant in this kind of solution as the data coming from medical devices has a very different nature to that coming from electronic sensors. Due to the adaptability of the platform to heterogeneous data and volumes of data; individuals, policymakers, and clinics could benefit from it to fight the propagation of the pandemic.

Acoustic voice analysis in the COVID-19 era.

OBJECTIVE: Among the different procedures used by the ENT, acoustic analysis of voice has become widely used for correct diagnosis of dysphonia. The instrumental measurements of acoustic parameters were limited during the COVID-19 pandemic by the common belief that a face mask affects the results of the analysis. The purpose of our study was to investigate the impact of surgical masks on F0, jitter, shimmer and harmonics-to-noise ratio (HNR) in adults. METHODS: The study was carried out on a selected group of 50 healthy subjects. Voice samples were recorded directly in Praat. All subjects were trained to voice a vocal sample of a sustained /a/, at a conversational voice intensity, with no intensity or frequency variation, for the Maximum Phonation Time (MPT), wearing the surgical mask and then without wearing the surgical mask. RESULTS: None of the variations in acoustic voice analysis detected wearing a surgical mask and not wearing a surgical mask were statistically significant. CONCLUSIONS: Our study demonstrates that the acoustic voice analysis procedure can continue to be performed with the use of a surgical mask for the patient, even during the COVID-19 pandemic.

Characteristics of Pulmonary Auscultation in Patients with 2019 Novel Coronavirus in China.

BACKGROUND: Effective auscultations are often hard to implement in isolation wards. To date, little is known about the characteristics of pulmonary auscultation in novel coronavirus (COVID-19) pneumonia. OBJECTIVES: The aim of this study was to explore the features and clinical significance of pulmonary auscultation in COVID-19 pneumonia using an electronic stethoscope in isolation wards. METHODS: This cross-sectional, observational study was conducted among patients with laboratory-confirmed COVID-19 at Wuhan Red-Cross Hospital during the period from January 27, 2020, to February 12, 2020. Standard auscultation with an electronic stethoscope was performed and electronic recordings of breath sounds were analyzed. RESULTS: Fifty-seven patients with average age of 60.6 years were enrolled. The most common symptoms were cough (73.7%) during auscultation. Most cases had bilateral lesions (96.4%) such as multiple ground-glass opacities (69.1%) and fibrous stripes (21.8%). High-quality auscultation recordings (98.8%) were obtained, and coarse breath sounds, wheezes, coarse crackles, fine crackles, and Velcro crackles were identified. Most cases had normal breath sounds in upper lungs, but the proportions of abnormal breath sounds increased in the basal fields where Velcro crackles were more commonly identified at the posterior chest. The presence of fine and coarse crackles detected 33/39 patients with ground-glass opacities (sensitivity 84.6% and specificity 12.5%) and 8/9 patients with consolidation (sensitivity 88.9% and specificity 15.2%), while the presence of Velcro crackles identified 16/39 patients with ground-glass opacities (sensitivity 41% and specificity 81.3%). CONCLUSIONS: The abnormal breath sounds in COVID-19 pneumonia had some consistent distributive characteristics and to some extent correlated with the radiologic features. Such evidence suggests that electronic auscultation is useful to aid diagnosis and timely management of the disease. Further studies are indicated to validate the accuracy and potential clinical benefit of auscultation in detecting pulmonary abnormalities in COVID-19 infection.

Lima soundscape before confinement and during curfew. Airplane flights suppressions because of Peruvian lockdown.

Peru declared a state of emergency on March 16 in order to prevent SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) transmissions; thus, the International Airport was closed and the soundscape of urban zones under the flight tracks have been changed in view of the fact that airplane traffic was suspended. The authors have been conducting noise monitoring since February and because of that sufficient noise data for knowing the soundscape before and during the lockdown were obtained. This article presents a case of aircraft annoyance noise in one of Lima's city districts, which is near the aircraft climbing curve, toward the ocean on departure from Lima.