Estimating SpO with Deep Oxygen Desaturations from Facial Video Under Various Lighting Conditions: A Feasibility Study.

This paper presents a feasibility study to collect data, process signals, and validate accuracy of peripheral oxygen saturation (SpO) estimation from facial video in various lighting conditions. We collected facial videos using RGB camera, without auto-tuning, from subjects when they were breathing through a mouth tube with their nose clipped. The videos were record under four lighting conditions: warm color temperature and normal brightness, neutral color temperature and normal brightness, cool color temperature and normal brightness, neutral color temperature and dim brightness.

Contactless Monitoring of Respiratory Rate and Breathing Absence from Head Movements Using an RGB Camera.

Contactless vital sign monitoring is more demanding for long-term, continuous, and unobtrusive measurements. Camera-based respiratory monitoring is receiving growing interest with advanced video technologies and computational power. The volume variations of the lungs for airflow changes create a periodic movement of the torso, but identifying the torso is more challenging than face detection in a video.

Enhanced Contactless Heart Rate Monitoring Using Camera with Motion Artifact Removal During Physical Activities.

Contactless monitoring of heart rate (HR) can improve passive and continuous tracking of cardiovascular activities and overall people's health. Remote photoplethysmography (rPPG) using a camera eliminates the need for a wearable device. rPPG-based HR has shown promising results to be accurate and comparable to conventional methods such as contact PPG.

Motion- Based Respiratory Rate Estimation with Motion Artifact Removal Using Video of Face and Upper Body.

Respiratory rate (RR) is a significant indicator of health conditions. Remote contactless measurement of RR is gaining popularity with recent respiratory tract infection awareness. Among various methods of contactless RR measurement, a video of an individual can be used to obtain an instantaneous RR.

Remote Photoplethysmography and Heart Rate Estimation by Dynamic Region of Interest Tracking.

Remote photoplethysmography (PPG) estimates vital signs by measuring changes in the reflected light from the human skin. Compared to traditional PPG techniques, remote PPG enables contactless measurement at a reduced cost. In this paper, we propose a novel method to extract remote PPG signals and heart rate from videos.

Deep Multivariate Domain Translation for Device Invariant Pulmonary Patient Identification from Cough and Speech Sounds.

Pulmonary audio sensing from cough and speech sounds in commodity mobile and wearable devices is increasingly used for remote pulmonary patient monitoring, home healthcare, and automated disease analysis. Patient identification is important for such applications to ensure system accuracy and integrity, and thus avoiding errors and misdiagnosis. Widespread usage and deployment of such patient identification models across various devices are challenging due to domain shift of acoustic features because of device heterogeneity.

Utilizing Deep Learning on Limited Mobile Speech Recordings for Detection of Obstructive Pulmonary Disease.

Passive assessment of obstructive pulmonary disease has gained substantial interest over the past few years in the mobile and wearable computing communities. One of the promising approaches is speech-based pulmonary assessment wherein spontaneous or scripted speech is used to evaluate an individual's pulmonary condition. Recent approaches in this regard heavily rely on accurate speech activity segmentation and specific, hand-crafted features.

SpeechSpiro: Lung Function Assessment from Speech Pattern as an Alternative to Spirometry for Mobile Health Tracking.

Respiratory illnesses are common in the United States and globally; people deal with these illnesses in various forms, such as asthma, chronic obstructive pulmonary diseases, or infectious respiratory diseases (e.g., coronavirus).

Toward Early Severity Assessment of Obstructive Lung Disease Using Multi-Modal Wearable Sensor Data Fusion During Walking.

Early detection of chronic diseases helps to minimize the disease impact on patient's health and reduce the economic burden. Continuous monitoring of such diseases helps in the evaluation of rehabilitation program effectiveness as well as in the detection of exacerbation. The use of everyday wearables i.

Adapting to Noise in Speech Obfuscation by Audio Profiling Using Generative Models for Passive Health Monitoring.

Passive health monitoring has been introduced as a solution for continuous diagnosis and tracking of subjects' condition with minimal effort. This is partially achieved by the technology of passive audio recording although it poses major audio privacy issues for subjects. Existing methods are limited to controlled recording environments and their prediction is significantly influenced by background noises.

CoughMatch - Subject Verification Using Cough for Personal Passive Health Monitoring.

Automatic cough detection using audio has advanced passive health monitoring on devices such as smart phones and wearables; it enables capturing longitudinal health data by eliminating user interaction and effort. One major issue arises when coughs from surrounding people are also detected; capturing false coughs leads to significant false alarms, excessive cough frequency, and thereby misdiagnosis of user condition. To address this limitation, in this paper, a method is proposed that creates a personal cough model of the primary subject using limited number of cough samples; the model is used by the automatic cough detection to verify whether the identified coughs match the personal pattern and belong to the primary subject.

CoughGAN: Generating Synthetic Coughs that Improve Respiratory Disease Classification.

Despite the prevalence of respiratory diseases, their diagnosis by clinicians is challenging. Accurately assessing airway sounds requires extensive clinical training and equipment that may not be easily available. Current methods that automate this diagnosis are hindered by their use of features that require pulmonary function tests.

Estimation of the Lung Function Using Acoustic Features of the Voluntary Cough.

Spirometry test, a measure of the patient's lung function, is the gold standard for diagnosis and monitoring of chronic pulmonary diseases. Spirometry is currently being done in hospital settings by having the patients blow the air out of their lungs forcefully and into the spirometer's tubes under the supervision and constant guidance of clinicians. This test is expensive, cumbersome and not easily applicable to every-day monitoring of these patients.

A Comprehensive Approach for Classification of the Cough Type.

Identifying the presence of sputum in the lung is essential in detection of diseases such as lung infection, pneumonia and cancer. Cough type classification (dry/wet) is an effective way of examining presence of lung sputum. This is traditionally done through physical exam in a clinical visit which is subjective and inaccurate.