OBJECTIVES: The mechanisms of high-flow nasal cannula are still debated but may be mediated by the generation of low positive end-expiratory pressure and a washout of the airway dead space. The aims of this study were to assess the effects of high-flow nasal cannula on tidal volume using a noninvasive method using a time-of-flight camera, under various conditions. DESIGN: A physiologic evaluation in healthy volunteers. SETTING: An university hospital ICU. SUBJECTS: Ten healthy volunteers were included in a physiologic study (CamOpt study, ClinicalTrials.gov identifier: NCT04096183). INTERVENTIONS: All volunteers were submitted to 12 different conditions (i.e., gas flow [baseline = 0; 30–60 L/min]; mouth [open/closed]; respiratory rate [baseline; baseline + 10 breaths/min]). Tidal volume measurements were performed every minute, during a 6-minute recording period. In all combinations, reference respiratory rate was measured by using chronometric evaluation, over a 30-second period (RRREF), and by using the time-of-flight camera (RRTOF). MEASUREMENTS AND MAIN RESULTS: Tidal volume increased while increasing gas flow whatever the respiratory rate and mouth condition (p < 0.001). Similar results were observed whatever the experimental conditions (p < 0.01), except one (baseline respiratory rate + 10 breaths/min and mouth closed). Tidal volume increased while decreasing respiratory rate (p < 0.001) and mouth closing (p < 0.05). Proportion of tidal volume greater than 10, 15, and 20 mL/kg changed while increasing the flow. RRTOF was in agreement with RRREF (intraclass correlation coefficient, 0.96), with a low mean bias (0.55 breaths/min) and acceptable deviation. CONCLUSIONS: Time-of-flight enables to detect tidal volume changes under various conditions of high-flow nasal cannula application. Tidal volume increased significantly while increasing gas flow and mouth closing. Such technique might be useful to monitor the risk of patient self-inflicted lung injury or under assistance.

This work shows a significant noise compensation and surface restitution after surface filtering and therefore a potential use of the Kinect V2 camera for different radiotherapy-based applications, such as respiratory tracking and collision detection.

Purpose Monitoring of physiological parameters is a major concern in Intensive Care Units (ICU) given their role in the assessment of vital organ function. Within this context, one issue is the lack of efficient noncontact techniques for respiratory monitoring. In this paper, we present a novel noncontact solution for real‐time respiratory monitoring and function assessment of ICU patients. Methods The proposed system uses a Time‐of‐Flight depth sensor to analyze the patient’s chest wall morphological changes in order to estimate multiple respiratory function parameters. The automatic detection of the patient's torso is also proposed using a deep neural network model trained on the COCO dataset. The evaluation of the proposed system was performed on a mannequin and on 16 mechanically ventilated patients (a total of 216 recordings) admitted in the ICU of the Brest University Hospital. Results The estimation of respiratory parameters (respiratory rate and tidal volume) showed high correlation with the reference method (r = 0.99; P < 0.001 and r = 0.99; P < 0.001) in the mannequin recordings and (r = 0.95, P < 0.001 and r = 0.90, P < 0.001) for patients. Conclusion This study describes and evaluates a novel noncontact monitoring system suitable for continuous monitoring of key respiratory parameters for disease assessment of critically ill patients.