Surface imaging for real‐time patient respiratory function assessment in intensive care

Abstract

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.

Advancements in Methods and Camera-Based Sensors for the Quantification of Respiration

“…Monitoring of pulmonary function such as tidal volume, minute ventilation, forced vital capacity, and forced expiratory volume has been studied in many works as well in [ 65 , 116 , 117 , 118 , 119 , 120 ] (2010–2015), [ 6 , 7 , 8 , 9 , 32 , 46 , 52 , 88 , 91 , 92 , 100 , 103 , 110 , 121 , 122 , 123 , 124 ] (2016–2020).…”

“…Nazir et al [ 110 ] recently presented a contactless real time system, based on a single ToF sensor, for quantitative assessment of respiration in ICU patients. By analyzing the patient’s chest wall surface geomorphologic changes, the authors calculate multiple respiratory function parameters: RR and volume.…”

Technical note: Surface imaging for real‐time patient positioning in external radiation therapy

“…Furthermore, this technique is not able to accurately reconstruct low reflective surfaces such as hair or clothes, in comparison with other technologies. 9,10 The Catalyst system uses a projector unit based on light-emitting diode (LED) lights and a charged-coupled device (CCD) camera. The patient position is determined in real time based on the triangulation approach.…”

“…However, the frequency rate is limited to 6.5 Hz 9 in addition to an extended reconstruction time. Furthermore, this technique is not able to accurately reconstruct low reflective surfaces such as hair or clothes, in comparison with other technologies 9,10 . The Catalyst system uses a projector unit based on light‐emitting diode (LED) lights and a charged‐coupled device (CCD) camera.…”

The authors reply

“…We do also agree about the fact that agitation or delirium may impair signal monitoring despite automated calibration of the signal. However, all calibrations of TOF monitoring are performed on a real-time basis using a validated real-time artificial intelligence skeleton tracing (4) and box-of-interest selection, as described in the proof-of-concept article (5). Either right or left hemithorax movements are evaluated, in association with the abdominal excursion monitoring, in order to avoid any false estimation of V t and to consider asynchrony and irregular respiration.…”