Key result
A proposed remote imaging system for cardiopulmonary signal extraction outperformed conventional methods like independent and principle component analysis in stationary and non-stationary scenarios.
Why the study?
Does a novel remote imaging system with noise artifact removal improve cardiopulmonary signal extraction compared to conventional methods?
Does a novel remote imaging system with noise artifact removal improve cardiopulmonary signal extraction compared to conventional methods?
A novel remote optical imaging system successfully extracts cardiopulmonary signals from multiple subjects at long distances with improved noise artifact removal compared to conventional methods.
Hypothesis-generating for contactless monitoring; requires prospective clinical validation before any practice consideration.
Most existing imaging technologies are prone to noise artifact resulting from movement of subjects, movement of the camera, facial expressions, talking, skin tone, and lighting variations. In addition, these technologies have been limited to detecting physiological signs from a single subject at a time. Still, another challenge facing these technologies is that they have only been demonstrated over a limited range to a subject. This paper proposes an efficient remote imaging system with a new, low-complexity method for noise artifact removal to extract the cardiopulmonary signal from a number of subjects (up to six people) and at long-distances (up to 60 m). The experimental results of the proposed system showed a strong agreement, high correlation, and low noise level with the reference measurements and outperformed the conventional measurement methods such as independent component analysis and principle component analysis in both the stationary and non-stationary scenarios.
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Al‐Naji et al. (2018) studied Cardiopulmonary signal extraction. Remote imaging system with noise artifact removal vs. Independent component analysis and principle component analysis was evaluated on Cardiopulmonary signal extraction (agreement, correlation, and noise level). A proposed remote imaging system for cardiopulmonary signal extraction outperformed conventional methods like independent and principle component analysis in stationary and non-stationary scenarios.
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