Key result
An EMD-based algorithm for automatic emboli detection in echo Doppler audio signals achieved 83% sensitivity and 76% specificity for assessing decompression sickness risk.
Why the study?
Precordial echo Doppler audio analysis for circulating gas bubbles requires specialist doctors, but on-site medical assistance cannot always be guaranteed after underwater activity.
Does an EMD-based algorithm accurately detect emboli in echo Doppler audio signals from divers?
Does an EMD-based algorithm accurately detect emboli in echo Doppler audio signals from divers?
An EMD-based algorithm can automatically detect circulating gas bubbles in echo Doppler audio signals with 83% sensitivity and 76% specificity, potentially aiding in real-time decompression sickness risk assessment.
May support automated emboli monitoring in divers; leaves open prospective validation before clinical use.
Divers’ health state after underwater activity can be assessed after the immersion using precordial echo Doppler examination. An audio analysis of the acquired signals is performed by specialist doctors to detect circulating gas bubbles in the vascular system and to evaluate the decompression sickness risk. Since on-site medical assistance cannot always be guaranteed, we propose a system for automatic emboli detection using a custom portable device connected to the echo Doppler instrument. The empirical mode decomposition method is used to develop a real-time algorithm able to automatically detect embolic events and, consequently, assess the decompression sickness risk according to the Spencer’s scale. The proposed algorithm has been tested according to an experimental protocol approved by the Divers Alert Network. It involved 30 volunteer divers and produced 37 echo Doppler files useful for the algorithm’s performances evaluation. The results obtained by the proposed emboli detection algorithm (83% sensitivity and 76% specificity) make the system particularly suitable for real-time evaluation of the decompression sickness risk level. Furthermore, the system could also be used in continuous monitoring of hospitalized patients with embolic risks such as post surgery ones.
No takes yet. Share an insight, caveat, or question.
Pierleoni et al. (2019) studied Decompression sickness risk (n=30). EMD-based algorithm for automatic emboli detection was evaluated on Emboli detection (sensitivity and specificity). An EMD-based algorithm for automatic emboli detection in echo Doppler audio signals achieved 83% sensitivity and 76% specificity for assessing decompression sickness risk.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: