Meta: Data Compression and Event Detection Grand Challenge 2024 With SPRSound Dataset

The development of digital stethoscopes and automatic respiratory sound algorithms is crucial for accelerating diagnosis, reducing physician workload, and lowering mortality rates from respiratory diseases. However, transmitting data from digital stethoscopes to cloud or other storage devices require substantial storage and transmission capacities, especially for wearable devices used for long-term monitoring. Besides, current automatic algorithms often predict labels for segmented sound events, lacking precision in detecting the onsets and offsets of respiratory sound events. To address these challenges, we organized a grand challenge inviting the community to develop data compression and event detection algorithms to reduce the storage and transmission burden and event segmentation workload. A new testing set was prepared to evaluate the performance of the submissions. The top teams presented their work at the 20th IEEE Biomedical Circuits and Systems Conference (BioCAS) 2024.

IEEE SOCIETY/COUNCIL Circuits and Systems (CAS) Society

DATA TYPE/LOCATION Sound and Text; Worldwide

DATA DOI/PID 10.21227/bhw7-2044; 10.21227/nfkk-1x47