Multimodal physiological signal learning for clinical sleep respiratory event recognition
He Qin, Xiaocun Chen, Yao Liu, Xu Wei, Fei Chen, Lijie Lu, Liyun Liu, Tanjun Wei, Xionghui Hu, Xianhai Li, Xinhui Cheng · 2026
Read Multimodal physiological signal learning for clinical sleep respiratory event recognition by He Qin, Xiaocun Chen, Yao Liu, Xu Wei, Fei Chen, Lijie Lu, Liyun Liu, Tanjun Wei, Xionghui Hu, Xianhai Li, Xinhui Cheng (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13593408.txt.
Description
He Qin and ten co-authors build a multimodal learning frame that spots sleep breathing events from body signals for clinical use. Sound event spotting aids screening, care reads, and long term tracking. The study came out in twenty twenty-six.
Two signal streams feed the frame: brain linked signals and breath sound linked traits. A dual branch encoder reads each stream's time patterns. A routing module swaps fine detail between streams, and a query module pools the traits that mark an event. Training adds balanced loss plus sleep stage and arousal side tasks, to cope with rare event classes. Patient level cross checks gauge the skill.
Catalog record
| CREATOR | He Qin, Xiaocun Chen, Yao Liu, Xu Wei, Fei Chen, Lijie Lu, Liyun Liu, Tanjun Wei, Xionghui Hu, Xianhai Li, Xinhui Cheng |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 74 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |