Event-Triggered Pseudo Supervised Meta Learning for Susceptibility Assessment of Acute Mountain Sickness

Lei Wang, Dawei Shi*, Lingling Zhu, Junzheng Wang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Acute altitude sickness presents as a syndrome characterized by individuals' incapacity to adapt to the hypoxic conditions of high-altitude environments. The assessment of this sickness typically relies on the subjective evaluation of symptom severity using the Lake Louise score, introducing potential subjective biases and rendering the labels unreliable. To address this challenge, this paper introduces a weakly supervised meta-learning algorithm tailored for the assessment of susceptibility to acute altitude sickness within a few-shot framework. Initially, objective sleep data is subjected to clustering, and pseudo-labels are generated from the cluster result exhibiting the highest mutual information with the Lake Louise score. This approach capitalizes on the mutual complementarity of subjective and objective data, thereby enhancing label credibility. Subsequently, a task-driven pseudo-label supervised meta-learning algorithm is formulated to comprehensively explore individual differences. Moreover, recognizing the necessity for model updates during online learning, an event-triggered online learning algorithm is devised to optimize computational resources. Experimental validation utilizing data from 18 real subjects demonstrates promising results: an accuracy of 79.900% and an F1 score of 79.342% for acute altitude sickness susceptibility assessment, with further improvements evident through the online updated model's accuracy of 81.992% and F1 score of 81.366% on the test set. These outcomes underscore the viability of the proposed event-triggered weakly supervised meta-learning algorithm in the assessment of susceptibility to acute altitude sickness.

Original languageEnglish
Title of host publicationProceedings - 2024 39th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1702-1706
Number of pages5
ISBN (Electronic)9798350379228
DOIs
Publication statusPublished - 2024
Event39th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2024 - Dalian, China
Duration: 7 Jun 20249 Jun 2024

Publication series

NameProceedings - 2024 39th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2024

Conference

Conference39th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2024
Country/TerritoryChina
CityDalian
Period7/06/249/06/24

Keywords

  • Acute Mountain Sickness
  • Event-triggered
  • Pseudo Supervised Meta Learning
  • Unreliable Labels

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