A methodological framework for validating a multi-domain physiological sensor for divers using a scalable data fusion...

Area of Science:

• Physiological monitoring
• Biomedical engineering
• Diving science

Background:

• Diving poses physiological risks, but understanding these is limited by underwater monitoring technology.
• Existing validation methods for sensors are insufficient for complex underwater environments.

Purpose of the Study:

• To present a methodology for evaluating novel physiological sensors for both land and underwater use.
• To address the need for reliable physiological assessment in diving.

Main Methods:

• Developed a custom data acquisition platform using Robot Operating System 2 (ROS 2).
• Conducted human subject testing in dry normobaric, dry hyperbaric, and shallow water immersion environments.
• Synchronized multiple heterogeneous data streams for comprehensive analysis.

Main Results:

• The methodology allows for systematic evaluation of sensor performance across different conditions.
• The ROS 2 platform enables scalable and reproducible validation of physiological monitoring technologies.
• Identified challenges in distinguishing sensor variability from true physiological changes underwater.

Conclusions:

• The proposed framework provides a robust approach to validating diving monitoring technologies.
• This methodology is crucial for advancing the development of reliable underwater physiological sensors.
• Facilitates a better understanding of physiological responses during diving.