Multi-sensor fusion for biomechanical analysis: evaluation of dynamic interactions between self-contained breathing...

Area of Science:

• Biomechanics
• Ergonomics
• Wearable Technology

Background:

• Firefighter health is impacted by Self-Contained Breathing Apparatus (SCBA) use.
• Understanding the dynamic interactions between SCBA and the human torso is crucial for assessing health risks and improving equipment design.

Purpose of the Study:

• To quantify the three-dimensional (3D) dynamic interactions between SCBA and the human torso using multi-inertial sensor fusion.
• To validate the accuracy of the sensor fusion technique against a 3D motion capture system.

Main Methods:

• Six volunteer firefighters participated in walking and running experiments on a treadmill while wearing SCBA.
• Multi-inertial sensor fusion technology was employed to calculate interaction forces and moments.
• Data from the sensor fusion technique were validated using a 3D motion capture system.

Main Results:

• The multi-inertial sensor fusion technique demonstrated good agreement with the 3D motion capture system.
• Relative root mean square errors (RMSEs) for predicted forces and moments were below 9.4%.
• Peak pack forces reached up to 150 N, exceeding the SCBA's weight during carriage.

Conclusions:

• The multi-inertial sensor fusion technique effectively evaluates 3D dynamic SCBA-torso interactions.
• This technology provides a scientific basis for firefighter health monitoring.
• The findings support ergonomic optimization of SCBA systems for improved firefighter safety and performance.