Evaluating Lumbar Shape Deformation With Fabric Strain Sensors

Area of Science:

• Biomechanics
• Wearable technology
• Space suit engineering

Background:

• Pressurized space suits pose injury risks during extravehicular activity (EVA) due to physical interactions and poor fit.
• Reduced performance and excessive body contact within suits can lead to astronaut injuries.
• A wearable system is needed to accurately measure body motion inside space suits.

Purpose of the Study:

• Develop a multifactor statistical model to predict torso body shape changes and lumbar motion during suited movement.
• Utilize fabric strain sensors placed on the body to capture human motion within space suits.
• Enhance the study of suit-related contact and inform the development of injury countermeasures.

Main Methods:

• An array of flexible strain sensors was attached to 12 male participants.
• Participants adopted specific static lumbar postures while 3D body scans and sensor data were collected.
• A predictive model was developed using sensor signals to estimate body shape, validated via cross-validation.

Main Results:

• The torso shape model achieved an average root mean square error (RMSE) of 2.02 cm.
• The model accurately replicated subtle soft tissue deformations, including skin folding and bulges.
• Prediction accuracy was consistent across different posture types.

Conclusions:

• This sensor-based method offers a valuable tool for space suit testing and analysis.
• Findings will drive the development of injury countermeasures and enhance space suit fit assessments.
• The technique is applicable to ergonomic evaluations in field settings beyond space exploration.