Pressure monitoring based identification of the EOD suit–human interface load distribution

Abstract

Soldiers working in the field of explosive ordnance disposal (EOD) wear cumbersome personal protective equipment (PPE) that may affect their performance in the field, limit their mobility, and cause discomfort. The objective of this study was to develop a test methodology to identify the relationship between EOD suit interface loads and mission-critical performance metrics. The physical interactions between an EOD suit and human subjects were monitored using a distributed pressure sensor network to investigate the interface load distribution during EOD-related physical positions and activities. More specifically, a Med-Eng brand Model EOD 8 suit was utilized to evaluate shoulder discomfort and leg mobility restriction. Thirty-four college aged adults of varying athletic abilities completed a test course and walked on a treadmill for 2 min while wearing the EOD 8. Demographic information was collected before testing via a survey and qualitative observations were collected at the end of testing with a questionnaire. After each test course repetition, participants ranked their perceived exertion using the Borg scale. Overall, the time it took participants to complete the test course increased by 17% and participants experienced a 60% increase in perceived exertion while wearing the EOD 8. The region that experienced the most pain and discomfort was the top of the shoulders (59%) and there was a negative correlation (r = − 0.5, p < 0.05) between participants' body mass index (BMI) and the max shoulder pressure. The groin protector was found to restrict hip rotation when the subject squatted to pick up an object, producing a pressure 30-times higher than without the EOD 8. These results suggest that a range of motion evaluation method for EOD suits and other protective ensemble can be successfully developed using a combination of user feedback and strategically placed pressure sensors. This study implements the largest pressure region ever recorded on the human body and is the first of its kind to investigate the movement restriction of PPE for various practical tasks.

Invariant Extended Kalman Filtering for Human Motion Estimation with Imperfect Sensor Placement

“…Besides the stance-foot location, the pose (position and orientation) and velocity of the body (e.g., pelvis or chest) are also of particular interest in gait analysis and wearable robot controller design, because they can be used to study postural balance and gait stability [10]. Body pose and velocity have been estimated through the nonlinear forward kinematics between the stance foot, which is obtained through accurate initialization and contact detection, and the body frame [11].…”