Identification of Shoulder Joint Clearance in Space Suit Using Electromagnetic Resonant Spiral Proximity Sensor for Injury Prevention

Abstract Shoulder injury is one of the most common phenomena that occurs for astronauts when they are training for space flight. During training, astronauts are required to wear a full space suit, known as the extravehicular mobility unit (EMU). The major component of the EMU that attributes to shoulder injury is the hard upper torso (HUT). This component is primarily comprised of a rigid fiberglass shell with metal scye bearing joints. Placement of the scye bearing joints for the shoulders does not allow for enough range of motion, which can lead to rotator cuff tears. Additionally, shoulder injury also occurs when donning the suit and training in the Neutral Buoyancy Laboratory (NBL). The EMU currently does not contain any provision to account for this biomechanical interference to adjust for optimum range of motion. The objective of this paper is to propose a novel detection scheme using a wearable electromagnetic resonant spiral sensor that could allow for a quantitative value of proximity between the shoulder and the metallic scye bearing joint of the HUT. The presence of the liquid cooling and ventilation garment (LCVG) is also investigated in the environment to validate that accuracy of proximity detection is still achieved. Optimal location for the wearable proximity sensor would be on top the LCVG around the shoulder joint where the scye bearing joints are more likely to meet the shoulder. The first study investigated the ability of the wearable proximity sensor to detect the distance from an aluminum sheet (representing the scye bearing joint) with no LCVG present, while the second study incorporated the wearable proximity sensor on top of the LCVG for a simulated suit environment. Four scenarios were performed with two wearable proximity sensors, resonating at different frequencies, placed in an environment with and without the LCVG. Ten repeated tests were used to train and an additional ten tests to validate a regression learning algorithm to predict the distance for each scenario. Experimental results indicated that the wearable proximity sensors in both the open air and with the LCVG have enough accuracy to provide a root mean square error (RMSE) of approximately 1 mm or less. This accuracy is sufficient for use in the space suit to provide quantitative information for suit fit. The use of this proximity detection scheme incorporated into the suit will offer previously unknown information regarding suit fit, while also influencing optimum fit for future suit generations.