R-HEXSuit
: Towards a Resistive Exosuit for Hypogravity Adaptation and Muscle Health Maintainance in Space

Student thesis: Doctoral ThesisDoctor of Philosophy (PhD)

Abstract

As space missions to the Moon and Mars become a reality, maintaining astronauts’ musculoskeletal health in hypogravity remains a significant challenge. Prolonged exposure to hypogravity (gravity lower than Earth’s) leads to bone demineralisation and muscle atrophy, which jeopardises astronauts’ health and reduces performance. Current countermeasures, such as exercise and pharmacological interventions, have shown limited effectiveness.

This thesis presents the development of a prototype soft resistive exosuit designed to counteract muscle atrophy in astronauts during long-duration space missions, namely the R-HEXsuit. The research focuses on several key innovations: the scalability and atomic packing of Bubble Artificial Muscles (BAMs) which are the actuators of choice for the proposed exosuit, the creation of control strategies for dynamic scenarios, the introduction of novel anchoring methods for soft actuators, and the development of the first prototype of the R-HEXsuit.

Firstly, the thesis explores how the force-contraction characteristics of BAMs scale with their size, demonstrating that smaller BAMs provide higher force per unit area and faster response times than larger counterparts. A novel packing method inspired by crystalline structures of molecules is proposed, which enhances the performance of multi-actuator configurations by optimising their arrangement for high tensile force or contraction depending on the configuration chosen, while reducing system complexity and volume.

Next, control strategies for BAMs are examined, including the use of PID controllers for precise force and displacement management in dynamic scenarios, both linearly and while assisting a swinging leg in simulated hypogravity. The results suggest that BAMs can develop the necessary force and contraction in simulated hypogravity conditions, effectively responding to control inputs at pressures suitable for wearable applications.

Following this, a novel device , the MetaFit sleeve, is introduced to tackle the challenge of inefficient load transmission in soft exosuits. This device utilises a bi-stable auxetic cuff that dynamically adapts to the body's movements, significantly enhancing force transmission while ensuring comfort and ease of use. While currently at the proof-of-concept stage, the sleeve also incorporates an auxetic underactuated bending structure, designed to provide targeted assistance or resistance during arm flexion.

Finally, the R-HEXsuit is presented, a resistive exosuit designed to introduce Earth-like loads on the lower limbs muscles in reduced gravity environments. Experiments performed in simulated hypogravity (at the LOcomotion in Other Planets facility of the University of Milan) demonstrate that the suit effectively increases metabolic expenditure and muscle activation of the targeted muscles during walking tasks, closely replicating the conditions of walking on Earth. The exosuit maintains natural gait patterns and user mobility, making it a practical solution for counteracting the effects of long-term hypogravity exposure on astronauts.

This thesis lays the foundation for future advancements in wearable technology, offering a new approach to astronaut health management and rehabilitation through innovative design and engineering of soft exosuits. By addressing current limitations and exploring new avenues for development, this work aims to revolutionise the field of wearable devices, extending their applications beyond space missions to include rehabilitation, strength training, and everyday assistance.
Date of Award18 Mar 2025
Original languageEnglish
Awarding Institution
  • University of Bristol
  • University of the West of England
SupervisorJonathan M Rossiter (Supervisor), Richard Suphapol Diteesawat (Supervisor) & Helmut Hauser (Supervisor)

Keywords

  • soft robotics
  • exosuit
  • exoskeleton
  • Space exploration
  • wearable robotics
  • Human factors

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