A Lower Limb Wearable Exosuit for Improved Sitting, Standing, and Walking Efficiency

Xiaohui Zhang, Enrica Tricomi, Xunju Ma, Manuela Gomez-Correa, Alessandro Ciaramella, Francesco Missiroli, Luka Mišković, Huimin Su, Lorenzo Masia

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Sitting, standing, and walking are fundamental activities crucial for maintaining independence in daily life. However, aging or lower limb injuries can impede these activities, posing obstacles to individuals’ autonomy. In response to this challenge, we developed the LM-Ease, a compact and soft wearable robot designed to provide hip assistance. Its purpose is to aid users in carrying out essential daily activities such as sitting, standing, and walking. The LM-Ease features a fully-actuated tendon-driven system that seamlessly transitions between assistance actuation profiles tailored for sitting, standing, and walking movements. This device provides the user with gravity support during stand-to-sit, and offers hip extension assistance pulling force during sit-to-stand and walking. Our preliminary results show that with the LM-Ease, healthy young adults (n = 8) had significantly lower muscle activation: average reduction of 15.6% during stand-to-sit and 17.8% during sit-to-stand. Furthermore, with LM-Ease, participants demonstrated a 12.7% reduction in metabolic cost during ground walking. These evidences suggest that the LM-Ease holds potential in reducing muscular activation and energy expenditure during these fundamental daily activities. It could serve as a valuable tool for individuals seeking assistance in enhancing lower limb mobility, thereby bolstering their independence and overall quality of life.

Original languageEnglish
JournalIEEE Transactions on Robotics
DOIs
StateAccepted/In press - 2024

Keywords

  • Adaptive Lower Limb Assistance Control
  • Machine Learning
  • Wearable Robotics; Exosuits

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