ROBOMECH Journal (Jan 2023)

Soft actuators-based skill training wearables: a review on the interaction modes, feedback types, VR scenarios, sensors utilization and applications

  • Priyanka Ramasamy,
  • Enrique Calderon-Sastre,
  • Gunarajulu Renganathan,
  • Swagata Das,
  • Yuichi Kurita

DOI
https://doi.org/10.1186/s40648-023-00239-x
Journal volume & issue
Vol. 10, no. 1
pp. 1 – 15

Abstract

Read online

Abstract Dexterity training helps improve our motor skills while engaging in precision tasks such as surgery in the medical field and playing musical instruments. In addition, post-stroke recovery also requires extensive dexterity training to recover the original motor skills associated with the affected portion of the body. Recent years have seen a rise in the usage of soft-type actuators to perform such training, giving higher levels of comfort, compliance, portability, and adaptability. Their capabilities of performing high dexterity and safety enhancement make them specific biomedical applications and serve as a sensitive tools for physical interaction. The scope of this article discusses the soft actuator types, characterization, sensing, and control based on the interaction modes and the 5 most relevant articles that touch upon the skill improvement models and interfacing nature of the task and the precision it demands. This review attempts to report the latest developments that prioritize soft materials over hard interfaces for dexterity training and prospects of end-user satisfaction.

Keywords