An environment for motor skill transfer based on wearable haptic communication

• Published in: Personal and ubiquitous computing 2021-04, Vol.25 (2), p.411-435
• Main Authors: Camarillo-Abad, Hector M., Sánchez, J. Alfredo, Starostenko, Oleg
• Format: Article
• Language: English
• Subjects: Accelerometers; Automation; Coders; Communication; Computer Science; Critical components; Dance; Electronic devices; Haptic interfaces; Mobile Computing; Original Article; Personal Computing; Touch; User Interfaces and Human Computer Interaction; Wearable computers; Wearable technology
• ISSN: 1617-4909; 1617-4917
• DOI: 10.1007/s00779-020-01425-z

We propose an environment for assisting in the transfer of motor skills by supporting nonverbal communication with wearable haptic technology. The proposed setting comprises a human expert and several learners, all endowed with wearable devices. Learners benefit from the automated feedback obtained via wearable technology regarding a desired move relevant to a specific motor skill. Similarly, the expert benefits from automated means to provide instructions to the learner as well as from monitoring data provided by wearable devices. We focus on tactile communication as the basis for this interaction, thus supporting users who are not able to rely on other senses that are relevant to most motor skill-related tasks, such as sight and hearing. We discuss leader-follower dance as a motor skill context in order to instantiate and validate critical components of our skill transfer environment, using accelerometers and gyroscopes as the basis for sensing movements. In this particular scenario, our approach focuses on the haptic communication elements needed to perform a leader-follower dance, assessing movements by the learners in response to the intent of the expert. In order to validate our approach, we have prototyped and conducted experiments with the three critical components of our environment that enables tactile communication between experts and learners. Our development is informed by user research conducted with expert dance teachers, through which we gathered expert dance moves that resulted in a reference database that makes up one of the components that are critical to demonstrate the potential of our proposed environment. We also implemented a tactile encoder that is used to send movement instructions to learners through the sense of touch, as well as an autonomous classifier that uses the reference database as input. Overall, our results provide a roadmap for building an environment for skill transfer using nonverbal communication based on haptic wearable devices.