Puneet Sharma, Roland Klemke and Fridolin Wild
In this chapter, the authors focus on capturing an expert’s experiences using wearable sensors. For this, first, we outline a set of high level tasks that facilitate the transfer of experience from an expert to a trainee. Next, we define a mapping strategy to associate each task with one or more low-level functions such as: gaze, voice, video, body posture, hand/arm gestures, bio-signals, fatigue levels, haptic feedback, and location of the user in the environment. These low level functions are then decomposed to their associated state-of-the art sensors. Based on the requirements and constraints associated with the use cases from three different industrial partners, a set of sensors are proposed for the experience-capturing prototype. Finally, we discuss the attributes and features of the proposed prototype, along with its key challenges, constraints, and possible future directions.
This is the abstract of a book chapter. The full chapter is available here. Citation: Puneet Sharma, Roland Klemke and Fridolin Wild (2019): Experience Capturing with Wearable Technology in the WEKIT project, In: Buchem, Klamma, Wild (Eds.): Perspectives on Wearable Enhanced Learning (WELL): Current Trends, Research, and Practice, Springer.
