Open Universiteit

Please use this identifier to cite or link to this item: http://hdl.handle.net/1820/8442
Title: Requirement analysis and sensor specifications – First version
Authors: Sharma, Puneet
Wild, Fridolin
Klemke, Roland
Helin, Kaj
Azam, Tre
Keywords: WEKIT
Requirements
Sensors
Wearables
Augmented Reality
Issue Date: 30-Sep-2016
Citation: Sharma, P., Wild, F. (Eds.), Klemke, R., Helin, K., & Azam, T. (2017, 4 July). Requirement analysis and sensor specifications – First version. WEKIT project delivarable D3.1. Retrieved from http://wekit.studiohangloose.it/wp-content/uploads/2017/06/WEKIT_D3.1.pdf
Abstract: In this first version of the deliverable, we make the following contributions: to design the WEKIT capturing platform and the associated experience capturing API, we use a methodology for system engineering that is relevant for different domains such as: aviation, space, and medical and different professions such as: technicians, astronauts, and medical staff. Furthermore, in the methodology, we explore the system engineering process and how it can be used in the project to support the different work packages and more importantly the different deliverables that will follow the current. Next, we provide a mapping of high level functions or tasks (associated with experience transfer from expert to trainee) to low level functions such as: gaze, voice, video, body posture, hand gestures, bio-signals, fatigue levels, and location of the user in the environment. In addition, we link the low level functions to their associated sensors. Moreover, we provide a brief overview of the state-of-the-art sensors in terms of their technical specifications, possible limitations, standards, and platforms. We outline a set of recommendations pertaining to the sensors that are most relevant for the WEKIT project taking into consideration the environmental, technical and human factors described in other deliverables. We recommend Microsoft Hololens (for Augmented reality glasses), MyndBand and Neurosky chipset (for EEG), Microsoft Kinect and Lumo Lift (for body posture tracking), and Leapmotion, Intel RealSense and Myo armband (for hand gesture tracking). For eye tracking, an existing eye-tracking system can be customised to complement the augmented reality glasses, and built-in microphone of the augmented reality glasses can capture the expert’s voice. We propose a modular approach for the design of the WEKIT experience capturing system, and recommend that the capturing system should have sufficient storage or transmission capabilities. Finally, we highlight common issues associated with the use of different sensors. We consider that the set of recommendations can be useful for the design and integration of the WEKIT capturing platform and the WEKIT experience capturing API to expedite the time required to select the combination of sensors which will be used in the first prototype.
URI: http://hdl.handle.net/1820/8442
Appears in Collections:3. TELI Deliverables and reports

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