A Multimodal Deep Log-Based User Experience (UX) Platform for UX Evaluation

Autor: Anees Ul Hassan, Hafiz Syed Muhammad Bilal, Wajahat Ali Khan, Muhammad Afzal, Tae Ho Hur, Sungyoung Lee, Jae Hun Bang, Jamil Hussain
Rok vydání: 2018
Předmět:
user experience measurement
Computer science
galvanic skin response
02 engineering and technology
lcsh:Chemical technology
Biochemistry
Article
050105 experimental psychology
Field (computer science)
Analytical Chemistry
User experience design
Human–computer interaction
0202 electrical engineering
electronic engineering
information engineering
lcsh:TP1-1185
0501 psychology and cognitive sciences
EEG
Electrical and Electronic Engineering
Instrumentation
facial expression
eye-tracking
user experience platform
business.industry
mix-method approach
05 social sciences
user experience evaluation
interaction tracker
self-reporting
Atomic and Molecular Physics
and Optics
User Research
Triangulation (geometry)
Analytics
User experience evaluation
Eye tracking
020201 artificial intelligence & image processing
business
Zdroj: Sensors (Basel, Switzerland)
Sensors, Vol 18, Iss 5, p 1622 (2018)
Sensors; Volume 18; Issue 5; Pages: 1622
ISSN: 1424-8220
DOI: 10.3390/s18051622
Popis: The user experience (UX) is an emerging field in user research and design, and the development of UX evaluation methods presents a challenge for both researchers and practitioners. Different UX evaluation methods have been developed to extract accurate UX data. Among UX evaluation methods, the mixed-method approach of triangulation has gained importance. It provides more accurate and precise information about the user while interacting with the product. However, this approach requires skilled UX researchers and developers to integrate multiple devices, synchronize them, analyze the data, and ultimately produce an informed decision. In this paper, a method and system for measuring the overall UX over time using a triangulation method are proposed. The proposed platform incorporates observational and physiological measurements in addition to traditional ones. The platform reduces the subjective bias and validates the user’s perceptions, which are measured by different sensors through objectification of the subjective nature of the user in the UX assessment. The platform additionally offers plug-and-play support for different devices and powerful analytics for obtaining insight on the UX in terms of multiple participants.
Databáze: OpenAIRE
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