Improving Challenge/Skill Ratio in a Multimodal Interface by Simultaneously Adapting Game Difficulty and Haptic Assistance through Psychophysiological and Performance Feedback

Carlos David Rodriguez Guerrero, Kristel Knaepen, juan carlos fraile, Javier Perez Turiel, Valentin Garibay, Dirk Lefeber

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

In order to harmonize robotic devices with human beings, robots should be able to perceive important psychosomatic impact triggered by emotional states such as frustration or boredom. This paper presents a new type of biocooperative control architecture, which acts towards improving the challenge/skill relation perceived by the user when interacting with a robotic multimodal interface in a cooperative scenario. In the first part of the paper, open loop experiments determined which physiological signals were optimal to include in the feedback loop. These were HR, SCL and SCR frequency. In the second part of the paper, the proposed controller presents a two degree of freedom biocooperative architecture, simultaneously modulating game difficulty and haptic assistance through performance and psychophysiological feedback. With this setup, the perceived challenge can be modulated by means of the game difficulty and the perceived skill by means of the haptic assistance. A new metric (i.e., FlowIndex) is proposed to numerically quantify and visualize the challenge/skill relation. Results are contrasted with previous comparable published work and show that the new method obtained a higher FlowIndex (i.e., a better challenge/skill relation), and an improved balance between augmented performance and user satisfaction (higher level of Valence i.e., more enjoyable, more satisfactory experience).
Original languageEnglish
Article number242
Number of pages242
JournalFrontiers in Neuroscience
Volume11
Issue numberMAY
DOIs
Publication statusPublished - 1 May 2017

Keywords

  • Biocooperative
  • Biomechatronics
  • Haptics
  • Human-robot interaction
  • Multimodal interfaces
  • Psychophysiology
  • Rehabilitation robotics

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