A Meta-Bayesian Approach for Rapid Online Parametric Optimization for Wrist-based Interactions

Yi-Chi Liao, Ruta Desai, Alex M. Pierce, Krista E. Taylor, Hrvoje Benko, Tanya R. Jonker, Aakar Gupta

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

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Abstract

Wrist-based input often requires tuning parameter settings in correspondence to between-user and between-session differences, such as variations in hand anatomy, wearing position, posture, etc. Traditionally, users either work with predefined parameter values not optimized for individuals or undergo time-consuming calibration processes. We propose an online Bayesian Optimization (BO)-based method for rapidly determining the user-specific optimal settings of wrist-based pointing. Specifically, we develop a meta-Bayesian optimization (meta-BO) method, differing from traditional human-in-the-loop BO: By incorporating meta-learning of prior optimization data from a user population with BO, meta-BO enables rapid calibration of parameters for new users with a handful of trials. We evaluate our method with two representative and distinct wrist-based interactions: absolute and relative pointing. On a weighted-sum metric that consists of completion time, aiming error, and trajectory quality, meta-BO improves absolute pointing performance by 22.92% and 21.35% compared to BO and manual calibration, and improves relative pointing performance by 25.43% and 13.60%.
Original languageEnglish
Title of host publicationCHI '24: Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems
EditorsFlorian Floyd Mueller, Penny Kyburz, Julie R. Williamson, Corina Sas, Max L. Wilson, Phoebe Toups Dugas, Irina Shklovski
PublisherACM
Number of pages38
ISBN (Electronic)979-8-4007-0330-0
DOIs
Publication statusPublished - 11 May 2024
MoE publication typeA4 Conference publication
EventACM SIGCHI Annual Conference on Human Factors in Computing Systems - Honolulu, USA, Honolulu, United States
Duration: 11 May 202416 May 2024
https://chi2024.acm.org/

Conference

ConferenceACM SIGCHI Annual Conference on Human Factors in Computing Systems
Abbreviated titleACM CHI
Country/TerritoryUnited States
CityHonolulu
Period11/05/202416/05/2024
Internet address

Keywords

  • meta-learning
  • target selection
  • wrist-based interaction
  • human-in-the-loop optimization
  • meta-Bayesian optimization
  • Bayesian optimization
  • adaptive interface
  • calibration

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