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Machine Learning and Therapeutic Strategies in VR

Published: 13 February 2020 Publication History

Abstract

Cognitive behavioral therapy is one of the few treatment options for individuals suffering from psychological and physiological abnormalities like phobias, post-traumatic stress, stuttering, and anxiety. They are expensive in both cost and time, and are often difficult to evaluate for effectiveness. Virtual Reality (VR) can ameliorate ineffective and costly therapies, because it effectively reproduces stressful environments, and is mobile enough to be used at home. However, psychological therapies are supervised by highly trained psychiatrists whose years of experience help them diagnose patients' problems in a personalized manner. Can we use Machine Learning (ML) to glean information from patients that allow for such tailored-made therapy training for VR systems? Machine Learning of subject training history and behavior allows the system to adapt therapies to individual levels and needs. Machine Learning of sensor data that provide details of patient stress levels in time gives us moment-to-moment responses that can be used to customize their training in terms of difficulty and responsiveness. We detail use of these ML strategies in the case of helping stutterers cope with immanent episodes of public and social speaking using VR with systematic desensitization. 23 stutterers and 4 speech pathologists participated in our user studies, which refined our prototype to lower relaxation fidelity, reduce scene blur, and improve voice efficacy. Use of Artificial Intelligence (AI) in VR technology serves to enable customization and adaptive training while maintaining the ease-of-use and comparatively low cost over traditional therapeutic strategies. This research opens up possibilities of using ML to customize levels, encounters, and environmental complexity in interactive experiences utilizing biometrics and in-game behavior.

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Cited By

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  • (2024)Unleashing the Potential: A Holistic Approach to Adaptive Learning in Virtual RealitySmart Mobile Communication & Artificial Intelligence10.1007/978-3-031-54327-2_4(40-52)Online publication date: 27-Feb-2024
  • (2021)A Pilot Study of Indian Ragas-Based Music Therapy for Enhancement of Chronic Patient Health ConditionAdvances in Speech and Music Technology10.1007/978-981-33-6881-1_27(325-339)Online publication date: 1-Jun-2021

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ARTECH '19: Proceedings of the 9th International Conference on Digital and Interactive Arts
October 2019
571 pages
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 February 2020

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Author Tags

  1. Machine learning
  2. immersive therapy
  3. stuttering
  4. virtual reality

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ARTECH 2019

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ARTECH '19 Paper Acceptance Rate 95 of 174 submissions, 55%;
Overall Acceptance Rate 128 of 238 submissions, 54%

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Cited By

View all
  • (2024)Unleashing the Potential: A Holistic Approach to Adaptive Learning in Virtual RealitySmart Mobile Communication & Artificial Intelligence10.1007/978-3-031-54327-2_4(40-52)Online publication date: 27-Feb-2024
  • (2021)A Pilot Study of Indian Ragas-Based Music Therapy for Enhancement of Chronic Patient Health ConditionAdvances in Speech and Music Technology10.1007/978-981-33-6881-1_27(325-339)Online publication date: 1-Jun-2021

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