A Machine Learning Approach to Automatic Phobia Therapy with Virtual Reality

Phobia is an anxiety disorder that affects 13% of the world’s population and it is manifested through an extreme and irrational fear toward objects or situations. A lot of research has been done on studying the contributing factors to the onset, development, and maintenance of phobias, underlying cognitive and behavioral processes, physical manifestation, and treatment methods. In this chapter, we present a new automated approach to phobias therapy, based on the integration of virtual reality technology, artificial intelligence, and affective computing—the ability of computational machines to recognize, adapt, and respond intelligently to human emotions. First, we introduce the results obtained by applying various machine learning algorithms for classifying the six basic emotions—anger, disgust, fear, joy, sadness, and surprise—based on the physiological recordings and self-reported ratings from the DEAP database. Then we present the stages of development and evaluation of a virtual environment for treating acrophobia that relies on gradual exposure to stimuli, accompanied by physiological signals monitoring. In a pilot experiment, we proposed a model for automatically adapting exposure scenarios according to the users’ emotional states, which has been tested on four acrophobic subjects. Here, the results obtained pass through a critical analysis in which we discuss the progress of the research and current limitations. Finally, we introduce the conceptual design of a system for phobias treatment that can be used as a therapy tool in clinical setups and also for home training, integrating virtual reality, machine learning, gamification techniques, biophysical data recording, emotion recognition, and automatic scenario adaptation. The system uses an intelligent virtual therapist that can understand emotions based on physiological signals, provides encouragement, and changes the level of exposure according to the user’s affective states.

@article{balan2021machine,
  title = {A Machine Learning Approach to Automatic Phobia Therapy with Virtual Reality},
  author = {Oana Cristina Balan and Alin Dragos Bogdan Moldoveanu and Marius Leordeanu},
  year = {2021},
  journal = {Modern Approaches to Augmentation of Brain Function (Springer)},
}