Intelligent Biofeedback using an Immersive Competitive Environment

In this paper we introduce the idea of enhancing biofeedback by placing it within a competitive virtual gaming environment. This is an example of a new concept to be called ‘Affective Feedback’. In essence this term means that the computer is an active intelligent participant in the biofeedback loop. The relationship between human and machine is now two way the computer is affected by the state of the human and vice versa. We demonstrate the concept through a simple video game where two people compete in a race based on the relaxation levels of the players. The competitive virtual environment affects the players’ level of relaxation while the levels of relaxation determine the outcome of the game. The person most relaxed wins the game. INTRODUCTION BIOFEEDBACK TO AFFECTIVE FEEDBACK: If a person is provided with real-time information about a certain aspect of their physiology, they can determine the way that their mental changes affect this state. Over time, the person can learn, consciously or subconsciously, how to control this aspect of their “bio-state. ” This process is known as biofeedback and can be used to gain mental control over brainwaves, blood flow, muscular action, and many other physiological events. For example, many studies have shown that, over time, people can gain control of their brainstate (as measured by an electroencephalogram [EEG]) when given a graphical or auditory representation of their EEG. Biofeedback has many clinical applications and has been used to treat a wide range of conditions, from attention deficit disorder(ADD) to addiction. Affective Feedback is a hybrid of traditional biofeedback and “affective computing,” a term coined by Rosalind Picard meaning “computing that.arises from or deliberately influences emotion. ” The basic idea is to make the framework in which the biofeedback takes place directly influence and affect the “bio-state” of the user. In other words, the person is not only affected by the feedback information about their bio-state, but also by the way that it is presented. An example of a simple way of achieving this goal will be presented in this paper. We have created a two-player competitive racing game which is based on the players’ level of relaxation, as measured by their galvanic skin response. The basic idea is simple: As a player relaxes, their character moves faster. Therefore, the person who relaxes most wins the race. In some sense, this is traditional biofeedback: The person is given feedback information on their level of relaxation by the action of their dragon. However, the key difference is that the environment is designed to affect the user. First of all, the game takes place in a visually stunning virtual 3-D world. This type of environment has been shown to draw more of the user's attention and make the feedback more effective. In addition, the game provides a much more appealing and effective “reward” for achieving the correct “bio-state. ” Studies have shown that more “meaningful” reinforcement makes biofeedback more effective, especially in children. Finally, and most important, the competitive framework has a profound affect on the mental state of the user. Competitive games are normally associated with tension and stress, so the player must learn how to override this tendency and learn not only how to relax, but how to relax in a tense environment. This game demonstrates a small but important step into the next age of intelligent, ubiquitous computers: Computers with the ability to recognize, react to, and affect our physiological state in a meaningful way. Currently, we are working to expand the concept by adding other bio-state measurements and creating a more “intelligent” interface. The hope is that, in the future, we will be able to create a game in which the computer actually “learns” which environments foster different mental states in individual users, and uses this information to affect and reinforce the user’s target “bio-state. ” In some sense, the computer would be performing its own biofeedback as it is changing the environment and recording how the user reacts. Traditional biofeedback is a standard feedback loop: The user learns to control their state based on information presented on a computer. Affective feedback creates another loop: The computer learns how different environments and frameworks affect the user and adjusts accordingly. It is important to note that, just as biofeedback can be administered without this new loop, affective feedback is possible without traditional biofeedback. If the computer “knows” how different situations and environments can affect the user’s state, it can change based on the needs of the user. This research has large potential for interesting expansion and, given the clinical applications of biofeedback, a good chance of genuinely improving peoples’ lives.