Abstract
To support a healthy human mental state, controlling the environment is one of the best-known solutions. However, it is difficult to design an environmental control system because of the uniqueness of individual preferences and mental state fluctuations. Here, we propose “Buddy system” as an adaptive mental state support solution that controls devices in the environment, depending on the recognized user’s mental state at the time and how it could be improved, serving a role similar to a “buddy” to individuals. The recognition of mental states and the locus of actions to control one’s surrounding environment are implemented on the basis of a brain-derived theory of computation known as active inference and free-energy principles, which provide biologically plausible computations for perceptions and behavior in a changing world. For the generation of actions, we modify the general calculations of active inference to adjust to individual environmental preferences. In the experiments, the Buddy system sought to maintain the participants’ concentration while a calculation task was conducted. As a result, the task performance for most of the participants was improved through the aid of the Buddy system. The results indicated that the Buddy system can adaptively support to improve the mental states of individual users.
Highlights
RECENT advances in technology have made many aspects of human life easier
Even though information technology improves quality of life (QoL), a study showed that the stressors associated with telework can lead to a reduction in well-being [1], eventually diminishing work performance
We propose to apply a recent neurobiological theory called free energy principles (FEP) and a derived scheme called active inference [13], [14] to develop a mental support system that is able to recognize and improve a person’s mental state by controlling the environment while conforming to individual users
Summary
RECENT advances in technology have made many aspects of human life easier. For instance, working conditions for many may permanently shift to telework, aided by information technology, given the sudden demand in the wake of the COVID-19 pandemic. Overall, both the recognition and improvement of mental states by controlling the environment in real time are required to develop an effective mental support system. We propose to apply a recent neurobiological theory called free energy principles (FEP) and a derived scheme called active inference [13], [14] to develop a mental support system that is able to recognize and improve a person’s mental state by controlling the environment while conforming to individual users. Active inference schemes are just starting to be adopted in the robotics field to develop the capacity to estimate and control adaptive states, which are needed by robots operating in dynamically-changing and noisy real-world setting [18], [19].
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