State-Space Modeling and Fuzzy Feedback Control of Cognitive Stress

“Distress” or a substantial amount of stress may decrease brain functionality and cause neurological disorders. On the other hand, very low cognitive arousal may affect one’s concentration and awareness. Data collected using wrist-worn wearable devices, in particular, skin conductance data, could be used to look into one’s cognitive-stress-related arousal. Our goal here is to present excitatory and inhibitory wearable machine-interface (WMI) architectures to control one’s cognitive-stress-related arousal state. We first present a model for skin conductance response events as a function of environmental stimuli associated with cognitive stress and relaxation. Then, we perform Bayesian filtering to estimate the hidden cognitive-stress-related arousal state. We finally close the loop using fuzzy control. In particular, we design two classes of controllers for our WMI architectures: (1) an inhibitory controller for reducing arousal and (2) an excitatory controller for increasing arousal. Our results illustrate that our simulated skin conductance responses are in agreement with experimental data. Moreover, we illustrate that our fuzzy control can successfully have both inhibitory and excitatory effects and regulate one’s cognitive stress. In conclusion, in a simulation study based on experimental data, we have illustrated the feasibility of designing both excitatory and inhibitory WMI architectures. Since wearable devices can be used conveniently in one’s daily life, the WMI architectures have a great potential to regulate one’s cognitive stress seamlessly in real-world situations.