Cognitive Game for OCD Effects Minimisation Using IoT

Smart homes using IoT devices for resident monitoring and/or appliances metering, aim to optimise the home environment and provide assistance to health practitioners, when it comes to the elderly or people with certain diseases. Recently, research has moved towards integrating sensory outputs other than visibility and audio, with sensors aiming to mimic all five senses of the human. In this paper, we take onboard an IoT installation scenario with cameras, RFID tags and an electronic nose to capture repetitive behaviors of home residents suffering from Obsessive Compulsive Disorder (OCD) episodes. We propose the setup of such an IoT system, which utilises visible, movement and smell sensors. We devise an OCD metric to classify the behavior of the resident and we give a Hidden Markov Model (HMM) algorithm to classify and predict the behavior based on the metric. Finally, when OCD behavior is identified, we provide a game-theoretic algorithm for the patient to play, in order to minimise the OCD intrusive thoughts.