Subject independent agitation detection

The need to automate the detection of agitation for dementia patients is a major requirement for caregivers. This research aims at sensing and recognizing negative emotions specifically ldquostressrdquo for patients with dementia. An autonomous multi-sensory device has been developed to achieve automatic assessment of agitation and to control stimulation that will reduce the agitation level automatically. The focus of this paper is the agitation detection algorithm. Three vital signs are monitored for agitation detection: the Heart Rate (HR) the Galvanic Skin Response (GSR) and Skin Temperature (ST). These measures are fed into an SVM based learning machine. Results show accurate detection of agitation, quick adaptation to the subject and a strong correlation between the physiological signals monitored and the emotional states of the subjects. The result is a learning algorithm that is ldquoSubject-Independentrdquo.