Adaptive affective response identification for hearing threshold detection

Emotional arousal, or affective patterns, can be probed using observable bioelectric signals, in particular using the fluctuations of electroencephalographic potentials from the human scalp. Hearing impairment related to increased threshold of audio tone detection may cause the loss of intelligibility of speech resulting in an innate automatic emotional response. An adaptive support vector machine can be trained to identify a subject's unique affective response based upon an audiogram hearing test. This paper presents the efficacy of our model, initial SVM classification data, and discusses potential application.