title: An evidence-based toolset to capture, measure and assess emotional health.
abstract: We present: (1) an automated telephone check-in system to capture emotional health, based on automatic emotion classification, crowd-sourcing, and the experience sampling method; (2) a method that combines acoustic-based and perception-based emotion classifiers to maximize the likelihood of correctly identifying the emotion in a speech recording; (3) an evidence-based toolkit to measure and assess emotional health; and (4) the results of three experimental trials held in 2010 and 2011: (a) English speaking members of Alcoholics Anonymous, (b) English and French speaking general population, and (c) English speaking Opioid addicts undergoing Suboxone maintenance treatment. Emotional health can be defined as the ability to express emotions, identify one's own emotions, relate to other people's emotions, and to live life with predominantly positive emotions. Emotional health plays a major role in addiction treatment and Cognitive Behavioral Therapy (CBT).
authors.affiliation: Génie logiciel et des TI, École de technologie supérieure, Université du Québec, Canada. emotiondetect@gmail.com
authors.forename: Edward
authors.initials: E
authors.lastname: Hill
authors.forename: Pierre
authors.initials: P
authors.lastname: Dumouchel
authors.forename: Charles
authors.initials: C
authors.lastname: Moehs
mesh_terms: D001331:Automation; D015928:Cognitive Behavioral Therapy / Q000379:methods; D003142:Communication; D004644:Emotions; D006801:Humans; D008603:Mental Health; D013060:Speech; D019966:Substance-Related Disorders / Q000523:psychology; D017216:Telemedicine / Q000379:methods; D013689:Telephone