Facial expression recognition in ageing adults: from lab to ambient assisted living

This paper introduces an application that uses a webcam and aims to recognise emotions of ageing adults from their facial expression. Six basic emotions (Happiness, Sadness, Anger, Fear, Disgust and Surprise) as well as a Neutral state are distinguished. Active shape models are applied for feature extraction, the Cohn–Kanade, JAFFE and MMI databases are used for training, and support vector machines ($$\nu$$ν-SVM) are employed for facial expression classification. These six basic emotions are classified into three categories (Happiness, Negative-Emotion and Surprise), as Sadness, Anger, Fear and Disgust have been grouped into a single expression. The new three categories are found to be relevant for the purpose of detecting abnormalities in the ageing adult’s mood state. In the future, we will transfer the experience in a lab/research setup to a real ambient assisted living environment, which is the elderly person’s home. The application is devised to be the starting point to enhance the mood of the elderly people living alone at their homes by external stimuli.