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This paper presents 'Expression' -an integrated assistive solution using Google Glass. The key function of the system is to enable the user in perceiving social signals during a natural dyadic conversation. The design and implementation of the system addressed a number of technical and research challenges -video acquisition and communication over Wi-Fi, efficient detection and tracking of faces, overheating of Google Glass, robust detection of facial features and modeling behavioral expressions, and feedback system for perceiving social signals. Performance evaluation was conducted to ensure the completeness and generalizability of models. Furthermore,usability studies were performed with ten (10) subjects (six visually impaired and four blind-folded) to illustrate the utility of the 'Expression'. Subjective evaluation of Expression was performed using a five (5) point Likert Scale and was found to be excellent (4.383).

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The lack of ability to perceive emotions and affective states is a setback for people who are blind or visually impaired in professional and social communications. Towards developing assistive technology solution in facilitating natural dyadic conversations for people with such disability, this paper describes the development of a smart phone based system called interactive mobile affect perception system (iM AP S) for prediction of affective dimensions (valence-arousal-dominance). The proposed solution utilizes an Android platform in conjunction with a wireless network to build a fully integrated iM AP S. Empirical analyses were conducted to measure the efficacy and utility of the proposed solution. It was found that the proposed framework can predict affect dimensions with good accuracy (Maximum Correlation Coefficient for valence: 0.68, arousal: 0.71, and dominance: 0.67) in natural dyadic conversation. The overall minimum and maximum response times are (181 milliseconds) and (500 milliseconds), respectively.

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