In recent years, due to the rise in availability of unstructured big data and technological affordances, there has been a proverbial “explosion” of research within the field of sentiment analysis and affective computing, facilitating the study of in-situ communicated emotion and its accurate detection at an unprecedented scale. Increasingly the emotional dimension and its key important role is being recognized in e-coaching, with attempts at its integration within such systems. This chapter reviews the predominant extant models for representing affect, as well as emotion related states relevant to older persons’ experiences, including the state-of-art for their automated detection and integration within e-coaching systems. Given the approaches available, we describe how the NESTORE system addresses emotion recognition, self-tracking and subsequent feedback intended to help older adults make sense of their affective experiences across their daily life, as well as the role it can play in holistic e-coaching systems. Finally, from the NESTORE experience, we draw recommendations about how future e-coaching system could be implemented in the future to include the emotional dimension.