  Machine learning (ML) is the fastest growing field in computer science and
healthcare, providing future benefits in improved medical diagnoses, disease
analyses and prevention. In this paper, we introduce an application of
interactive machine learning (iML) in a telemedicine system, to enable
automatic and personalised interventions for lifestyle promotion. We first
present the high level architecture of the system and the components forming
the overall architecture. We then illustrate the interactive machine learning
process design. Prediction models are expected to be trained through the
participants' profiles, activity performance, and feedback from the caregiver.
Finally, we show some preliminary results during the system implementation and
discuss future directions. We envisage the proposed system to be digitally
implemented, and behaviourally designed to promote healthy lifestyle and
activities, and hence prevent users from the risk of chronic diseases.
