An evaluation of the effectiveness of personalization and self-adaptation for e-Health apps

There are many e-Health mobile apps on the store, from to improve a user’s lifestyle mental coaching. Whilst these might consider user context when they give their interventions, prompts, and encouragements, still tend be rigid e.g., not using experience tailor themselves user. To better engage user, we have previously proposed Reference Architecture for enabling self-adaptation AI personalization in apps. In this work evaluate end users’ perception, usability, performance impact, energy consumption contributed by Architecture. We do so implementing compliant app conducting two experiments: study measurement-based experiment. Although limited number of participants, results our show that usability is similar control app. Users’ perception was found positively influenced compared group. Results experiment showed some differences measurements between The are, however, deemed minimal. Our experiments promising an implemented following This preliminary evidence use techniques can beneficial within domain