XAmI Applications to Telemedicine and Telecare

Telemedicine and telecare are another important application of ambient intelligence (AmI). This chapter first summarizes the applications of artificial intelligence (AI) in telemedicine and telecare. Since some of these AI applications are difficult to understand or communicate with patients, various explainable ambient intelligence (XAmI) techniques have been applied, such as shape-added explanation value (SHAP) analysis and locally interpretable model-agnostic explanation (LIME) to overcome such difficulties. Telemedicine services for type-II diabetes diagnosis are taken as an example to illustrate such applications. Several issues with existing XAmI applications in telemedicine and telecare are then discussed. It is worth noting that after SHAP analysis, some important attributes may be difficult to measure by patients themselves, which affects the utility of telemedicine or telecare applications.