HEALFUL - Internet of Health Things Platform to Monitor Quality of Life

Abstract

Monitoring people’s Quality of Life (QoL) has attracted interest due to the health benefits of an accurate QoL analysis, such as early healthcare interventions. However, most instruments to assess QoL are questionnaires, and their application is time-consuming, intrusive, and error-prone. This work proposes an Internet of Health Things (IoHT) platform called Healful that applies Machine Learning to infer users’ QoL. A case study with 44 participants was conducted for six months, and during this evaluation, health data were collected daily through smartphones and wearables. These data were processed and compiled into two datasets with 1,373 instances each. Next, five Machine Learning models were built using 10-fold cross-validation to estimate participants’ QoL. Random Forest (RF) had the best results considering the Root Mean Squared Error (RMSE). RF got an RMSE of 7.8618 for the physical domain and 7.4591 for the psychological domain.