Smartphone Sensors for Monitoring Cancer-Related Quality of Life: App Design, EORTC QLQ-C30 Mapping and Feasibility Study in Healthy Subjects

Abstract

Quality of life (QoL) indicators are now being adopted as clinical outcomes in clinical trials on cancer treatments. Technology-free daily monitoring of patients is complicated, time-consuming and expensive due to the need for vast amounts of resources and personnel. The alternative method of using the patients’ own phones could reduce the burden of continuous monitoring of cancer patients in clinical trials. This paper proposes monitoring the patients’ QoL by gathering data from their own phones. We considered that the continuous multiparametric acquisition of movement, location, phone calls, conversations and data use could be employed to simultaneously monitor their physical, psychological, social and environmental aspects. An open access phone app was developed (Human Dynamics Reporting Service (HDRS)) to implement this approach. We here propose a novel mapping between the standardized QoL items for these patients, the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30) and define HDRS monitoring indicators. A pilot study with university volunteers verified the plausibility of detecting human activity indicators directly related to QoL.

Mining Facebook data for Quality of Life assessment

“…sensor and GPS data, telephone calls and SMS logs; e.g. Asensio-Cuesta et al 2019;Cote et al 2017Cote et al , 2019Messner et al, 2019), while research investigating the link between SNS activity data and QoL is scant. Still, given the widespread use of SNS in the general population, studies exploring the association between indicators of SNS use and QoL could provide useful insights and foster the development of tools aimed at monitoring individual (and possibly group-level) QoL in an unobtrusive way, thus potentially reducing the barrier to screening for large populations.…”

Location Based Indoor and Outdoor Lightweight Activity Recognition System

“…Several studies have already verified that analysing people's out of home behavior (which activities they perform, which are their mobility patterns, etc.) could provide insights about their cognitive status [56,57], quality of life [58] or even mood [59].…”

Recent trends in smartphone-based detection for biomedical applications: a review

“…The sensitivity and specificity of classification in the case of remote specialists are 0.9259 and 0.8667, respectively, whereas for CNN, it is found to be 0.8500 and 0.8875 [ 68 ]. Also, the development is made in the direction of assessing the quality of life of cancer patients with the help of a human dynamic reporting service (HDRS) application, which monitors the activities of the patients based on the data acquired by their mobile phone sensors [ 69 ]. Furthermore, in a study conducted by Alzubaidi et al (2019), a CNN model DFU-QNET was used to grade the severity of foot ulcers in diabetic patients into two classes known as normal and abnormal.…”