Symptoms during cancer treatment are common, compromise patient quality of life and ability to tolerate treatment, and often go undetected at clinic visits. This project combines smartphone and wearable sensor data with machine learning to remotely monitor symptoms during chemotherapy and to develop a system that automatically recommends patient-provider contact when severe symptoms are detected. Supplemental work aims to identify patient- and provider-perceived barriers, benefits, and preferences related to how mobile sensor tools and data could be used to support patient-provider communication during chemotherapy and how to best support patient and provider use of these digital tools. Findings will address a gap in the literature about how wearable devices and other passive sensors might impact patient-provider communication and will inform future work integrating mobile sensing into clinical cancer care.
(Funding Source: NHI/NCI. R37CA242545, R37CA242545-05S1)