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Personal Patient-Generated Data Visualizations for Diabetes Patients

Abstract : Patients with chronic conditions are usually advised or are self-motivated to track their health data at home and present this data to the healthcare providers during clinical visits. However, often these patient-generated data collections are large, complex and individual. These characteristics make it challenging and time-consuming for providers to understand this data during short clinical visits. We interviewed four diabetes patients and obtained a sample of their data collections to understand their personal lifestyle and perspectives on the process of tracking, recording, and presenting their data. Based on the information we gathered from patients in our study, we designed various personal visualizations tailored to them.
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https://hal.archives-ouvertes.fr/hal-01910365
Contributor : Charles Perin <>
Submitted on : Friday, November 23, 2018 - 7:50:12 PM
Last modification on : Wednesday, June 17, 2020 - 1:42:52 PM

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  • HAL Id : hal-01910365, version 1

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Fateme Rajabiyazdi, Charles Perin, Lora Oehlberg, Sheelagh Carpendale. Personal Patient-Generated Data Visualizations for Diabetes Patients. IEEE VIS 2018 Electronic Conference, Oct 2018, Berlin, Germany. ⟨hal-01910365⟩

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