A Smartwatch Based system for Monitoring Fluid Consumption of End Stage Kidney Patients

Open Access
Conference Proceedings
Authors: Mehdi BoukhechbaMingyue TangBrendan BowmanJamie ZoellnerEmaad Abdel-Rahman

Abstract: Background:End Stage Kidney disease (ESKD) patients must follow unique dietary restrictions. The most onerous of these is the need to restrict fluid intake. The ramifications of poor fluid control include increased mortality and morbidities, frequent hospitalizations with diagnoses of heart failure and pulmonary edema, increased hospital length of stay, and increased total cost of care. Fluid intake control is a bedrock component of treatment for ESKD Patients, but continues to be a major challenge for patients, healthcare providers, and organizations. The ramifications of poor fluid control include increased mortality and morbidities, frequent hospitalizations and increased total cost of care. The goal of this work is to investigate the feasibility of leveraging smartwatch technology to monitor fluid consumption of ESKD patients outside of the clinic. Adequate assessment of fluid intake of patients with ESKD on HD and offering timely feedback to patients and clinicians has the potential of curbing the extra fluid intake, hence reduce mortality and morbidity, and hopefully cut the costs of the need of frequent hospitalizations and/or extra dialysis treatments.Methods:We have designed a smartwatch app called Fluisense (available on Android play store,, https://play.google.com/store/apps/details?id=com.mob.fluisense) to help ESKD patients monitor their fluid intake. Fluisense helps patients record Fluid intake logs in an intuitive manner. Fluisense also collects sensor data such as mobility, acceleration, and heart rate to investigate biomarkers indicative of fluid overload. To the best of our knowledge, this is the first work leveraging smartwatches to monitor fluid accumulation of ESKD patients.N=15 ESKD patients were given an Android smartwatch with Fluisense pre-installed and were asked to log their fluid intake through the app by choosing from a list of predefined volumes each time they consume any liquid. The app computed and displayed the self-reported daily volume intake to help patients monitor their own fluid consumption. Patients received text messages twice a day (9am and 8pm) to remind them to use the watch. We also recorded patients’ weights before and after each of the thrice weekly dialysis sessions. The sum of self-reported interdialytic fluid intake was computed and compared against the interdialytic weight gain recorded in the clinic.Results: Patients recorded Fluids in 214 days out of 259 total days (i.e., 83% compliance rate). The average self-reported interdyalitic fluid consumption is 51 oz +/-64, and the average interdialytic weight gain is 2.67 kg +/- 1.56. We found a moderate but significant correlation between the self-reported fluid volumes and the interdialytic weight gain (r=0.363, P<0.001, r2=0.06). A deep learning method has also been designed to predict the interdialyctic weight gain from sensor data. Results validated through leave one subject out cross validation show an F1 score of 91 at predicting the level of weight change.Conclusion: Leveraging smartwatch-based sensing technology is a promising solution for fluid monitoring of ESKD patients. This can be related to the ease of utilization of this technology and the ecological validity of its measurements given they are collected close to when they happen, reducing recall biases.

Keywords: Healthcare, Kidney Disease, Wearable computing

DOI: 10.54941/ahfe1002101

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