Integrated Monitoring for Personalized Renal Replacement Therapy

Abstract

Introduction: Emerging renal support devices tend towards automated physiological monitoring and treatment adaptation. In the patient-centred development of the mobile NEPHRON+ system decisive physiological aspects and their mutual affections were identified and methods of measurement were incorporated into a wearable system enabling a personalized and un-supervised auto-adaptive treatment. Methods: Nephrologists determined the physiological variables to be monitored in dialysis patients. The experts' opinions were confirmed by extensive literature survey to find formalized relationships between the physiological parameters. As a basis for the embedded device control, suitable means of monitoring were integrated into the prototype of NEPHRON+, a networked mobile dialysis system. Results: To monitor the principal function of the blood cleansing device, ion selective and enzymatic electrodes tailored towards the miniaturized device are integrated in the mobile blood treatment system. Weight measurements are transmitted via Bluetooth to gauge the hydration surplus to be removed. Both, fluidic and chemical dynamics in the body are described based on the measurements using compartment models. Hemodynamic instabilities frequently arise during blood cleansing treatment due to homeostatic imbalance. Thus an electric sphygmomanometer and heart rate acquisition are likewise connected for intermittent measurements. To interpret these context sensitive parameters an accelerometer is embodied into the wearable system enabling to estimate the influence of the treated patient's physical activity on aforementioned vital parameters. This allows differentiating between the vital parameter dynamics arising from activity and the negative influence of homeostatic imbalance. Conclusion: A prototypic architecture for a defined treatment scenario has been realized to demonstrate the technical feasibility, enabling comprehensive physiological monitoring of dialysis treatments. Mathematical models of the monitored variables were gleaned for context aware evaluation of the mutually dependent parameters.