RENAL9: REDIEM 2.0: Renal Extremity Device to Measure Impedance, Edema, Movement

Abstract

Background: Renal failure due to chronic kidney disease (CKD) is a leading cause of global mortality. CKD disrupts fluid balance regulation, inducing comorbidities such as excessive swelling of the extremities (edema) and restless leg syndrome (RLS). Clinical limitations impede the ability to quantitatively track edema and RLS in variable settings. We report on the development of a wearable device capable of continuously measuring and analyzing: 1. leg edema, 2. water content, and 3. RLS-specific leg movements. Methods: An enhanced system (2.0) was designed through integration of flex sensors, accelerometry, electromyography (EMG) and impedance biosensors into a flexible stocking that transmits data to a smartphone application for graphical interpretation. Assessment of components was performed through simulations of RLS and edema. EMG and accelerometry were assessed for identification accuracy by applying sensors to a subject performing movements of set type/frequency to simulate RLS. Subject’s plantar reflex was induced to verify increased EMG response to sudden reflexive motion. Flex sensors were assessed on simulated edema via a measured-fill hydration system with compressed sponges, measuring resistance in relation to circumference during expansion. Results: RLS sensor trials were able to differentiate RLS movement with EMG using peak detection software (Figure A). This was verified using accelerometry, which identified leg movement at >95% recognition accuracy. Edema sensor trials were able to accurately measure linear change in resistance during circumference expansion with an R2 value of 0.949 (Figure B). Further assessment will be performed to confirm water content using impedance sensors. Conclusion: Preliminary data demonstrates measurement and recognition accuracy in all components tested. Correlations identified between circumference expansion and resistance change allow for accurate quantification of swelling via resistance measurements. Motion differentiation/identification allows for tracking of RLS movement incidence and frequency. Ability to perform condition progression analysis on an aggregation of this data over time indicates future utility of the integrated device in CKD treatment. Continued work is intended to demonstrate this viability and conclude with a complete and comprehensive system for use by clinicians and patients.Figure 1. A. Representative EMG demonstrating RLS motion. Peaks identified by detection software are associated with sudden or jerk-like motions. B. Detection of circumference change (edema) via change in resistance using sensor.