Initiative awards chronic disease pilot grants to two digital biomarker-focused projects

Wearable Sweat Sensors for Smartphone-Enabled Diabetes Monitoring

Investigators
Mohammad H. Malakooti, Department of Mechanical Engineering
Miqin Zhang, Department of Materials Science & Engineering

Project abstract
This collaborative project aims to develop a non-invasive, battery-free, cost-effective wearable sweat sensor, integrated with a smartphone, that can continuously monitor pH and glucose levels and thus enable self-health monitoring for diabetic patients. The sensor is designed based on change in color resulted from biochemical reactions (i.e., colorimetric sensing) and can simultaneously detect the pH level and glucose concentration in sweat via two different materials coated on textile fabrics.

The first phase of this research will focus on printing coating materials and chemicals on the fabric and investigate how the material properties and processing parameters would affect the detection sensitivity using artificial sweat. Solutions of known pH and glucose levels will be prepared and applied to the sensor to establish baselines and standard color charts. A large number of photos will be taken for image analysis to quantify the color intensities.

Research in phase two will focus on digital data acquisition and analysis using advanced image processing tools and machine learning algorithms. This is crucial for studying flexible colorimetric sensors as they are designed to be worn on human body (i.e., curved surfaces) and can deform or wrinkle. The results of this pilot project will enable us to pursue external funding, which can potentially lead to groundbreaking technologies for affordable and user-friendly medical devices. The overarching goal of this research program is to improve public health and promote health equity.

Evaluating a novel, portable, self-administered device (“Beacon”) that measures critical flicker frequency toward at-home testing for minimal hepatic encephalopathy in cirrhosis

Investigators
George N. Ioannou, Department of Medicine
James Fogarty, Paul G. Allen School of Computer Science & Engineering
Sean A. Munson, Department of Human Centered Design & Engineering
Philip Vutien, Department of Medicine, Veterans Affairs Puget Sound Healthcare System
Ravi Karkar, Paul G. Allen School of Computer Science & Engineering
Richard Li, Paul G. Allen School of Computer Science & Engineering

Project abstract
Cirrhosis causes a spectrum of neurocognitive impairments known as hepatic encephalopathy (HE), which can range from minimal HE (MHE) to a life-threatening coma. Critical flicker frequency (CFF) is one of the best screening tests for MHE. CFF is the minimum frequency at which a flickering light source appears fused to an observer. However, CFF testing requires specialized equipment, such as the Flicker Fusion System (FFS), which is bulky, expensive, and not designed for self-use or at-home testing.

We developed a novel device for CFF testing called Beacon that is portable, inexpensive and an ideal candidate for at-home testing. Extensive in-clinic testing with 108 cirrhotic patients shows that Beacon-derived CFFs are nearly identical to those from the ‘gold-standard’ FFS. We aim to perform a pilot at-home study to:

• Specific Aim 1: Determine whether patients with cirrhosis (n=25) can self-measure CFF using Beacon at-home, including daily measurements over 2 weeks and weekly measurements over 4 weeks, calculating adherence to this protocol and variability of these CFF measurements.
• Specific Aim 2: Determine whether Beacon-derived at-home CFF measurements correspond to clinical events, including quality of life measures, episodes of overt HE, and accidents.
• Specific Aim 3: Make any software and hardware improvements to Beacon to facilitate and simplify its self-administration by patients based on semi-structured interview-questionnaires with study participants.

This pilot data will help inform the design of a longer, multicenter trial that investigates the impact of at-home CFF testing on clinical outcomes such as quality of life, hospitalizations, accidents, and mortality.