Creating User-Centric Solutions to Predict Outcomes
Create a novel set of wearable physiological sensors that supports a patient’s quality of life while very accurately recording and transmitting 4 key physiological parameters to feed PhysIQ’s predictive analytics algorithm.
Sensor system development that not only supported the analytics algorithm seamlessly throughout clinical trials and into commercialization, but led to a partnership with – and investment by Samsung, and a grant from the U.S. Agency for International Development for a program developed to improve the health outcomes of Ebola patients.
The end-to-end innovation support and leverage we received from Insight - from strategy, to long-range scaling and technical ￼￼development to production - made it possible for us to exceed our aggressive development timelines and navigate the medical domain. The success we’ve experienced for our startup to date would not have been possible otherwise.”
- Gary Conkright, CEO of PhysIQ.
PhysIQ’s predictive analytics platform is not your mainstream consumer motion and heart rate monitor, but a complex remote data collection device with aspirations to predict significant health events days in advance of their occurrence. To ready PhysIQ’s proprietary analytics platform for a VA funded clinical trial, we rapidly sourced, repurposed, created and reinvented several sensing technologies. These technologies had to accurately sense, record and transmit key physiological parameters including oxygen saturation, cardiac rhythm, respiratory bioimpedance and overall activity levels readings to be effectively utilized by the PhysIQ algorithm through persistent monitoring.
We then explored, sourced and tested a range of reflectance sensors for the BTE sensor, and an array of electrode technologies including adhesive, gel, and carbon. We created mock-ups and evaluated each iteratively and frequently for both functionality and efficacy testing and verification. Our team of human factors and design experts also created a complete system focused on user comfort and effective and unobtrusive data monitoring, with every component designed to be securely worn while patients go about their daily activities.
We then created a verified functional model for PhysIQ, worked with CMs to quickly create tooled components, and also with soft goods manufacturers for textile based wearable components of the system. A final round of usability and clinical effectiveness testing was performed and the documented results were used to confirm both functional and regulatory acceptability. The final system of sensors was highly effective supporting clinical trials and moving the platform toward commercialization.