AI for Nonprofits

Chapter 4.1Predictive Medical Analytics Case Study: Michael J. Fox Foundation and Sensoria Health

Based on insights from an interview with Davide Vigano.

Background and Problem Statement

The Michael J. Fox Foundation (MJFF) has long been at the forefront of Parkinson's disease research, with a mission to find a cure and improve the quality of life for those affected by the disease. Despite significant advancements, one of the persistent challenges has been the ability to diagnose, and then monitor and eventually predict, the progression of Parkinson's disease in individual patients. Accurate and early detection and prediction is crucial for tailoring personalized and timely treatments, improving patient outcomes, and accelerating research efforts.

Sensoria Health (Sensoria), a company specializing in truly wearable technologies, remote patient monitoring, and data analytics, recognized the potential of AI in addressing this challenge. The goal was to collect accurate human locomotion data and then leverage Machine Learning (ML) and AI-driven predictive analytics to provide accurate and individualized insights into disease diagnosis and progression, ultimately enhancing patient care and research precision.

AI-Driven Solution

In collaboration with MJFF, Sensoria developed an innovative ML/AI-driven solution that integrated wearable technology with advanced predictive analytics. They equipped patients with “smart socks” embedded with textile pressure sensors and microelectronics ...