I-Corps: Translation Potential of Muscle Activity Monitoring Using Smart Patches

The significance of this I-Corps project is based on the translation from lab to market of a wearable, artificial intelligence (AI)-powered, muscle activity monitoring patch designed to improve health tracking in both clinical and at-home patient settings. This solution seeks to address the lack of accurate, real-time muscle monitoring, which is critical for individuals with neurodegenerative diseases, athletes, and those recovering from injuries. In the United States, approximately 7 million people suffer from neurodegenerative conditions such as Parkinson’s and Alzheimer’s diseases, while over 30 million individuals participate in organized sports, where injuries like strains and sprains are common and often result in significant recovery time and healthcare costs. The benefit of this approach is improved accuracy in detecting muscle fatigue and strain, enabling healthcare professionals, athletes, and individuals to take proactive steps in preventing injuries and managing neuromuscular conditions. This innovation has the potential to provide multiple benefits by enabling healthcare professionals, coaches, and individuals to detect early signs of muscle-related conditions, improve rehabilitation outcomes, reduce medical expenses, enhance sports performance, and promote healthier lifestyles by preventing injuries.

This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of an artificial intelligence (AI)-enhanced wearable patch that provides real-time, precise data on muscle strain and exertion levels. This solution consists of a flexible, biocompatible sensor patch integrated with advanced AI algorithms designed to continuously monitor biomechanical activity. Current methods for muscle activity assessment rely on manual examinations, subjective self-monitoring, or intermittent clinical evaluations, which lack real-time feedback and often miss subtle physiological changes. The non-invasive design of this device ensures ease of use, making it accessible for various applications, including rehabilitation, sports performance optimization, and elderly care. By combining real-time data acquisition with AI-driven analysis, this smart patch device can deliver continuous muscle activity monitoring and predictive insights that support early interventions.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Award Number: 2513228
Principal Investigator: Fatemehsadat Tabei
Funds Obligated: $50,000
State: TX