Researchers at Ohio State University have developed a revolutionary new insole that uses solar power, pressure sensors, and machine learning to track gait and detect early signs of conditions like plantar fasciitis and Parkinson’s disease. The smart insole combines high-resolution pressure sensing, onboard solar power, and machine learning to analyze gait in real-time.
The system features 22 pressure sensors embedded in a polydimethylsiloxane (PDMS) matrix, which work together to provide accurate readings across a range of pressures. The sensors are powered by flexible perovskite solar modules that harvest ambient light, allowing the system to run for extended periods without recharging.
The smart insole can detect subtle changes in gait and pressure distributions that reveal important information about skeletal, nervous, and muscular systems. It can track conditions like plantar fasciitis, diabetic neuropathy, and Parkinson’s disease, as well as monitor gait recovery in stroke patients and post-surgical recovery after knee or hip replacements.
The system provides continuous, objective data that supplements traditional assessments and supports earlier interventions. For clinicians, it offers a valuable tool for tracking patient progress and adjusting treatment plans accordingly. The smart insole also has potential applications in athletics, where it can help prevent overuse injuries by identifying fatigue-related gait changes and optimize form in running or strength training.
The prototype has already passed key durability benchmarks, including 180,000 cycles of compression testing with no loss in accuracy or stability. Researchers plan to improve gesture recognition, expand the range of detectable motions, and integrate additional sensor types in future iterations.
Source: https://www.allaboutcircuits.com/news/solar-on-top-sensors-on-bottom-smart-insole-offers-biometric-insights