Imagine a smart sensor you clip onto your shoe that tracks every single step with the precision of a laboratory, but while you are outside in the real world. It combines satellite signals with motion sensors to map exactly how a person moves. This helps doctors spot early signs of brain-related diseases or helps coaches tweak an athlete's stride in real-time.
Current wearable motion trackers lack the accuracy needed for clinical or professional athletic analysis unless used in a controlled lab. This prevents doctors and trainers from getting precise data on how patients and athletes actually move in their daily lives.
A wearable shoe-attached device integrating GNSS and IMU sensors, a noise-reducing GREP algorithm, and a cloud-based monitoring platform.
If you are a clinic dealing with the difficulty of monitoring patient decline between visits — this project developed a wearable device and cloud platform that tracks body kinematics with centimeter-level accuracy. This allows doctors to monitor the evolution of neurodegenerative diseases remotely and adjust treatments based on real-world data.
If you are a training center dealing with the lack of precise biomechanical data outside of a lab — this project developed a GNSS and IMU integrated sensor that tracks step length and stride. This enables trainers to adapt high-level training programs in real-time to improve performance.
If you are a therapy center dealing with subjective assessments of patient recovery — this project developed a sensor-based monitoring solution that provides objective, continuous tracking of movement. This allows physiotherapists to verify the effectiveness of rehabilitation processes in the patient's natural environment.
Based on available project data, there is no specific pricing or cost information provided for the end-user device.
The project focuses on designing a compact, user-friendly case that can be attached to any shoe, suggesting a design intended for scalable manufacturing.
The system utilizes a patented algorithm called GREP, which is used to reduce background noise and improve data accuracy.
It includes a cloud platform for data processing and visualization, allowing remote monitoring and sharing of results between patients and medical professionals.
The project period runs from 2024-10-01 to 2027-03-31, indicating the development and testing phase is currently active.
The consortium is heavily industry-driven with a 56% industry ratio, comprising 5 industrial partners and 4 SMEs. This strong commercial lean, supported by 2 universities and 1 research center across 4 countries, suggests the project is focused on market viability rather than just academic theory.
Contact GTER SRL INNOVAZIONE IN GEOMATICA GNSS E GIS in Italy
Contact us to explore licensing opportunities for the GREP algorithm.
