The STRAVEDO project (STRumenazione Atta alla Valutazione dell’Equilibrio DOmestico) aims to design and develop a wearable measurement system, embedded in standard eyeglass frames, capable of monitoring key physiological and biomechanical parameters to assess and potentially mitigate the risks associated with domestic imbalance in older adults. This initiative is part of Spoke 10 of the Age-It program and targets the creation of smart technological solutions to enhance real-time monitoring and support for ageing populations.
The core technical innovation lies in the integration of a tri-axial accelerometer and a photoplethysmographic (PPG) sensor into the eyeglass structure. These components enable the monitoring of cardiovascular (heart rate, oxygen saturation, respiratory rate), cognitive (speech phase detection), and motor (mobility and stability) parameters. The data acquired is intended to inform both preventive and responsive care strategies in domestic environments.
The wearable prototype's development is structured into three main work packages. WP1 focuses on project coordination and management; WP2 on sensor selection, integration, and configuration; and WP3 on the design of the acquisition chain and signal analysis pipeline.
The system’s ultimate goal is to contribute to SDG 3 (Good Health and Well-being) and SDG 11 (Sustainable Cities and Communities), enabling the elderly to live independently and safely while remaining socially connected.
During the first reporting period (August–December 2024), the STRAVEDO project initiated all major planned activities across WP1 to WP3. Key technical accomplishments included the evaluation and selection of optimal tri-axial accelerometers and PPG sensors, along with their best positioning on eyeglass frames to ensure accurate signal capture. Extensive frequency domain analyses allowed identification of the signal bands of interest, sampling frequencies, and integration strategies.
Prototypes for the measurement system were assembled and tested, and the acquisition platform was designed accordingly. Additionally, preliminary signal analyses were conducted to shape the future development of custom data-processing algorithms. No significant delays or critical issues were encountered.
A scientific dissemination plan was also outlined, with commitments to present findings at a national or international conference by September 2025 and to submit a scientific publication to an open-access journal by October 2025.