Osteoarthritis (OA) is one of the leading causes of disability worldwide. It affects millions of people, greatly limiting their mobility and independent lifestyle. Earlier diagnostic and improved patient stratification is required to deploy personalized OA treatments.
The Inmodi project is developing a smart wearable platform for an in-motion joint health assessment at any Point-of-Care. The objective is to optimize patient-specific treatment plans and improve outcomes. The core technology is a combination of acoustic, thermal and kinematic sensors and an artificial intelligence (AI)-based data analysis extracting new relevant biomarkers of the joint function. We aim to introduce a wearable system for reliable preliminary assessment of the knee joint function in primary healthcare.
While proof-of-concept is established, some critical innovative steps are still required to reach Inmodi’s goals. The current hardware requires the integration of a new edge AI platform with custom hardware accelerators to enable the real-time processing of the multimodal synchronized data. The development of novel biomarkers requires training data for the AI. This data can only be obtained through a clinical validation to be done in collaboration with the Schulthess Klinik (Zürich), offering access to a large pool of documented patients and enabling prototypes testing while getting feedback from practitioners. We plan to establish a new state of-the-art in the field of biometrics for joint assessment, by providing novel interpretable information for the development of personalized models with an approach applicable to clinical practices.
