BOAT Innosuisse

Recent progress in data science and fabrication processes enable the rise of Patient-Specific Anatomic Braces (PSABs). Currently, over 80% of wrist and ankle fractures are operated because conventional cast immobilization does not provide sufficient stability to hold the fracture fragments in place. Besides, for the minority of stable fractures still not operated, the current plaster or synthetic casts are cumbersome. Thanks to their high degree of accuracy and adaptability, PSABs allow optimal fracture immobilisation, therefore, reducing surgery indications and are comfortable.

The overall vision driving the project is to take the best from both data-driven machine learning and expert (medical and mechanical) knowledge to come up with an integrated algorithmic framework going from limb imaging to PSAB production. The long-term goal of Swibrace, a start-up founded in Fribourg in 2017, is indeed to provide fast and efficient solutions to produce PSABs.

Swibrace has already developed in partnership with HEIA-FR PSAB's derived from 3D scans of patients' limbs. Using conventional software, fitting of the geometry of a generic brace to the patient's 3D scan currently takes approximately three days, which is not acceptable. BOAT addresses this bottleneck by automating PSAB design from limb's images. This will be done thanks to a novel collaboration around statistical machine learning, where Idiap Research Institute will join efforts with Swibrace, HEIA-FR and Inselspital Bern in order to perform registration of limbs, achieve image-driven deformations of PSBAs to allow optimal geometrical fits, and automate key design steps so as to produce in a swift way and at competitive cost PSAB accommodating post-traumatic swelling. The participation of Inselspital is essential in assessing and improving the quality of produced braces through ethical clinical testing.

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