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Healthcare

Assisted Diagnosis & Prescription

Medical Assistants

Neural network formation of 3D-model orthopedic insoles

Neural network formation of 3D-model orthopedic insoles

For:
Medicine, public sector
Goal:
Improved Customer Experience
Problem addressed
Development of comfortable, individualized, anatomically correct orthopedic 3D
insoles for the treatment of flat feet.
Scope of use case
Artificial intelligence methods are used to construct individual medical products
to reduce the risk of developing diseases of the musculoskeletal system.
Description
The system consists of two parts, hardware and software.
The hardware scans 3D / 2D foot images of patients and
receives a production file format ready for loading into a
specialized machine or a 3D printer.
In the software, a local orthopaedic 3D model of the insole is
formed according to a unique authors technique using a
local software package based on artificial intelligence.
The received data is stored on a cloud platform.
The 3D-method makes it possible to more accurately orthose
complex pathologies and atypical deformations due to the
sophisticated equipment used and accurate removal of
anatomical physiological parameters of the foot up to 10 000
p/sm2 . The patients foot is scanned in the sitting position; it
is not exposed to loads; the 3D laser scanning is 6 cm high,
which allows for obtaining full-colour 3D models of the
patients legs with an accuracy of half a millimetre. Further
automatic milling is highly accurate for orthopaedic shoes.
The process of creating insoles is completely autonomous
and personalized, and does not require the intervention of an
orthopaedic doctor.
Overall, the system is modularized with capabilities to self-
learn and for future extensions.
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