ARTIFICIAL INTELLIGENCE–BASED AUTONOMOUS SOCKET PROPOSAL PROGRAM: A PRELIMINARY STUDY FOR CLINICAL DECISION SUPPORT SYSTEM

Year 2024, , 206 - 213, 27.08.2024

Murat Ali Çınar , Bülent Haznedar , Kezban Bayramlar

https://doi.org/10.21653/tjpr.1421321

Abstract

Purpose: The aim of this study is to develop artificial intelligence-based interfaces that can be used by professionals (clinicians and/or academics) working with disabled individuals who need prosthetics and to create a sample data set for professionals working in this field.
Methods: 101 patients who had undergone amputation were enrolled. The residual limbs of all patients were scanned using a three-dimensional (3D) scanner and saved on the computer. The prosthetic sockets, fabricated using traditional methods, were also scanned with the same scanner and saved as a 3D model. Residual limb–prosthetic socket matches were obtained using data points and a deep neural network (DNN)-based decision support system was developed.
Results: Simulation studies conducted with the point cloud data sets of 101 patients yielded a training success rate of 86%. The DNN model exhibited a generalization success rate of 78%.
Conclusion: The artificial intelligence–based software interface has potential and could assist professionals by suggesting a suitable 3D socket model for patients in need of a prosthesis. Further studies will benefit from additional sample data to enhance the accuracy of the model.

Keywords

Amputation, Artificial Intelligence, Decision Support System

Project Number

2180990

YAPAY ZEKA TABANLI OTONOM SOKET ÖNERME PROGRAMI: KLİNİK KARAR DESTEK SİSTEMİ İÇİN ÖN ÇALIŞMA

Abstract

Amaç: Bu çalışmanın amacı, protez ihtiyacı olan engelli bireylerle çalışan profesyonellerin (klinisyenler ve/veya akademisyenler) kullanabileceği yapay zeka tabanlı arayüzler geliştirmek ve bu alanda çalışan profesyoneller için örnek bir veri seti oluşturmaktır.
Yöntem: Amputasyon cerrahisi geçiren toplam 101 hasta çalışmaya dahil edildi. Tüm hastaların güdükleri üç boyutlu tarayıcı kullanılarak tarandı ve bilgisayara kaydedildi. Çalışmaya dahil edilen hastaların geleneksel yöntemlerle üretilen protez soketleri de aynı tarayıcıyla taranarak elde edilen üç boyutlu modelleri de bilgisayara kaydedildi. Üç boyutlu tarayıcılarla elde edilen nokta bulutu verileri kullanılarak güdük-protez soket eşleşmeleri elde edildi ve derin sinir ağı (DNN) tabanlı bir karar destek sistemi geliştirildi.
Sonuçlar: 101 hastaya ait nokta bulutu veri setleri ile yapılan simülasyon çalışmalarında %86 oranında eğitim başarı oranı elde edildi. DNN modeli %78'lik bir genelleme başarı oranı sergiledi.
Tartışma: Bu çalışma ile geliştirilen yapay zeka tabanlı otonom soket önerme ara yüzü protez ihtiyacı olan hastalar için uygun 3 boyutlu soket modeli önererek profesyonellere yardımcı olabilir. Daha sonraki çalışmalarda modelin doğruluğunu artırmak için daha fazla hastanın verilerinin kullanılması planlanmaktadır.

Keywords

Amputasyon, Yapay Zeka, Karar Destek Sistemi

Supporting Institution

TÜRKİYE BİLİMSEL VE TEKNOLOJİK ARAŞTIRMA KURUMU (TÜBİTAK)

Project Number

2180990

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