Bone fracture detection using electrical impedance tomography based on STEMlab Red Pitaya

Khusnul Ain, Osmalina Nur Rahma, Alfian Pramudita Putra, Nur Syavinas, Dudi Darmawan, Harsh Sohal

Abstract


Bone fractures can result in accidents, osteoporosis, bone cancer, or other conditions. X-Ray is a medical imaging technique often used to detect bone fractures. However, X-Rays can have radiation effects that harm patients, health workers, and the environment. Electrical impedance tomography (EIT) is a system that can obtain object images based on the electrical impedance distribution. In bone fractures, the proximal bone tissue experiences increased blood flow with local edema due to the inflammatory reaction which indicates the presence of a high conductivity diffusion material at the fracture location. EIT based on the STEMlab Red Pitaya module can be utilized to detect bone fractures. Red Pitaya serves as a controller, possessing a voltage generator, an oscilloscope, and 16 input/output pins that fulfill most of the EIT functions. To test the EIT-based system’s efficacy, a 3D-printed polylactic acid (PLA)-based bone phantom model was used. This model was placed on a cylindrical phantom filled with water as a substitute for soft tissue. The voltage data then are reconstructed using electrical impedance and diffuse optical reconstruction software (EIDORS), a MATLAB toolbox devoted to image reconstruction from impedance measurement results. The results of the reconstruction demonstrated that EIT based on the Red Pitaya STEMlab module could distinguish between normal bone and fractured bone.

Keywords


Biomeasurement; Bone fracture detection; Electrical impedance tomography; Healthcare; STEMlab Red Pitaya

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DOI: http://doi.org/10.11591/ijeecs.v32.i1.pp150-159

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The Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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