Affiliations: [a] Department of Electrical and Electronics Engineering, Loyola-ICAM college of Engineering and Technology, Chennai, Tamil Nadu, India
| [b] Department of Biomedical Engineering, Rajalakshmi Engineering College, Chennai, Tamil Nadu, India
| [c] D. M (Neuro), Consultant Neurologist, Fortis Malar Hospital, Chennai, Tamil Nadu, India
Correspondence:
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Corresponding author. G. Annie Nancy, Department of Electrical and Electronics Engineering, Loyola-ICAM college of Engineering and Technology, Chennai, Tamil Nadu, India. E-mail: [email protected].
Abstract: Pressure injury usually develop in the bony prominence of immobile bedridden subjects. Predicting pressure injuries based on the subjects’ physiological information will reduce the burden of the caretakers in adjusting the frequency of repositioning such subjects. Visual assessment, diagnostic, and prognostic approaches only provide pressure injury information after onset. Therefore, the objective of this unique modeling technique is to predict the internal alterations that take place in human tissues before the onset of pressure injuries. In this approach the bio-mechanical and bio-thermal properties was integrated to predict the internal changes of skin, fat, and muscle layers when subjects were self-loaded continuously for one hour in the sacrum region. A change in temperature of all the layers, as well as the distribution of Von-Mises stress in these layers, was observed. The inflammation caused by the changes in the temperature and the stress was measured from the simulation model. Ultrasound measurements was also taken for the same subjects in the supine position in the sacral region, before and after one hour by applying a self-load. An identical change in the thickness of the above-mentioned layers due to thermal expansion was noticed. Hence this computational model is hypothesized to give identical thermal expansion in comparison with the ultrasound measurements. There was an agreement between the thermal expansion using the simulation technique and the ultrasound technique which was assessed through Bland-Altman analysis, with a 96% confidence interval.
