Assessment and Evaluation of Diabetic Foot using Biothesiometry and Artificial Neural Networks

Abstract

Introduction: Diabetes is a common disorder that is prevalent in the general population. As it advances, it causes a multitude of consequences, some of which are fatal. Diabetic Neuropathy (DN) is one such illness that causes nerve damage, and it is quickly recognised and diagnosed using a technique known as biothesiometry. Aim: To create an assessment tool based on an Artificial Neural Network (ANN) that evaluates diabetic foot based on Vibration Perception Threshold (VPT) values. Materials and Methods: This experimental and predictive study was done using VPT values for 696 controlled and diabetic groups selected by purposive sampling. The VPT was measured by a biothesiometre. A metal probe was placed under the foot of the person and the voltage was increased gradually from zero and the transition from no vibration to the point of vibration is marked as VPT. Average of three measurements were taken to calculate the VPT value of the given patient. This involves the VPT value which helps in the assessment of severity of the condition. The recorded data was fed as an input to the ANN model which predicted the average VPT value of the left and right foot. Furthermore, the ANN model was assessed my means of statistical measures and parameters. Results: The results of the study confirmed the correlation between the values of VPT acquired at different points of the foot and the coefficient for the left and right foot was found to be 0.99549 and 1.0000 respectively. Furthermore, the efficiency of the proposed ANN model was assessed using statistical measures like Mean Square Error (MSE), Mean Absolute Error (MAE), Square Sum Error (SSE) and Coefficient of determination (R2). The predicted values were very close to the experimental VPT results, and the correlation coefficient R are 0.99549 and 0.99975 for the left and right foots respectively, which shows the best settlement. Conclusion: The study concluded that VPT acquired from the foot of diabetic patients is useful in categorising the level of severity of DN. Furthermore, the results of ANN model proved that there exists a strong correlation between the average VPT values of left and right foot and those that are acquired from different points of the foot such as Great Toe, First metatarsal, Third metatarsal, Fifth metatarsal, In step and heel which concluded the study to be effective in the assessment and diagnosis of DN.

Keywords

• diabetes
• vibrometre
• vibration perception threshold