Detection and prediction of osteoporosis using impulse response technique and artificial neural network

Abstract

Osteoporosis is an age related disorder manifested by skeletal fractures. This has been recognized as an important health issue mainly in women. Low bone mineral density is the major cause for osteoporosis. Detection and prediction of osteoporosis is a major challenge. Detection of osteoporosis helps in determining the density of the bone and also in the prevention of osteoporotic fractures in the high risk populations. In this study an easy first line method has been proposed to detect and predict osteoporosis. Impulse response test was carried out on the tibial bone for the detection of osteoporosis with the help of LabVIEW. The vibrations which were generated by the periodic impact of surgical hammer were captured by the accelerometer. The recorded analog signal was examined in frequency domain. The natural frequency of the vibration was significantly decreased in osteoporosis subjects which in turn indicate the loss in mechanical strength of the bone and bone mineral density. Prediction of osteoporosis was performed using a decision making system such as ANN in Matlab where factors other than bone mineral density was considered.