Indian Journal of Science and Technology

The PDF file you selected should load here if your Web browser has a PDF reader plug-in installed (for example, a recent version of Adobe Acrobat Reader).

If you would like more information about how to print, save, and work with PDFs, Highwire Press provides a helpful Frequently Asked Questions about PDFs.

Alternatively, you can download the PDF file directly to your computer, from where it can be opened using a PDF reader. To download the PDF, click the Download link above.

Fullscreen Fullscreen Off


In this paper, we propose a method to distinguish healthy people from those suffering from Parkinson's disease using foot pressure data, Fast Fourier Transform (FFT), and Principal Component Analysis (PCA). We applied an FFT based on the Hamming method to extract frequency ranges of pressure data from the left and right feet of subjects. We used PCA to reduce the dimensions of features generated by FFT. A neural Network with Weighted Fuzzy Membership functions (NEWFM) was used to distinguish healthy subjects from those with Parkinson's disease. Our method yielded accuracy, specificity and sensitivity values of 75.90%, 61.41%, and 81.09%, respectively.

Keywords

Fft, Gait, Newfm, Parkinson’s Disease, Pca.
User