PVD is a common vascular disease in Western society. Treatment of the disease ranges from non-invasive treatments such as taking drugs to very invasive treatments such as full anesthesia surgery. Diagnosis of the disease is not a simple matter, since various tests, specialist analysis and sometimes hospitalization are required. This project implements identification automation of the disease symptom. Prof. Aharon Hoffman suggested using a free smart phone application that measures the acceleration during walking.
The phone is placed in the user's pocket and by starting the application the acceleration is measured for a few minutes.
This is a continuance project concentrated on the application output signal processing. Upon receiving the output, the system developed in the project process the signal, generate frequency and time features, and introduce them into a learning system that classify whether there is a risk that the user is suffering from the disease or that there is no such risk
Prof. Aharon Hofman, Rambam
Ofer Danino, Erez Fridman