Recognition of PVD based on Walking Pattern Acquired from Smartphone

PVD is a highly common blood vessel disease in modern society, which can be treated in a variety of ways. Treatment of the disease ranges from non-invasive treatments such as taking drugs to especially invasive treatments such as surgery under anesthesia. However, the problem we wish to solve relates to the accessibility of diagnosing the disease to the general population, with an emphasis on simple diagnosis.
Today, diagnosis of the disease requires expensive resources because the existing tests require hospital equipment and the interpretation of a specialist.
In this project we are trying to implement a smart and accessible system for identifying a symptom of PVD. Prof. Aharon Hoffman suggested using a free smartphone application that measures the patient's acceleration during walking. The phone is placed in the user's pocket and by command is measuring his acceleration for a few minutes.
This project is a follow-up project. However, we needed to do all the work again due to significant failures in the previous results that led to the selection of a new solution. In Part I of the project, we will focus primarily on the initial processing phase, building the application, using a server for the data storage and the system used by the doctor, and processing the initial information that the application measures in order to extract a number of features that we can use more easily to diagnose the disease.
Eventually, a learning system will be used to examine these characteristics and classify whether the person is ill and the degree of his illness.

Recognition of PVD based on Walking Pattern Acquired from Smartphone
Recognition of PVD based on Walking Pattern Acquired from Smartphone
Recognition of PVD based on Walking Pattern Acquired from Smartphone
Collaboration:

Prof. Aharon Hofman Emek hospital Afula