Smart Foot Weight Analytics for Health Diagnosis
Analysis of pressure distribution on the plantar surface of the foot is an important factor considered today in the fields of healthcare, sports, and the shoe industry. Millions of people in Pakistan and around the world are affected by foot-related issues like arthritis, tendonitis, back pain, and heel pain,diabetic foot ulcers and many of these are directly or indirectly related to improper weight distribution on the feet. The proposed system is designed using force sensing resistor (FSR) sensors that measure the pressure, thus saving the information in an array of sensor networks for transferring data into the CPU for processing. In the processing unit, machine learning algorithms and statistical analysis techniques are utilised to understand the pressure distribution on different parts of the foot. We collected the sample data of two hundred individuals, for training and testing the model. While collecting the data various factors are considered like age, gender, height, and previous medical history for more precise observations. In post-processing, weight distribution, and pressure patterns are observed in a user-friendly GUI interface in 2D and 3D forms for displaying the plantar pressure data that will help the experts and medical professionals to monitor foot health. This system can also help medical professionals in rehabilitation centers for continuous monitoring and the fast recovery of patients and in the shoe industry to make customised medicated shoe insoles.
Keywords: FSR sensor, Foot pressure distribution, medicated shoe Insole, Plantar pressure distribution, Foot weight distribution, Pressure mapping, Rehabilitation.
Tools: Arduino,Embedded Systems, Machine learning, Python
Department: Department of Electrical Engineering
Project Team Members
| Name |
Email |
|
Uman Ahmad
|
uman2019@namal.edu.pk |
|
Muhammad Haris
|
haris2020@namal.edu.pk |
|
Muhammad Shafqat Ashraf
|
sahafqat2020@namal.edu.pk |
Project Poster
