WalkFit

Innovation Type:

Product

Technologies Involved:

AI and ML

Stage of Innovation:

Prototype / Proof of Concept

Market Segment:

B2B and B2C

Impact:

Social

Team:

1) Rahi Shah

2) Hriday Boriawala

Project Stage:

Competition / Event Project

Project Start Year:

2022

Competition / Event Name:

IRIS National Fair 2022

About

WalkFit, is an AI-powered attachment for walking sticks designed by Rahi Shah and Hriday Boriawala. This innovative tool aims to prevent falls among seniors, particularly those with conditions like osteoarthritis and osteoporosis. WalkFit provides real-time stability alerts and detects improper gait, enhancing safety and mobility for elderly users. The project reflects the duo’s efforts to address the health challenges faced by older adults through accessible technology.

How it works

This device attaches to any walking stick to assess a user's stability by measuring weight-bearing tendencies. Equipped with Force Sensitive Resistors (FSR) and gyro sensors, it detects how much of the user’s weight is supported by the stick, analyzing pressure values to identify dependency levels, which indicate fall risk. Data from the sensors is transmitted to a laptop via Bluetooth, creating real-time heat maps that show pressure points—blue for low pressure and red for high pressure. High pressure on one side can indicate issues on the opposite limb. This data aids in diagnosing balance or mobility issues and sends early alerts to prevent falls. A mobile app is planned to make the data accessible and notify caregivers remotely. After testing with seniors, the prototype showed promising results, leading to awards and further development.

Applications

• Fall Risk Assessment and Prevention: By monitoring weight distribution and stability, the device predicts and prevents potential falls, which is especially useful for seniors with mobility issues.

• Remote Monitoring for Caregivers: The device can connect to a mobile app to alert caregivers or family members who live far away about changes in a user’s balance or mobility.

• Rehabilitation and Physical Therapy: Physiotherapists can use the device to monitor patients' weight-bearing patterns, aiding in diagnosis and personalized treatment plans.

• Early Diagnosis of Mobility-Related Conditions: Patterns in weight distribution can help detect conditions like osteoarthritis, osteoporosis, and issues in the knees or hips before they worsen.

• Progress Tracking for Patients: Doctors and therapists can track a patient’s progress and treatment effectiveness over time, adjusting therapy as needed based on real-time data.

• Assistive Device Compatibility: Since it attaches to any walking stick, the device is versatile and suitable for various types of users without requiring specialized equipment.

• Research and Clinical Studies: The device can provide valuable data for studies on mobility, fall risk, and rehabilitation in the elderly, improving strategies for fall prevention.