Functional Walking Analysis System
Gait disorders are one of the most common problems encountered in neurological and orthopedic patients as well as in elders. Gait disorders are an established risk factor for falling because of impaired stepping and postural stability. For detection of causes of risk of falling or fall phobia needs
Project Title
Functional Walking Analysis System
Project Area of Specialization
Project Summary
Gait disorders are one of the most common problems encountered in neurological and orthopedic patients as well as in elders. Gait disorders are an established risk factor for falling because of impaired stepping and postural stability. For detection of causes of risk of falling or fall phobia needs clinical assessment of gait.
Project Objectives
With functional shoe platform to improve bio-mechanist practices, to recovers gait patients, to improves their treatment plans. Through functional shoe, bio-mechanist can quickly collect reliable, repeatable gait profile data comprises of gait phases duration, report generation and diagnosis documentation. This system allows bio-mechanist to speedily start a right path of recovery, validate treatment programs, to record improvement over time.
Project Implementation Method
The idea behind the study is to design and analyze the walking abnormalities using wearable gait analysis system. The system consists of network of sensors and goniometers. In order to accurate detection of walking, sensors are mounted on heel, first metatarsal, fifth metatarsal, thumb positions of both shoes, ankle joint, knee joint and hip joint. In this study, possibilities of detecting duration of gait phases are heel strike, loading response, midstance, preswing and swing. In addition, system comprises of two goniometers for the analysis of arc of motion of knee and ankle joint. Both duration of each gait phase and arc of motions are served as an input for real time analysis. The gait phases and goniometer signals are fed in to Arduino mega 2560 which serves as a medium for importing data to LabVIEW 2014. In LabVIEW, an algorithm is implemented to calculate, analyze and predict walking abnormality reliably.
Benefits of the Project
Due to this technology, clinicians and researchers can be used to
- Determine root cause of lower limb problems
- Identify and correct pathomechanical problems
- Measures and evaluate treatment programs
- Diagnose neurological disorder
- Ensure effective offloading to reduce plantar ulceration risk
- Design new footwear products
Technical Details of Final Deliverable
A functional walking analysis system has an ability to detect abnormality walking and lower limb musculoskeleton system.
Final Deliverable of the Project
Type of Industry
Technologies
Sustainable Development Goals
Required Resources
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Sensors (Force sensitive Resistor) | Equipment | 10 | 2500 | 25000 |
| Raspberry Pi | Equipment | 2 | 5000 | 10000 |
| sensors (Inertial measurement Unit) | Equipment | 8 | 2500 | 20000 |
| Miscellaneous | Miscellaneous | 1 | 10000 | 10000 |
| Screen | Equipment | 1 | 10000 | 10000 |
| Raspberry Pi accessories | Equipment | 1 | 5000 | 5000 |
| Total in (Rs) | 80000 |
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