Design of a terrain detection system for foot drop

The ankle foot orthotic (AFO) has been around for centuries. They were created to augment functionality of an ankle damaged due to injury or disease. A common reason a patient might be prescribed an AFO is a condition called foot drop. Foot drop can be caused by many conditions, but the most common reason is a stroke. Foot drop can be characterized by the inability to raise and/or lower a patient\u27s foot. This incapacitation of the patient\u27s foot leads to unnatural gaits and joint fatigue, as well as increasing the patient\u27s likelihood of tripping and becoming seriously injured. Hard plastic AFOs that hold a patient\u27s foot in a neutral position are the current standard for combating foot drop. These AFOs come in many different shapes and sizes, which emphasizes the wide variety in functionality of someone with foot drop. Unfortunately, the restrictive nature of the AFO can cause unnatural movements in the patient\u27s foot; these unnatural tendencies are more exaggerated when walking down stairs and ramps, as the natural gait is to land toe first, the opposite of what the brace allows the patient to do. The purpose of this project is to create a sensor system for an AFO to help identify varying terrain. In the future this information can then be made to control an active AFO. Each terrain type will be first measured by a pair of simple infrared range finder, attached on the lower leg, one range finder looks ahead of the user and the other looks straight down at the ground. Models for the ground conditions can be established by representing each with Fourier series created using RANdom Sample Consensus (RANSAC). RANSAC coefficients will be scaled off the rate of data coming in and gait speed. Each model has a period term so the data can easily be scaled to match the pattern of walking regardless of pace. Gait speed will be measured using the downward facing ankle-mounted rangefinder, but with a threshold to determine when the foot is in contact with the ground. Once this initial set-up is completed, the system can take in data live and provide a prediction of the type of ground the patient is walking over, using pattern recognition techniques. The hope for this project is that if the system can accurately predict the change in ground type from, for example, level walking to walking down a ramp, an AFO could then be made to adjust itself, giving the patient a more natural gait, even when encountering adverse conditions. A byproduct of constantly using a patient\u27s own gait to measure ground type is the ability to track a patient\u27s changing gait over time, giving therapists a valuable new tool for tracking progress in a patient

A framework for synthesis of human gait oscillation using Intelligent Gait Oscillation Detector (IGOD)

The main objective of this paper illustrates an elementary concept about the designing, development and implementation of a bio-informatics diagnostic tool which understands and analyzes the human gait oscillation in order to provide an insight on human bi-pedal locomotion and its stability. A multi sensor device for detection of gait oscillations during human locomotion has been developed effectively. It has been named “IGOD”, an acronym of the “Intelligent Gait Oscillation Detector”. It ensures capturing of different person’s walking pattern in a very elegant way. This device would be used for creating a database of gait oscillations which could be extensively applied in several implications. The preliminary acquired data for eight major joints of a human body have been presented significantly. The electronic circuit has been attached to IGOD device in order to customize the proper calibration of every joint angle eventually.</p