Printed by www.postersession.com Biofeedback System for Propulsion Training Tom Soike (BME), Nicholson Chadwick (BME), Noah Reding (EE) Project Sponsors.

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Presentation transcript:

printed by Biofeedback System for Propulsion Training Tom Soike (BME), Nicholson Chadwick (BME), Noah Reding (EE) Project Sponsors Dr. Mark Richter, Max Mobility and Dr. Paul King Department of Biomedical Engineering, Vanderbilt University, Nashville, TN Currently, there are over 2.5 million Americans who are confined to wheelchairs. Some users propel themselves improperly, leading to damage of their upper extremities later in life. Approximately 65% wheelchair users experience upper extremity pain or injury. Research has linked a relationship between impact stresses placed upon the wrist, elbow, and shoulder during propulsion to upper extremity injury. The propulsiometer we used can be seen in Figure 5 below. This device collects data from the wheelchair about push frequency, push angle, peak force, tangential force, and peak loading rate. This data is collected by the sensors on the wheel and sent to the onboard miniDAT computer. This computer compiles the data and wirelessly transmits the information to the laboratory PCs. We took existing software code from MATLAB and LABView and compiled a new software program in LABview which can analyze and relay information much faster to the users. To make the software program accurately run, we installed a more accurate angle sensor which allowed the program to exactly know the location of the wheel so appropriate offset parameters could be applied. Currently, the personal mobility device industry is a $2-3 Billion operation. The increasing cost of medical care and surgeries associated with repair of upper extremity injury consequently emphasizes US demand for mobility devices. The personal mobility market is projected to increase 6.9% annually, reaching $7.4 Billion by Thus, there is an even greater value placed upon the development and improvement of mobility devices. One way that our project can be integrated into this market scenario is through the physical therapy industry. Currently, there are more then 77,00 physical therapists in the United States, and it is our goal to provide these professionals with our device, aiding them in the treatment and training of their patients. The goal of the biofeedback project is to develop software that works with an established propulsiometer to effectively “teach” new and existing wheelchair users proper propulsion methods in hopes of reducing their chances of developing injuries to the upper extremities later in life. We are using an existing propulsiometer built by Max Mobility Laboratories to collect push frequency, push angle, peak force, tangential force, and peak loading rate while one is using a wheelchair. This information is wirelessly sent to a computer for further analysis. Improving the quality of the angle sensor on the propulsiometer is a concurrent goal. Currently, the personal mobility device industry is a $2-3 Billion operation. The increasing cost of medical care and surgeries associated with repair of upper extremity injury consequently emphasizes US demand for mobility devices. The personal mobility market is projected to increase 6.9% annually, reaching $7.4 Billion by Thus, there is an even greater value placed upon the development and improvement of mobility devices. One way that our project can be integrated into this market scenario is through the physical therapy industry. Currently, there are more then 77,00 physical therapists in the United States, and it is our goal to provide these professionals with our device, aiding them in the treatment and training of their patients. BACKGROUND PROJECT GOAL MATERIALS AND METHODS RESULTS CONCLUSIONS Max Mobility Laboratory MiniDAT On- board Computer Wheel Handrim Load Cell Wireless Transmitter Powersource Transmitter EXISTING PRODUCTS Currently, 3Rivers Company offers a device for clinicians called the smart wheel. This device is attached to the center of the wheel and measures the average force of push, length of push, smoothness of push, and the push frequency. Some of the disadvantages to this design are that the device can only fit one size of wheel diameter, there is no real-time data analysis, and the cost of the device is $22, Our design seeks to improve upon 3Rivers technology in that it allows for real-time data analysis, providing the user with data the moment it is created. Also, our design is interchangeable between all wheel dimensions and is projected to cost less (under $20,000.00). Our design also allows for analysis of the push angle. Max Mobility Laboratory focuses on the research and development of new and existing devices for individuals with physical disabilities. This lab is run by Dr. Mark Richter and staffed by Russell Rodriguez and Adam. Features of the lab that aid in our project are an operating wheelchair treadmill with variable incline (0-6 o ), a machine shop to fabricate and modify components, PCs for data collection, and a radio transmission system which allows wireless data collection. Max Mobility Laboratory focuses on the research and development of new and existing devices for individuals with physical disabilities. This lab is run by Dr. Mark Richter and staffed by Russell Rodriguez and Adam. Features of the lab that aid in our project are an operating wheelchair treadmill with variable incline (0-6 o ), a machine shop to fabricate and modify components, multiple PCs for data collection, and a radio transmission system which allows wireless data collection Fig 1: Wheelchair on the treadmill, Fig2: PC and lab configuration, Fig3: Hydraulic lift associated with the treadmill, Fig4: Noah testing the device. Fig6: 3Rivers Smart Wheel device shown in center of wheel, Fig7: Our design through Max Mobility Fig6: 3Rivers Smart Wheel device shown in center of wheel, Fig7: Our design through Max Mobility 67 Fig5: The device used for data collection. This fits on to the outside of the wheel. 1 2 Figure 1 displays how the newly installed angle sensor allows for very accurate angle measurements. The linear encoder that we installed has 256 lines for determining the angle that the wheel is at with respect to a “0” degree that is established by the user. The EDAC on the propulsiometer takes the output from the encoder and converts it to a voltage that corresponds to an angle value. However, the EDAC has 4096 lines for determining the angle and this, in combination with a 4X multiplier on the EDAC, causes the angle on Channel 6 of the device to reset after every 4 turns. Figure 2 shows a sample of the user interface that will be provided to the physical therapists that will use the device. These visual meters make it easier for the users to understand how to characterize their pushes. By placing markers that correspond to optimal push characteristics on the meters, the person in the wheelchair will be able to see what they need to do in order to achieve their best propulsion methods. Fig 1: Sawtooth waveforms denotes cycles in wheel propulsion. Fig2: The user-friendly interface with specific subject targets. The accomplishments of this project will hopefully lead to more freedom in the lives of all wheelchair users. The main benefits will come from the reduced probability of reconstructive surgery to the upper extremities and; consequently, not having to spend more money on an electric wheelchair. Electric wheelchairs range in cost from $1,600- $7,500 while a manual wheelchair can cost as little as $200. Money will also be saved on potential corrective surgeries for stress injuries caused by incorrect usage. Currently, long, smooth pushes are determined to be the least damaging to one’s upper extremities. Our research has provided Max Mobility the program to effectively test this hypothesis, further solidifying the standards deemed appropriate for proper propulsion.