Fitbit accuracy had to be verified Able-bodied test subject wore Fitbit Subject was asked to perform various activities Assistant recorded actual ambulation parameters values Fitbit values were compared to actual values Compariso n validated Fitbit’s accuracy Fitbit One: Uses three-dimensional accelerometer to detect motion Measures relevant parameters such as steps taken, distance traveled, and elevation Able to record and store ambulation data for periods up to 10 days Clips onto most articles of clothing Commercially available for less than $100 System for K-Level Assessment in Amputees: Turning Qualitative into Quantified Results. Connor Bortz, Matthew Galbraith, Jessica Lewis, Chelsea Madden, Anthony Rossi Overview Background Information The Product The FitBit® “One”, a commercially available product has the capabilities needed for the project. Project Scope To develop a system to measure various gait parameters that pertain to ambulating to be used for diagnosis justification, and prosthetic prescription. Final Design Concept Generation Testing Plan Acknowledgements The accuracy of the Fitbit and capabilities of Fitabase were tested through various simulations. The purpose of the simulations was to emulate different K-levels, specifically K-2 and K-3. These two levels are the most difficult to differentiate, causing the most problems during diagnosis and Medicare applications. Metrics We would like to thank our sponsor, John Horne, our advisor Dr. Buckley, and the rest of the Senior Design Staff. Prototype Prototype data collection process: 1.Data from the Fitbit is extracted and stored in the cloud 2.Fitabase converts the data into an intraday csv file 3.Ambulation data is processed and produces K-Level Diagnosis. In addition to the prototype, the experiments and clinical trials were carefully designed as well. In order for the program to be implemented, necessary clinical trials will be used for validation of the device’s use in the prosthetic industry. Product Overview Testing Process Validation MetricDescription Time The device must be completed before the final deadline. Budget The total development and prototype cost cannot exceed the budget. Compatibility The device will be compatible with the parts of existing prosthetics. Number of Steps The device will measure the number of steps the user takes over a certain period of time. Speed The device will measure the speed of the user in meters per second. Distance The design will measure the distance the user covers in meters. Incline/Decline The device will recognize whether the user travels over an incline or decline. Data Acquisition The device will be able to store data over a certain amount of time. This data will be able to be uploaded in a certain amount of time. Cost The device should be sold to consumer below target value. Portability The device will stay within a reasonable weight and size. User Readability The device will have a reasonable screen size. The testing validated that the Fitbit was indeed accurate and Fitabase was able to capture the appropriate data to differentiate simulated K-2 and K-3 patients. Path Forward Next, the Fitbit will be used on actual amputee patients in order to gather data and normalize across the different K- levels. The finalized software will then predict a patients K- level based on ambulation data acquired by the Fitbit, which will help diagnosis and Medicare approval. Problem with Data Collection Traditional Fitbit data collection process: 1.Data is collected by the Fitbit 2.The user uploads the information the device has collected to the Fitbit database 3.These values are displayed directly from the Fitbit website Problems with this method include: The smallest increment of time the data can be viewed is one day The cadence change of the user cannot be calculated There is little customization with how the data is displayed Cannot handle large volume of patients. Current Problem: Amputees nationwide have trouble gaining Medicare approval Data that is analyzed is too qualitative Need to develop a method that uses tangible data to justify patient’s K-Level selection End Goal: Implement a device that collects ambulation data throughout the day and effectively display this data K-level designation will be based on data collected