1 / 13

Stride Length Detection using Mobile Devices

Stride Length Detection using Mobile Devices. By:- Guide:- Atul danda Scott Pardue Shashank s Alex Dohrn. Overview. About the project Progress Challenges Faced. About the Project. The objective of the project is to measure the accurate length of a stride.

eron
Download Presentation

Stride Length Detection using Mobile Devices

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Stride Length Detection using Mobile Devices By:- Guide:- Atuldanda Scott Pardue Shashanks Alex Dohrn

  2. Overview About the project Progress Challenges Faced

  3. About the Project The objective of the project is to measure the accurate length of a stride. Use of BUILT-IN inertial sensors to obtain instantaneous data from user mobile. Use of Accelerometer and Gyroscope. The current project is a sub-domain of a larger project(e.g Indoor Localization, Project TANGO)

  4. Accelerometer And Gyroscope An accelerometer is a device that measures g-force. It gives all its data in Cartesian Co-Ordinates i.e. X, Y, Z. -WikipediaA gyroscope is a device for measuring or maintaining orientation, based on the principles of angular momentum. Mechanical gyroscopes typically comprise a spinning wheel or disc in which the axle is free to assume any orientation. This gives the orientation of X, Y, Z i.e. Roll, Pitch and Yaw. -Wikipedia

  5. Graph of Gyroscope

  6. Ideal Graph of Accelerometer Component Value Time

  7. Progress • Stage 1 • Acclimatization to JAVA and Android Development Environment. • Literature survey about the project. • Development of Android App to tap data from sensors.

  8. Progress Stage 2 Exporting the data from Eclipse

  9. Stage 3 • Sampling the data at required time interval. Progress

  10. Progress Stage 4 Importing of data to MATLAB and Graphical Representation

  11. Work in Progress Implement a Low Pass Filter eliminate noise Obtain the optimum sampling rate. To compute the distance covered in a given stride. Achieve a tolerance range of 5%. Optimize the code, to calculate the distance travelled on skate board.

  12. Challenges Faced Reference 1. Step Length Estimation Using Handheld Inertial Sensors ValérieRenaudin*, Melania Susi and GérardLachapelle PLAN Group, Schulich School of Engineering, The University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada; E-Mails: msusi@ucalgary.ca (M.S.); gerard.lachapelle@ucalgary.ca (G.L.) Delayed in choosing a project closest to our domain. Novice to JAVA and Android development environment . Working on built in hardware of device. Working with a Black Box.

  13. Thank You

More Related