High impact blow inspection over a reactive mobile cloud framework
Download
1 / 22

High Impact Blow Inspection over a Reactive Mobile-Cloud Framework - PowerPoint PPT Presentation


  • 63 Views
  • Uploaded on

High Impact Blow Inspection over a Reactive Mobile-Cloud Framework. Presentation by: Eric L. Luster Hong Wu. Project Introduction. The state-of-the-art of this Project

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about ' High Impact Blow Inspection over a Reactive Mobile-Cloud Framework ' - omar-frederick


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.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
High impact blow inspection over a reactive mobile cloud framework

High Impact Blow Inspection over a Reactive Mobile-Cloud Framework

Presentation by:

Eric L. Luster

Hong Wu


Project introduction
Project Introduction Framework

  • The state-of-the-art of this Project

    • Various systems that are designed to evaluate correlations between head acceleration measurements and concussions are in the early stages of research and development.

    • Automatically detect the impact between the athletes by using online machine learning method.

    • Design a more effective solution for delivering textual and imagery to mobile devices


Project introduction1
Project Introduction Framework

  • The Instrumented Football Helmet (IFH) is a standard regulation football helmet that is equipped with sensors that measure, record, and analyze impacts. Upon examining similar products and existing patents, there are two areas of potential infringement.

  • US Patent number 5978972, filed in June 11, 1997, which outlines a system designed to measure and record in real time data relating to translational and angular acceleration of an individual’s head during normal sporting activity.

[1] A. Camp, A. Boeckmann, M. Olson, K. Hughes, ECE 477 Final Report − Fall 2008 Team 2 − PHI-Master


Related research
Related Research Framework

  • 2010 - A team from Arizona State University work on state of the art wireless delivery methods for reporting in real-time head impacts and concussions

  • 2010 - Simbex receives an NIH SBIR Phase II award to continue development of HitAlert™ technology to expand to enhance Simbex's product offerings in head impact biomechanics.

  • 2009 - Simbex receives an NIH SBIR Phase I award for develop HitAlert™ - high schools and youth football programs


News Framework

By Riddell on Tuesday, August 10, 2010

Ruling Finds Schutt Infringed Riddell’s Concussion

Reduction Technology Patents

  • (CHICAGO, August 10, 2010) – A federal court jury in Madison, Wis., has found that Schutt Sports Inc.’s DNA and ION football helmets infringed the concussion reduction technology features of the Riddell Revolution family of football helmets. The jury awarded Riddell just under $30 million in damages for Schutt’s infringing activities.


Paper # Framework 1P. Viola and M. Jones, “Rapid Object Detection using a Boosted Cascade of Simple Features,”

Hong Wu


Background Framework

P. Viola and M. Jones, “Rapid Object Detection using a Boosted Cascade of Simple Features,” IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Los Alamitos, CA, USA: IEEE Computer Society, 2001, p. 511.

Classical method in computer vision, cited over 4000 times

Motivation

Relation between computer vision, machine learning and mobile computing

Reduce the labor work of marking the samples.

Reduce the time used in training.


Method Framework - Data-driven training VS Intelligence-driven training - General feature - Adaboost


Online VS Offline Adaboost Framework

Online Training:

- Get the sample one by one

- Adaptive

- Not accurate in all cases

Offline Training:

- Get all the samples

at one time

Demo

http://www.youtube.com/watch?v=0tSxMmAngs8&feature=player_embedded


Problem Framework

Failure Case

http://www.youtube.com/watch?v=3AnWc5J9968&NR=1


Relation with the project Framework

Automatically detect the impact with less supervision.

Assume that the athlete was tracked by a camera and an impact is a true alarm if the athlete is running and then fall down.

The concept of online machine learning can be used in other applications such as training an accelerator sensor to detect the gesture of a person by using heart rate sensor.

Training: Accelerator sensor + heart rate sensor

Testing: Accelerator sensor


Paper 2 eric l luster support for mobile access to dicom images over heterogeneous radio networks
Paper #2 Framework Eric L. LusterSupport for Mobile Access to DICOM Images Over Heterogeneous Radio Networks

  • I.Maglogiannis, G. Kormentzas, and T. Pliakas, Wavelet-Based Compression With ROI Coding Support for Mobile Access to DICOM Images Over Heterogeneous Radio Networks, IEEE Transaction on Information Technology in Biomedicine, vol. 13, no., 4 July 2009


Paper background
Paper Background Framework

  • The visual quality of the medical images/scans is required to be high, in order to ensure correct and efficient assessment resulting in correct diagnosis.

  • In this context, a mobile device has to handle medical images of significant sizes, while also taking into account its own limitations concerning memory and processing resources.


Dlwic
DLWIC Framework

  • Useful when a user browses medical images using slow-bandwidth connections,

  • DLWIC uses the progressivism by stopping the coding when the quality of the reconstruction exceeds a threshold given as an input parameter to the algorithm.


Relevance to our project
Relevance to our Project Framework

  • Application enhances the viewing of the following types of images on a mobile device:

    • Computed Tomography (CT) scans

    • Computed Radiography (CR) scans

    • Magnetic Resonance (MR) images

    • Stored in picture archiving and communication systems (PACS)

    • Hospital Information Systems (HIS)

  • Furthermore, the current medical image viewers do not take into consideration the special requirements and needs of an heterogeneous radio access environment composed of different radio access technologies [e.g., GPRS/UMTS, WLAN, and DVB-H).


Back up slides
Back-up Slides Framework


Original master schedule
Original Master Schedule Framework

Old Schedule


Master schedule
Master Schedule Framework


Tables figures
Tables & Figures Framework


ad