[rehab] course design feedback (fwd)

[Dick Davis]

Laurie,
It won't open as a Word file.  By the way, wasn't iocane the poison that
they used in "The Princess Bride"?  Unfortunate name choice if it is.
Dick Davis

-----Original Message-----
From: rehab-bounces at nfbnet.org [mailto:rehab-bounces at nfbnet.org] On Behalf
Of Leslie Fairall
Sent: Monday, February 27, 2012 6:27 PM
To: Multiple recipients of NFBnet rehab Mailing List
Subject: [rehab] course design feedback (fwd)

From: Hallman, Laurie
Sent: Monday, February 27, 2012 3:20 PM
To: VHA BRS National Staff Listing
Subject: FW: course design feedback



I received a request for information regarding the development of a
research project. They have a short turn around and need information
preferably by this Tuesday COB. I answered their questions but presented
the problem of only getting information from one O&M instructor and told
them that I could try to forward to our group for input. If you have time,
please review the attached questions and respond to the email address
included (hprofita at gmail.com).

Laurie



From: Hal Pro [mailto:hprofita at gmail.com]
Sent: Monday, February 27, 2012 2:36 AM
To: Hallman, Laurie
Cc: Ben Leduc-Mills
Subject: course design feedback



Hi Laurie,



Thank you again for all of your help. We would greatly appreciate it if
you could pass along our questions to other specialists to assist in our
study design for evaluation of the ioCane, a sensor-based system that
attaches to a blind cane and is used to detect low-hanging objects. We
would like to test the ioCane's effectiveness and would appreciate as much
feedback and insight about a course design as possible. I have provided a
description of the ioCane below, and have included our list of questions
as an attachment.



Thank you very much!



Halley



Description of Technology

We present the design, implementation, and early results of ioCane, a
mobility aid for blind cane users that incorporates the use of ultrasonic
sensors and computer vision algorithms with the Android mobile operating
system, to provide a plug-and-play solution for the visually impaired that
has the potential to significantly enhance mobility and object avoidance
with a minimal learning curve. The system functions by taking in readings
from three seperate ultrasonic sensors placed along the cane and sending
the data to a circuit board built to interface with Android mobile
devices. The board then sends the sensor data (via Bluetooth) to our
ioCane application on the mobile phone, which determines a threshold
indicating whether the user is close to hitting an object. If so, the
application vibrates (increasing intensity with the proximity of the
object) or chimes (3 different tones, dependent on the height of the
object detected) to alert the user to avoid the object. In addition, the
ioCane application runs a series of computer vision algorithms to detect
and alert the user if specific objects of interest are approaching. The
sensors and board can fit directly onto a user's existing cane, are
extremely lightweight (under 400 grams), and can run off battery power. To
our knowledge, the ioCane is the first sensor-based mobility assistance
system to integrate natively with a mobile phone without any modifications
necessary to either the phone or the system, and provides a novel
integration of physical sensors and computer vision to provide navigation
assistance.




--
Halley P Profita

Computer Science Doctoral Candidate 2015 University of Colorado - Boulder
e| hprofita at gmail.com
p| 305.439.4578