Project ARM

=Problem Definition=

Individuals recovering from post-stroke arm impairments spend significantly more time conducting therapeutic exercise at home without therapist supervision than they spend doing supervised therapy in a clinical setting. It is difficult to quantify the amount and quality of arm usage that takes place between supervised therapy sessions, which would be useful to know both as an indicator of functional recovery, and also as a way to monitor activity level and its impact on motor recovery.

=Motivation=

As the leading cause of serious, long term disability, strokes affect about 795,000 people in the United States annually. Many times, this leads to loss of mobility in one of the patient’s arms.

=Objective=

Create a device to aid therapists in patient treatment which will:


 * 1) Be comfortable and breathable
 * 2) Be able to be donned/ doffed in under 30 seconds
 * 3) Interface with an Android application via Bluetooth
 * 4) Compare data points against an established baseline

=Design Work Examples=

Back Mounted Hardware Case Designs

 * Designed for initial harness

Wrist Mounted Hardware Case Designs

 * Bulky & unable to house all necessary components

Harness Designs

 * Need for multiple size options
 * Unable to switch arms
 * Difficult to don/dof

Hardware Prototype Version

 * Contains multiplexer, orientation sensors, and Arduino Feather

Phone App Flow


=Work Product Examples=

Upper Arm Mounted Hardware Case

 * Contains power supply, Arduino Feather, multiplexer, & absolute orientation sensor
 * Soft, curved Ninjaflex bottom for comfort and stability
 * 4.6x3.5x0.62 inches

Wrist/ Back Mounted Hardware Case

 * Contains BNO055 absolute orientation sensor
 * Compact, minimalistic, and allows easy access
 * 1.2x1.5x0.5 inches

Harness

 * Adjustable Velcro straps
 * Back and wrist sensors
 * Upper arm sensor

Phone App Screenshots

 * Generates placeholder baseline data which can be compared against placeholder exercise data

=Future Goals and Direction=


 * To allow patients to be able to don/ doff with one arm
 * To increase the sensor's stability and accuracy of readings
 * To complete a user-friendly application to follow progress of prescribed exercise routines
 * To integrate a physical On/ Off switch into the hardware

=Team Members=

=Document Archive=

Meeting Minutes


= Special Thanks =

Special thanks to Melissa Bogert, Chris Bitikofer, Sebastian Rueda-Parra, Dr. Matt Godfrey, Danielle Deschler, Prof. Lori Wahl, Mr. Bruce Bolden, Dr. Manuel Welhan, and Dr. Eric Wolbrecht for supporting this project.

= References =