Biological Stiffness Measurement

The aim of the project is to design and develop a handheld device that can accurately measure the stiffness of a biological tissue, specifically a brain in vivo.

Background
Currently doctors have just been using their fingers to attempt to get an estimation on brain stiffness for use as a symptom of a disease. Doctors can use magnetic resonance elastography (MRE) to obtain stiffness, but there really isn't a device in place to in a matter of moments determine biological tissues stiffness. Brain stiffness has been investigated increasingly as an indicator of neurological diseases, including Alzheimer's disease.

Deliverables

 * Concept sketches/CAD models of the device with sensors in place
 * Final machined device
 * Matlab and Arduino programs used to obtain raw data from sensors and send it to computation in order to establish a best fit modulus of elasticity

Previous Methods
While finding the elastic modulus of a metal can be done quite easily, our problem is finding that of a biological tissue which reacts very differently when an external force is introduced. There have been experiments performed to determine the elastic modulus of biological tissues, they are with devices that can't be made mobile, or devices that will either endanger the brain physically or through the introduction of foreign bacteria. Our findings on previous methods are shown below.

Biological Tissue
Biological tissue stiffness operates differently than that of metals, as seen in the figure below in which a pig spleen was tested.



We will be using a least-squares curve-fitting algorithm in order to map a best-fit curve to our force and indentation depth data points as seen below



Testing Implementation
Work needs to be done to determine the accuracy of our sensors for the project.

Ultrasonic Sensor
The Ultrasonic (US) sensor we are using from Balluff will read the distance to the biological tissue surface. Because the brain is a curved surface, we want to know where on the curved surface the device is reading. To test this distance we 3D printed a spherical object with a known radius as well as a portion of human brain for testing.

Load Cell
The Force sensor we ordered from DigiKey.

Meeting Minutes

 * [[Media:Nt9-12_meeting.pdf|September 12, 2016]]


 * [[Media:Nt9-15_meeting.pdf|September 15, 2016]]


 * [[Media:Nt9-19_meeting.pdf|September 19, 2016]]


 * [[Media:Nt9-22_meeting.pdf|September 22, 2016]]


 * [[Media:Nt9-26_meeting.pdf|September 26, 2016]]


 * [[Media:Nt9-29_meeting.pdf|September 29, 2016]]


 * [[Media:Nt10-3_meeting.pdf|October 3, 2016]]


 * [[Media:Nt10-6_meeting.pdf|October 6, 2016]]


 * [[Media:Nt10-10_meeting.pdf|October 10, 2016]]


 * [[Media:Nt10-13_meeting.pdf|October 13, 2016]]


 * [[Media:Nt10-17_meeting.pdf|October 17, 2016]]


 * [[Media:Nt10-20_meeting.pdf|October 20, 2016]]


 * [[Media:Nt10-24_meeting.pdf|October 24, 2016]]


 * [[Media:Nt10-27_meeting.pdf|October 27, 2016]]


 * [[Media:Nt10-31_meeting.pdf|October 31, 2016]]


 * [[Media:Nt11-3_meeting.pdf|November 3, 2016]]


 * [[Media:Nt11-14_meeting.pdf|November 14, 2016]]


 * [[Media:Nt11-17_meeting.pdf|November 17, 2016]]

Design Review
[[Media:NT_Design_Review.pdf|Design Review Presentation]]

Project Schedule
[[Media:NT_schedule.pdf|Gantt Chart]]

Technical Specification Data

 * [[Media:Honeywell-sensing-force-sensors-FSS-product-sheet--965250.pdf|Force sensor datasheet]]


 * [[Media:Datasheet_223120_GL.pdf|Ultrasonic sensor datasheet]]