Faculty Advisor

Claypool, Mark L.

Faculty Advisor

Lammert, Adam


Even mild traumatic brain injury (TBI) can lead to permanent damage if not treated immediately. In order to provide faster and more convenient methods to monitor TBI, speech and gait were explored as concussion indicators. Smartphones were used as sensors to record audio and acceleration data on the speech and gait of ten concussed and twelve non-concussed participants. Data from the two groups was statistically analyzed to determine significant differences with the hope that it could eventually lead to a more efficient method of diagnosing concussions. Although collecting speech and gait data through the smartphone was quick and convenient, there were no statistically significant differences found between the means, standard deviation, kurtosis, and skewness of the two groups.


Worcester Polytechnic Institute

Date Accepted


Project Type

Interactive Qualifying Project



Advisor Department

Computer Science

Advisor Department

Biomedical Engineering