Date of Award
Master of Science (MS)
Dr. Delphine Dean, Committee Chair
Dr. Joseph Singapogu, Co-Committee Chair
Dr. Brian Dean
Sensor based motion analysis is employed to assess frequency, severity and duration of Rett syndrome hand stereotypies as well as soft tissue palpation of an arteriovenous fistula. The only prior quantification of Rett symptoms have been visually in a clinical setting; defining palpation skill is largely unprecedented aside from breast tissue examination. We evaluate various sensors used to track motion, measure electromyography, galvanic skin response, and heart rate. The Leap motion controller is evaluated for the viability of tracking hand palpation. Verification tests are performed for determining the feasibility, accuracy, and precision of each sensor. A static phantom was defined as the two endpoints of each of the six fistulas within the palpation simulator and the accuracy of the Leap Motion was <0.9 cm. The 9 DOF motion sensor, EMG sensor, and heart rate sensor all pass their respective verification tests. The galvanic skin response sensor needs further thought into where the electrodes should be placed for proper readings to ensue. All sensors present acceptable precision and accuracy values within the proposed environment; improvements still need to be made for increased performance. Once resolved and perfected, validation studies should verify the preliminary trends of Rett patients’ hand stereotypy quantification and palpation by expert versus novice hemodialysis nurses.
Wells, Jared J., "A Sensor Based Approach to Analyzing Motion in Medical Applications: AV Fistula Cannulation and Rett Syndrome" (2018). All Theses. 2890.