Ball, John E.
Burch V, Reuben F.
Date of Degree
Graduate Thesis - Open Access
Master of Science
The ankle joint complex is a common source of injury for various demographics and is often observed during gait analysis. I investigate using soft robotic sensors as a means for collecting kinematic data at the ankle joint complex. I validate the linearity of these sensors by measuring stretch against extension and against stretch from frontal and sagittal planar foot movements using a wooden ankle mockup. I then conduct a study involving ten participants who perform repetitive trials of four foot movements (plantarflexion, dorsiflexion, inversion and eversion) using ten different locations. Four optimal locations were identified for these movements based on linearity, accuracy, robustness, and consistency. Lastly, I validated soft robotic sensors against the human gait cycle. Twenty participants were recruited and performed twelve trials, walking across a flat surface and a cross-sloped surface while motion capture data and soft robotic sensor data was collected.
Mississippi State University (MSU) Office of Research and Development (ORED) undergraduate research grant/MSU Bagley College of Engineering Working Group grants for the Multi–Sensor Working Group and the Wearables Working Group NSF 18-511—Partnerships for Innovation award number 1827652
Saucier, David, "Application of soft robotic sensors to predict foot and ankle kinematic measurements" (2020). Theses and Dissertations MSU. 716.