Year of Graduation
Douglas Van Citters, Ph.D., Ryan Chapman, Ph.D.
Thesis (Senior Honors)
Wearable sensors were leveraged to develop two methods for computing hip joint angles and moments during walking and stair ascent that are more portable than the gold standard. The Insole-Standard (I-S) approach replaced force plates with force-measuring insoles and achieved results that match the curvature of results from similar studies. Peaks in I-S kinetic results are high due to error induced by applying the ground reaction force to the talus. The Wearable-ANN (W-A) approach combines wearables with artificial neural networks to compute the same results. Compared against the I-S, the W-A approach performs well (average rRMSE = 18%, R2 0.77).
Dartmouth Digital Commons Citation
McCabe, Megan V., "Utilizing Neural Networks and Wearables to Quantify Hip Joint Angles and Moments During Walking and Stair Ascent" (2020). ENGS 88 Honors Thesis (AB Students). 17.