SUMMARY

Exoskeleton technology holds a large potential to help improve human mobility and physical capability. Most of the previous exoskeleton studies focused on targeting the hip or the ankle joint due to their large contributions to the power generation during level walking. However, the knee joint still plays an important role during slope walking, and there are still gaps in the field to improve/augment human mobility more effectively using a knee exoskeleton. For able-bodied adults, the role of the knee joint becomes more significant during sloped walking in terms of mechanical power. In addition, patients walking in genu recurvatum gait is another potential population that can benefit from the powered knee exoskeleton as the assistance can help the user achieve an improved walking pattern. The main objective of my proposal is to create effective controllers for the knee exoskeleton and evaluate the effectiveness of the powered assistance for enhancing human locomotion for both able-bodied adults and the patient population. The proposed study will focus on three key objectives: 1) Evaluate the biomechanical effectiveness of assistance strategies for able-bodied adults during incline walking, 2) Create an environmental/user-adaptive controller for the knee exoskeleton using a machine learning approach to enable adaptive assistance to the able-bodied user, 3) Explore the use of a robotic knee exoskeleton for improving gait quality for patients walking in genu recurvatum gait.