5 accepted papers
Traditional robotic knee-ankle prostheses categorize ambulation modes such as level walking, ramps, and stairs. However, human movement scales continuously across various states rather than discretely, making traditional mode classifiers inadequate for accurate intent recognition. This paper propose
Post-stroke gait is slow, energetically costly, and unstable. Rehabilitation is necessary to encourage, retrain, and assist proper gait mechanics in stroke survivors. Evidence indicates robotic ankle exoskeletons can improve gait outcomes in stroke survivors, however challenges remain with proper lo
Dynamically altering the parameters for assistance in a lower limb prosthesis is a challenge that depends directly on the ability to estimate gait parameters. Machine learning algorithms present an opportunity to develop methods for continuously determining walking speed in different conditions. Cur
Cervical spinal cord injury (SCI) can severely impact hand motor and sensory function, and accordingly, patients with SCI are often unable to complete basic everyday tasks without assistance. In recent years, there has been an increase in hand exoskeleton research due to their distinct advantages fo…
Developing intelligent prosthetic controllers to recognize user intent across users is a challenge. Machine learning algorithms present an opportunity to develop methods for predicting user's locomotion mode. Currently, linear discriminant analysis (LDA) offers the standard solution in the state-of-