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- All Subjects: gait
- Creators: Lee, Hyunglae
- Creators: Lockhart, Thurmon E
The concept of entrainment broadly applies the locking of phases between 2 independent systems [17]. This physical phenomenon can be applied to modify neuromuscular movement in humans during bipedal locomotion. Gait entrainment to robotic devices have shown great success as alternatives to labor intensive methods of rehabilitation. By applying additional torque at the ankle joint, previous studies have exhibited consistent gait entrainment to both rigid and soft robotic devices. This entrainment is characterized by consistent phase locking of plantarflexion perturbations to the ‘push off’ event within the gait cycle. However, it is unclear whether such phase locking can be attributed to the plantarflexion assistance from the device or the sensory stimulus of movement at the ankle. To clarify the mechanism of entrainment, an experiment was designed to expose the user to a multitude of varying torques applied at the ankle to assist with plantar flexion. In this experiment, no significant difference in success of subject entrainment occurred when additional torque applied was greater than a detectable level. Force applied at the ankle varied from ~60N to ~130N. This resulted in successful entrainment ~88\% of the time at 98 N, with little to no increase in success as force increased thereafter. Alternatively, success of trials decreased significantly as force was reduced below this level, causing the perturbations to become undetectable by participants. Ultimately this suggests that higher levels of actuator pressure, and thus greater levels of torque applied to the foot, do not increase the likelihood of entrainment during walking. Rather, the results of this study suggest that proper detectable sensory stimulus is the true mechanism for entrainment.
A knee exoskeleton and ankle assistive device (Robotic Shoe) are developed and used to provide walking assistance. The knee exoskeleton provides personalized knee joint assistive torque during the stance phase. The robotic shoe is a light-weighted mechanism that can store the potential energy at heel strike and release it by using an active locking mechanism at the terminal stance phase to provide push-up ankle torque and assist the toe-off. Lower-limb Kinematic time series data are collected for subjects wearing these devices in the passive and active mode. The changes of kinematics with and without these devices on lower-limb motion are first studied. Orbital stability, as one of the commonly used measure to quantify gait stability through calculating Floquet Multipliers (FM), is employed to asses the effects of these wearable devices on gait stability. It is shown that wearing the passive knee exoskeleton causes less orbitally stable gait for users, while the knee joint active assistance improves the orbital stability compared to passive mode. The robotic shoe only affects the targeted joint (right ankle) kinematics, and wearing the passive mechanism significantly increases the ankle joint FM values, which indicates less walking orbital stability. More analysis is done on a mechanically perturbed walking public data set, to show that orbital stability can quantify the effects of external mechanical perturbation on gait dynamic stability. This method can further be used as a control design tool to ensure gait stability for users of lower-limb assistive devices.
This dissertation examined several hurdles that must be overcome to create a standardized method of calculating the LyE for gait data when collected with an accelerometer. In each of the following investigations, both the Rosenstein et al. and Wolf et al. algorithms as well as three normalization methods were applied in order to understand the extent at which these factors affect the LyE. First, the a priori parameters of time delay and embedding dimension which are required for phase space reconstruction were investigated. This study found that the time delay can be standardized to a value of 10 and that an embedding dimension of 5 or 7 should be used for the Rosenstein and Wolf algorithm respectively. Next, the effect of data length on the LyE was examined using 30 to 1300 strides of gait data. This analysis found that comparisons across papers are only possible when similar amounts of data are used but comparing across normalization methods is not recommended. And finally, the reliability and minimum required number of strides for each of the 6 algorithm-normalization method combinations in both young healthy and elderly adults was evaluated. This research found that the Rosenstein algorithm was more reliable and required fewer strides for the calculation of the LyE for an accelerometer.