Joint torque feedback (JTF) is a new and promising means of kinesthetic feedback to provide information to a person or guide them during a motion task. However, little work has been done to apply the torque feedback to a person.
This project evaluates the properties of JTF as haptic feedback, starting from the fabrication of a lightweight elbow haptic exoskeleton.
A cheap hobby motor and easily accessible hardware are introduced for manufacturing and open-sourced embedded architecture for data logging. The total cost and the weights are $500 and 509g.
Also, as the prerequisite step to assess the JTF in guidance, human perceptual ability to detect JTF was quantified at the elbow during all possible static and dynamic joint statuses. JTF slopes per various joint conditions are derived using the Interweaving Staircase Method.
For either directional torque feedback, flexional motion requires 1.89-2.27 times larger speed slope, in mNm/(°/s), than the extensional motion. In addition, we find that JTFs during the same directional muscle's isometric contraction yields a larger slope, in mNm/mNm, than the opposing direction (7.36 times and 1.02 times for extension torque and flexion torque).
Finally, the guidance performance of the JTF was evaluated in terms of time delay and position error between the directed input and the wearer's arm.
When studying how much the human arm travels with JTF, the absolute magnitude of the input shows more significance than the duration of the input (p-values of <0.0001 and 0.001).
In the analysis of tracking the pulse input, the highest torque stiffness, 95 mNm/°, is responsible for the smallest position error, 6.102 ± 5.117°, despite the applied torque acting as compulsory stimuli. / Doctor of Philosophy / Joint torque feedback (JTF) is a new and promising means of haptic feedback to provide information to a person or guide them during a motion task. However, little work has been done to apply the torque feedback to a person, such as determining how well humans can detect external torques or how stiff the torque input should be to augment a human motion without interference with the voluntary movement.
This project evaluates the properties of JTF as haptic feedback, starting from the fabrication of a lightweight elbow haptic exoskeleton.
The novelty of the hardware is that we mask most of the skin receptors so that the joint receptors are primarily what the body will use to detect external sensations. A cheap hobby motor and easily accessible hardware are introduced for manufacturing and open-sourced software architecture for data logging. The total cost and the weight are $500 and 509g.
Also, as the prerequisite step to assess the JTF in guidance, human perceptual ability to detect JTF was quantified at the elbow during all possible static and dynamic joint statuses.
A psychophysics tool called Interweaving Staircase Method was implemented to derive torque slopes per various joint conditions.
For either directional torque feedback, flexional motion requires 1.89-2.27 times larger speed slope, in mNm/(°/s) than the extensional motion. In addition, the muscles' isometric contraction with the aiding direction required a larger slope, in $mathrm{mNm/mNm}$ than the opposing direction (7.36 times and 1.02 times for extension torque and flexion torque).
Finally, the guidance performance of the JTF was evaluated in terms of time delay and position error between the directed input and the wearer's arm.
When studying how much the human arm travels with JTF, the absolute magnitude of the input shows more significance than the duration of the input (p-values of <0.0001 and 0.001).
In the analysis of tracking the pulse input, the highest torque stiffness, 95 mNm/°, is responsible for the smallest position error, 6.102 ± 5.117°, despite the applied torque acting as compulsory stimuli.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/114749 |
| Date | 28 October 2021 |
| Creators | Kim, Hubert |
| Contributors | Mechanical Engineering, Asbeck, Alan Thomas, Leonessa, Alexander, Wicks, Alfred L., Ben-Tzvi, Pinhas, Nussbaum, Maury A. |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Dissertation |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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