Abstract
This paper presents a novel multi-axis robotic platform for the characterization of two important neuromuscular properties of the human ankle: mechanical impedance and reflex responses. The platform is capable of producing highly accurate position perturbations up to an angular speed of 200°/s and emulating a wide range of haptic environments in two degree-of-freedom (DOF) of the ankle: dorsiflexion-plantarflexion (in the sagittal plane) and inversion-eversion (in the frontal plane). This unique feature allows us to seamlessly simulate realistic mechanical environments and to transiently perturb the ankle for the characterization of its neuromuscular properties. The position controller achieved the accuracy of 0.05° even under the loading condition (a subject of 95 kg standing on the platform). The haptic controller could successfully emulate a wide range of mechanical environments, from compliant to rigid (50-1000 Nm/rad), with an error of 2% of the commanded values. We further validated that the proposed platform could reliably estimate the stiffness of a mockup (17.8-171.0 Nm/rad) that resembles the human ankle within an error of 1.6%. Finally we demonstrated that the platform could be successfully utilized to elicit medium-latency and long-latency reflex responses of the ankle muscles. Implications for future ankle studies are discussed.
Original language | English (US) |
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Title of host publication | ICRA 2017 - IEEE International Conference on Robotics and Automation |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 511-516 |
Number of pages | 6 |
ISBN (Electronic) | 9781509046331 |
DOIs | |
State | Published - Jul 21 2017 |
Event | 2017 IEEE International Conference on Robotics and Automation, ICRA 2017 - Singapore, Singapore Duration: May 29 2017 → Jun 3 2017 |
Other
Other | 2017 IEEE International Conference on Robotics and Automation, ICRA 2017 |
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Country/Territory | Singapore |
City | Singapore |
Period | 5/29/17 → 6/3/17 |
ASJC Scopus subject areas
- Control and Systems Engineering
- Software
- Artificial Intelligence
- Electrical and Electronic Engineering