Design of actuation system and minimization of sensor configuration for gait event detection for Gen 3.0 Portable Powered Ankle-Foot Orthosis (PPAFO)

Wang, Ziming

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https://hdl.handle.net/2142/92719 Copy

Description

Title

Design of actuation system and minimization of sensor configuration for gait event detection for Gen 3.0 Portable Powered Ankle-Foot Orthosis (PPAFO)

Author(s)

Wang, Ziming

Issue Date

2016-06-20

Director of Research (if dissertation) or Advisor (if thesis)

Hsiao-Wecksler, Elizabeth T.

Department of Study

Mechanical Sci & Engineering

Discipline

Mechanical Engineering

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(s)

• Portable Powered Ankle-Foot Orthosis (PPAFO)
• Powered Ankle-Foot Orthosis (PAFO)
• Pneumatic
• Gear design
• Powered Orthosis
• Inertial measurement units (IMU)
• Wearable sensors
• Gait
• Gait event detection
• Gait state estimation
• exoskeleton
• Kalman filter
• Principle component analysis (PCA)

Abstract

Powered ankle-foot orthoses (AFOs), which are capable of providing assistive torque at the ankle joint, have significant potential as both assistance and rehabilitation devices. Technology advancements have led to great progression in the development of powered AFOs. Our group had developed the Portable Powered Ankle-Foot Orthosis (PPAFO) that was capable of providing bidirectional assistive torque at the ankle joint. Two generations of the PPAFO were previously developed. Both designs used two different off-the-shelf rotary actuators. This thesis consists of two studies focusing on the development of a new compact higher torque actuation system and the identification of a minimum sensor configuration for gait event detection for a powered AFO. Study 1 presents the design and evaluation of a new actuation system for the PPAFO (Generation 3.0). The actuation system utilized two dual-action linear actuators and a customized gear train. Compared with the previous designs, it generated higher torque and power while providing a thinner lateral profile. The new design had a total weight of (680g) and was capable of generating 32 Nm torque and 110 W power. While running under the same torque and power level as the previous designs, the new design offered better longevity (42.9% and 81.4% increases in normalized run time for test bench emulation and treadmill walking). Although the overall weight of the new actuation system had a 20% increase compared with previous design, it could generate 166.7% more torque and 120% more power, which will enable us to test the system at various torque and power settings. Study 2 investigated the minimum sensor configuration for detecting gait events. Knowledge of the expected orientation and behavior of a limb as related to specific events during the gait cycle (or state timing as a function of the percentage of the gait cycle, % GC) is essential to allow appropriate control of a powered AFO. A total of five sensors were selected (two force sensitive sensors, one ankle angle sensor, and two inertial measurement units (IMU)). The performances of selected sensor configurations were quantified and compared through state-based and event-based approaches in terms of gait state estimation and gait event detection timing, respectively. Gait data were collected from five healthy subjects while walking on a treadmill wearing the Gen 3.0 PPAFO. Results indicated that, while single IMU configurations (located on the shank or foot) both outperformed all other configurations (mean state estimation error: < 2% GC; mean event detection timing error: < 23 ms), the shank IMU was able to detect more gait events than the foot IMU. Since more detectable events could improve the system's robustness (i.e., adjusting to variable speeds) by updating estimation more frequently, a single shank IMU configuration was recommended for powered AFO applications.

Graduation Semester

2016-08

Type of Resource

text

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http://hdl.handle.net/2142/92719

Copyright and License Information

Copyright 2016 Ziming Wang

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