| NSF Org: |
IIS Division of Information & Intelligent Systems |
| Recipient: |
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| Initial Amendment Date: | August 8, 2023 |
| Latest Amendment Date: | August 8, 2023 |
| Award Number: | 2306660 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Thomas Martin
tmartin@nsf.gov (703)292-2170 IIS Division of Information & Intelligent Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | August 15, 2023 |
| End Date: | July 31, 2027 (Estimated) |
| Total Intended Award Amount: | $720,000.00 |
| Total Awarded Amount to Date: | $720,000.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
2601 WOLF VILLAGE WAY RALEIGH NC US 27695-0001 (919)515-2444 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
1840 Entrepreneur Dr; EBIII 4402D Raleigh NC US 27607-7115 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | Smart and Connected Health |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
This project will develop a novel exoskeleton to improve walking in real-world environments. When people age and their muscle functions decline, it can limit their ability to generate enough ankle push-off power to walk normally. Mobility-challenged older adults often walk unnaturally and inefficiently. For example, they may compensate for reduced ankle push-off action by overusing the hip. This behavior not only affects the long-term health of the related leg joints, but also causes accelerated decline of physical mobility. Such mobility decline has profound impacts on older adults? lifestyles, as well as their long-term physical and psychological health. As walking speed decreases, an elderly individual may experience unexpected difficulties in his/her daily activities (e.g., being unable to cross a busy street before the light changes). When walking becomes more strenuous, an older adult is more likely to be physically inactive and suffer from the multiple health problems associated with such a sedentary lifestyle (high blood pressure, obesity, depression, etc.). Motivated by this significant challenge, our research in this project will be dedicated to the development of a new robotic ankle-foot orthosis (exoskeleton) system to assist the user?s ankle movement when walking in real-world environments. With the robotic orthosis? assistance, older adults may walk more naturally and efficiently with the enhanced ankle push-off, and thus enjoy significantly improved gait ability and physical mobility in their daily lives.
The project will conduct multiple research activities towards the creation of the proposed robotic ankle-foot orthosis (AFO) system. It will design and fabricate a compact and lightweight Daily-Use Robotic Ankle-Foot Orthosis (DUR-AFO) to provide the desired physical assistance with little additional load to the user. Through its powered assistance to the ankle, the DUR-AFO is anticipated to induce elderly individuals to augment their ankle push-off for a more natural and efficient gait (closer to younger healthy gait) and thus improve their gait ability. Further, the project will conduct biomechanical research to investigate the human gait-control mechanisms under independently controlled bilateral robot assistance in real-world locomotion (walking and turning); we will also explore the novel approach of using real-time information feedback (vibrotactile prompts, audio cues, etc.) to empower and motivate users to maintain a desired level of muscle efforts while enjoying the powered assistance by the DUR-AFO. Finally, the project will develop a novel Reinforcement Learning (RL)-based cyber system as the basis of the human-robot synergistic collaborative system, providing multiple important functions such as adapting the robot control parameters for gait quality optimization, determining the real-time feedback to the human user, and identifying the human motion intent in the form of the desired mode of locomotion. Overall, this novel human-robot synergistic collaboration framework not only optimizes the performance of the robot assistance to the human movement, but also promotes the human user?s beneficial behavioral changes (?maintaining a desired level of muscle efforts in walking exercise?) towards the shared goal of the human-robot system (?improving the human?s gait ability and overall mobility in daily-life activities?). This project is jointly funded by Smart and Connected Health and the Established Program to Stimulate Competitive Research (EPSCoR).
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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