# CAREER: Leveraging Human Neuromotor Learning to Enhance Robotic Exoskeleton Performance

> **NSF 01002526DB NSF RESEARCH & RELATED ACTIVIT** · University of Massachusetts Amherst (MA) · $650,866

## Abstract

This Faculty Early Career Development (CAREER) award supports research seeking to advance our fundamental understanding of how people learn to walk more efficiently with wearable robotic exoskeletons. Wearable robots have the potential to enhance mobility for a wide range of users, including individuals with neurological or musculoskeletal impairments, older adults, and able-bodied individuals. Unlike traditional walking aids, robotic exoskeletons can adapt their mechanical assistance to meet each user's unique needs and adjust over time to optimize gait efficiency. However, current personalization approaches focus primarily on adapting the robot without fully considering the human user's natural ability to learn and adapt. This research project attempts to address this critical gap by investigating novel ways to guide and leverage human neuromotor learning to further enhance the performance of gait-assistive exoskeletons. This award will also support training the next generation of researchers to develop robotic systems that enhance human locomotion through three key activities: (1) hosting a regional locomotion research symposium for students, (2) engaging students in hands-on human-robot physical interaction projects, and (3) raising public awareness of the potential of robotic technology to improve mobility.

The overall goal of this CAREER award is to develop gait-assistive robotic exoskeletons that not only adapt their mechanical assistance to the user but also acti

## Key facts

- **NSF award ID:** 2442120
- **Awardee organization:** University of Massachusetts Amherst (MA)
- **SAM.gov UEI:** VGJHK59NMPK9
- **PI:** Meghan E Huber
- **Primary program:** 01002526DB NSF RESEARCH & RELATED ACTIVIT
- **All programs:** CAREER-Faculty Erly Career Dev, ROBOTICS, HUMAN-ROBOT INTERACTION, WOMEN, MINORITY, DISABLED, NEC
- **Estimated total:** $650,866
- **Funds obligated:** $650,866
- **Transaction type:** Standard Grant
- **Period:** 06/15/2025 → 05/31/2030

## Primary source

NSF Award Search: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2442120

## Citation

> US National Science Foundation, Award 2442120, CAREER: Leveraging Human Neuromotor Learning to Enhance Robotic Exoskeleton Performance. Retrieved via AI Analytics 2026-06-08 from https://api.ai-analytics.org/grant/nsf/2442120. Licensed CC0.

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