Fusion of Human Gaze and Machine Vision for Predicting Intended Locomotion Mode-Reference-Cited by-同舟云学术

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Fusion of Human Gaze and Machine Vision for Predicting Intended Locomotion Mode

Published:2022 Issue: Volume:30 Page:1103-1112
ISSN:1534-4320
Container-title:IEEE Transactions on Neural Systems and Rehabilitation Engineering
language:
Short-container-title:IEEE Trans. Neural Syst. Rehabil. Eng.

Author:

Li Minhan¹^ORCID,Zhong Boxuan²^ORCID,Lobaton Edgar²^ORCID,Huang He¹^ORCID

Affiliation:

1. NCSU/UNC Joint Department of Biomedical Engineering, North Carolina State University and University of North Carolina at Chapel Hill, Raleigh, NC, USA

2. Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC, USA

Funder

National Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Biomedical Engineering,General Neuroscience,Internal Medicine,Rehabilitation

Link

https://ieeexplore.ieee.org/ielam/7333/9695946/9760454-aam.pdf

Reference37 articles.

1. The farthest point strategy for progressive image sampling

2. PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

3. Mobilenets: Efficient convolutional neural networks for mobile vision applications;howard,2017

4. Walking cadence (steps/min) and intensity in 21–40 year olds: CADENCE-adults

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