An optimal signal selection method based on feature neighborhood using for human gait mode recognition

Miao Zhang; Ronglei Sun

doi:10.1016/j.bspc.2024.106192

ScienceGate Book Chapters

JOURNAL ARTICLE

An optimal signal selection method based on feature neighborhood using for human gait mode recognition

Miao Zhang Ronglei Sun

Year: 2024 Journal: Biomedical Signal Processing and Control Vol: 93 Pages: 106192-106192 Publisher: Elsevier BV

DOI: 10.1016/j.bspc.2024.106192

Get Full-Text PDF Get Analytical Report

Keywords:

Pattern recognition (psychology) Feature (linguistics) Feature selection Artificial intelligence SIGNAL (programming language) Gait Curse of dimensionality Feature vector Computer science Mode (computer interface) Matrix (chemical analysis) Mathematics Dimensionality reduction Medicine

Metrics

Cited By

0.37

FWCI (Field Weighted Citation Impact)

Refs

0.44

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Prosthetics and Rehabilitation Robotics

Physical Sciences → Engineering → Biomedical Engineering

Diabetic Foot Ulcer Assessment and Management

Health Sciences → Medicine → Endocrinology, Diabetes and Metabolism

Gait Recognition and Analysis

Physical Sciences → Engineering → Biomedical Engineering

An optimal signal selection method based on feature neighborhood using for human gait mode recognition

Metrics

Citation History

Topics

Related Documents

Gait recognition based on sEMG signal using progressive feature selection method

Improving Human Gait Recognition Using Feature Selection

Human gait recognition using orthogonal least square as feature selection

Gait Recognition Based on Feature Selection of sEMG Signals Using PCA-RELM Method

Feature selection for Lidar-based gait recognition