期刊
IEEE SENSORS JOURNAL
卷 17, 期 8, 页码 2320-2321出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSEN.2017.2678484
关键词
Micro-Doppler radar; gait classification; falls; elderly; principal component analysis
资金
- Ministry of Internal Affairs and Communications of Japan
- JSPS KAKENHI [16K16093]
- Grants-in-Aid for Scientific Research [16K16093] Funding Source: KAKEN
This letter presents a gait classification technique for the identification of individuals with different gait patterns using simulated micro-Doppler radar remote sensing data. Proposed feature parameters for the classification are principal components of velocities extracted via micro-Doppler radar signals generated using motion capture-based kinematic data. Distinct differences were found in the proposed parameters among three groups of subjects with different gait patterns: healthy young and elderly adults, and elderly adults with a history of falls (elderly fallers).
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