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Toward Unobtrusive In-Home Gait Analysis Based on Radar Micro-Doppler Signatures

https://doi.org/10.1109/tbme.2019.2893528
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33/33 checkable references clean · checked 2026-07-26

Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.

11 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.

The 33 checked references that resolve
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Operational assessment and adaptive selection of micro‐Doppler features
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A kinect-based human micro-doppler simulator
resolves10.1109/ICASSP.2017.7952908
New analysis of radar micro-Doppler gait signatures for rehabilitation and assisted living
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Application of a continuous wave radar for human gait recognition
resolves10.1109/RADAR.2012.6212271
Evaluation of a micro-Doppler classification method on mm-wave data
resolves10.1109/TAES.2017.2740098
Fall Detection Using Deep Learning in Range-Doppler Radars
resolves10.1109/RADAR.2018.8378687
Radar classification of human gait abnormality based on sum-of-harmonics analysis
resolves10.1109/TGRS.2018.2816812
Indoor Person Identification Using a Low-Power FMCW Radar
resolves10.1109/TGRS.2009.2012849
Human Activity Classification Based on Micro-Doppler Signatures Using a Support Vector Machine
resolves10.1049/iet-rsn.2015.0084
Features for micro‐Doppler based activity classification
resolves10.1049/iet-rsn.2014.0551
Recognition of humans based on radar micro‐Doppler shape spectrum features
resolves10.1016/j.jbiomech.2004.02.047
Quantification of human motion: gait analysis—benefits and limitations to its application to clinical problems
resolves10.1111/jgs.13393
Mobility Device Use in Older Adults and Incidence of Falls and Worry About Falling: Findings from the 2011–2012 National Health and Aging Trends Study
resolves10.3390/s120202255
Gait Analysis Using Wearable Sensors
resolves10.1109/TBME.2017.2665438
Freezing of Gait Detection in Parkinson's Disease: A Subject-Independent Detector Using Anomaly Scores
resolves10.1109/LGRS.2015.2491329
Human Detection and Activity Classification Based on Micro-Doppler Signatures Using Deep Convolutional Neural Networks
resolves10.1109/TBME.2009.2036732
Unobtrusive and Ubiquitous In-Home Monitoring: A Methodology for Continuous Assessment of Gait Velocity in Elders
resolves10.1201/9781315155340
Radar for Indoor Monitoring
resolves10.1109/TBME.2014.2319333
Quantitative Gait Measurement With Pulse-Doppler Radar for Passive In-Home Gait Assessment
resolves10.3390/s140203362
Gait Analysis Methods: An Overview of Wearable and Non-Wearable Systems, Highlighting Clinical Applications
resolves10.1109/LGRS.2014.2336231
Human Detection Using Doppler Radar Based on Physical Characteristics of Targets
resolves10.1109/TBME.2014.2367038
Doppler Radar Fall Activity Detection Using the Wavelet Transform
resolves10.1109/MSP.2015.2502784
Radar Signal Processing for Elderly Fall Detection: The future for in-home monitoring
resolves10.1109/TAES.2014.130762
A novel algorithm for radar classification based on doppler characteristics exploiting orthogonal Pseudo-Zernike polynomials
resolves10.1049/PBRA034E
Radar Micro-Doppler Signatures: Processing and Applications
resolves10.1109/TBME.2016.2536438
Gait Rhythm Fluctuation Analysis for Neurodegenerative Diseases by Empirical Mode Decomposition
resolves10.1109/TBME.2015.2433935
Eight-Week Remote Monitoring Using a Freely Worn Device Reveals Unstable Gait Patterns in Older Fallers
resolves10.1109/RADAR.2017.7944431
Radar-based human gait recognition in cane-assisted walks
resolves10.1049/iet-rsn.2015.0113
Classification of micro‐Doppler signatures of human motions using log‐Gabor filters
resolves10.1155/2010/389716
A Human Gait Classification Method Based on Radar Doppler Spectrograms
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Analysis of Multivariate and High-Dimensional Data
resolves10.1109/TAES.2018.2799758
Deep convolutional autoencoder for radar-based classification of similar aided and unaided human activities
resolves10.1049/iet-rsn.2016.0055
Micro‐Doppler‐based in‐home aided and unaided walking recognition with multiple radar and sonar systems
The 11 references without a DOI — listed, not checked
no DOI — not checkedUsing micro-Doppler radar signals for human gait detection
no DOI — not checkedref31
no DOI — not checkedSDR-KIT 2400AD
no DOI — not checkedref35
no DOI — not checkedRadar fall detectors: A comparison
no DOI — not checkedMultiple joint-variable domains recognition of human motion
no DOI — not checkedRadar fall motion detection using deep learning
no DOI — not checkedref29
no DOI — not checkedA time-frequency classifier for human gait recognition
no DOI — not checkedCoupled harmonics: Estimation and detection
no DOI — not checkedA tutorial on principal component analysis
What this badge says. CiteStamped means the CHECKABLE references of this work were clean at the dated check: each resolved to a known work in a public registry, and none carried a retraction notice at that time. It says nothing about the quality, findings, or importance of the work itself, and nothing about references deposited without a DOI.

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