Evidence map›Paper›PMID 41902013›Full record

ArticleSensors (Basel, Switzerland)2026

Millimeter-Wave Body-Centric Radar Sensing for Continuous Monitoring of Human Gait Dynamics.

Yoginath Ganditi, Mani S Chilakala, Zahra Najafi, Mohammed E Eltayeb, Warren D Smith

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Yoginath GanditiDepartment of Electrical and Electronic Engineering, California State University, Sacramento, CA 95819, USA.ORCID 0009-0009-6622-6241
Mani S ChilakalaDepartment of Electrical and Electronic Engineering, California State University, Sacramento, CA 95819, USA.ORCID 0009-0003-8024-1815
Zahra NajafiDepartment of Electrical and Electronic Engineering, California State University, Sacramento, CA 95819, USA.
Mohammed E EltayebDepartment of Electrical and Electronic Engineering, California State University, Sacramento, CA 95819, USA.ORCID 0000-0003-2229-1649
Warren D SmithDepartment of Electrical and Electronic Engineering, California State University, Sacramento, CA 95819, USA.ORCID 0009-0002-1564-1102

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gait is a sensitive marker of mobility decline and fall risk, motivating unobtrusive sensing methods that can extract spatiotemporal parameters outside specialized gait laboratories. This paper presents a physics-based comparison of two millimeter-wave frequency-modulated continuous-wave (FMCW) radar deployment paradigms using a low-cost, system-on-chip (SoC) 60 GHz Infineon BGT60TR13C radar sensor: (i) a fixed (tripod-mounted) corridor observer and (ii) a shoe-mounted body-centric configuration attached to the medial side of the left shoe. Four healthy adult author-participants performed repeated 30 s corridor trials under five gait styles (regular, slow, fast, simulated festination, and simulated freezing-of-gait), including brief pauses during turns; an empty-corridor recording was acquired to characterize static clutter. Step events were detected using peak-picking on foot-related velocity envelopes with adaptive thresholds, and step count, cadence, step time, and step-time variability were derived. Performance of the fixed and shoe-mounted configurations was quantitatively compared to video ground truth using mean absolute percentage error (MAPE) for step count estimation. Across all gait styles, the shoe-mounted FMCW radar consistently reduced step-count error relative to the fixed corridor-mounted configuration, with the largest gains under irregular patterns (e.g., festination: 37.1% fixed vs. 9.6% shoe-mounted). These findings highlight the advantages of body-centric millimeter-wave radar sensing and support low-cost SoC radar as a pathway toward wearable, privacy-preserving gait monitoring in real-world environments.

Indexed as

Biosensing TechniquesGaitRadarAdultHumansMonitoring, PhysiologicShoescorridor-based monitoringdigital healthfixed (tripod-mounted) radarFMCW radargait analysismicro-Dopplermillimeter-wave radarshoe-mounted radarspatiotemporal gait parametersstep detection

Identifiers

PMID41902013
PMCPMC13029834

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.