Dual-Channel FMCW Harmonic Radar With Active Tags at 61/122 GHz for Phase-Based Gait Parameter Monitoring

Optimized rehabilitation after joint replacement surgery or other medical procedures affecting the musculoskeletal system requires practical movement analysis systems that enable the continuous and precise gait monitoring of patients in everyday life. To address this need, we present a system consisting of a frequency-modulated continuous-wave (FMCW) radar sensor and active frequency-doubling tags designed for accurate long-term monitoring. By using a harmonic measurement concept in which the tags double the frequency of the transceiver signal, a high signal-to-interference-and-noise ratio (SINR) is achieved, ensuring that the tags stand out clearly from the clutter produced by the leg. With our system, we particularly focus on a phase-based angle determination within the sagittal plane, enabled by two closely spaced receive antennas, allowing for more accurate and reliable gait monitoring compared to our previous system based on a bilateration method. By utilizing millimeter waves in the frequency range 56-63 GHz for transmission and 112-126 GHz for reception, we achieve a compact sensor size sufficient for the application. Based on measurements taken in a gait laboratory, we demonstrate that our system is capable of measuring the distance and angle between the sensor and tags during gait with an accuracy of up to 1.73 mm and 0.93°, respectively, using a stationary camera-based motion capture (MoCap) system as a reference.

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Publication Details

Journal
IEEE Journal of Radio Frequency Identification
Published
2025-01-01
DOI
https://doi.org/10.1109/jrfid.2025.3597021
Citations
2
Primary Topic
Non-Invasive Vital Sign Monitoring
Type
article
Field-Weighted Citation Impact
1.35

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article

Dual-Channel FMCW Harmonic Radar With Active Tags at 61/122 GHz for Phase-Based Gait Parameter Monitoring

Patrick Kwiatkowski, Nils Pohl, Steffen Hansen, Falko Heitzer et al.
2 citations
IEEE Journal of Radio Frequency Identification
Non-Invasive Vital Sign Monitoring
1.35
article

Dual-Channel FMCW Harmonic Radar With Active Tags at 61/122 GHz for Phase-Based Gait Parameter Monitoring

Patrick Kwiatkowski, Nils Pohl, Steffen Hansen, Falko Heitzer, Francisco Geu Flores, Alexander Orth
article en
2 citations

Abstract

Optimized rehabilitation after joint replacement surgery or other medical procedures affecting the musculoskeletal system requires practical movement analysis systems that enable the continuous and precise gait monitoring of patients in everyday life. To address this need, we present a system consisting of a frequency-modulated continuous-wave (FMCW) radar sensor and active frequency-doubling tags designed for accurate long-term monitoring. By using a harmonic measurement concept in which the tags double the frequency of the transceiver signal, a high signal-to-interference-and-noise ratio (SINR) is achieved, ensuring that the tags stand out clearly from the clutter produced by the leg. With our system, we particularly focus on a phase-based angle determination within the sagittal plane, enabled by two closely spaced receive antennas, allowing for more accurate and reliable gait monitoring compared to our previous system based on a bilateration method. By utilizing millimeter waves in the frequency range 56-63 GHz for transmission and 112-126 GHz for reception, we achieve a compact sensor size sufficient for the application. Based on measurements taken in a gait laboratory, we demonstrate that our system is capable of measuring the distance and angle between the sensor and tags during gait with an accuracy of up to 1.73 mm and 0.93°, respectively, using a stationary camera-based motion capture (MoCap) system as a reference.

IEEE Journal of Radio Frequency IdentificationVol. 9
Fraunhofer Institute for High Frequency Physics and Radar Techniques (DE), University of Duisburg-Essen (DE), Ruhr University Bochum (DE)
Bundesministerium für Bildung und Forschung
Affordable and clean energy
Openalex Percentile: Top 18%
Non-Invasive Vital Sign Monitoring
1.35
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