Remote Gait Analysis Using Ultra-Wideband Radar Technology Based on Joint Range-Doppler-Time Representation

被引:1
作者
Hadjipanayi, Charalambos [1 ,2 ]
Yin, Maowen [1 ,2 ]
Bannon, Alan [1 ,2 ]
Rapeaux, Adrien [1 ,2 ]
Banger, Matthew [3 ]
Haar, Shlomi [2 ,4 ]
Lande, Tor Sverre [5 ]
McGregor, Alison H. [3 ]
Constandinou, Timothy G. [1 ,2 ]
机构
[1] Imperial Coll London, Dept Elect & Elect Engn, London SW7 2AZ, England
[2] Imperial Coll London, UK Dementia Res Inst, London SW7 2AZ, England
[3] Imperial Coll London, Dept Surg & Canc, MSk Lab, London, England
[4] Imperial Coll London, Dept Brain Sci, London, England
[5] Univ Oslo, Dept Informat, Oslo, Norway
基金
英国医学研究理事会; 英国工程与自然科学研究理事会;
关键词
Ultra wideband radar; Legged locomotion; Radar; Feature extraction; Sensors; Doppler effect; Biomedical monitoring; Doppler analysis; gait variability and asymmetry; impulse-radio ultra-wideband (IR-UWB) radar; in-home gait analysis; spatiotemporal gait features; IDENTIFICATION; CLASSIFICATION; PARAMETERS; LSTM;
D O I
10.1109/TBME.2024.3396650
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Objective: In recent years, radar technology has been extensively utilized in contactless human behavior monitoring systems. The unique capabilities of ultra-wideband (UWB) radars compared to conventional radar technologies, due to time-of-flight measurements, present new untapped opportunities for in-depth monitoring of human movement during overground locomotion. This study aims to investigate the deployability of UWB radars in accurately capturing the gait patterns of healthy individuals with no known walking impairments. Methods: A novel algorithm was developed that can extract ten clinical spatiotemporal gait features using the Doppler information captured from three monostatic UWB radar sensors during a 6-meter walking task. Key gait events are detected from lower-extremity movements based on the joint range-Doppler-time representation of recorded radar data. The estimated gait parameters were validated against a gold-standard optical motion tracking system using 12 healthy volunteers. Results: On average, nine gait parameters can be consistently estimated with 90-98% accuracy, while capturing 94.5% of participants' gait variability and 90.8% of inter-limb symmetry. Correlation and Bland-Altman analysis revealed a strong correlation between radar-based parameters and the ground-truth values, with average discrepancies consistently close to 0. Conclusion: Results prove that radar sensing can provide accurate biomarkers to supplement clinical human gait analysis, with quality similar to gold standard assessment. Significance: Radars can potentially allow a transition from expensive and cumbersome lab-based gait analysis tools toward a completely unobtrusive and affordable solution for in-home deployment, enabling continuous long-term monitoring of individuals for research and healthcare applications.
引用
收藏
页码:2854 / 2865
页数:12
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