期刊论文详细信息
Signals
Development of an Area Scan Step Length Measuring System Using a Polynomial Estimate of the Heel Cloud Point
Joseph K. Muguro1  Minoru Sasaki1  Nursyuhada Binti Haji Kadir1  Kojiro Matsushita1  Senanayake Mudiyanselaga Namal Arosha Senanayake2 
[1] Department of Mechanical Engineering, Gifu University, 1-1 Yanagido, Gifu 501-1193, Japan;Mathematical & Computing Sciences, Universiti Brunei Darussalam, Jalan Tungku Link, Gadong BE1410, Brunei;
关键词: LiDAR;    step length;    distance measurements;    gait parameters;   
DOI  :  10.3390/signals3020011
来源: DOAJ
【 摘 要 】

Due to impaired mobility caused by aging, it is very important to employ early detection and monitoring of gait parameters to prevent the inevitable huge amount of medical cost at a later age. For gait training and potential tele-monitoring application outside clinical settings, low-cost yet highly reliable gait analysis systems are needed. This research proposes using a single LiDAR system to perform automatic gait analysis with polynomial fitting. The experimental setup for this study consists of two different walking speeds, fast walk and normal walk, along a 5-m straight line. There were ten test subjects (mean age 28, SD 5.2) who voluntarily participated in the study. We performed polynomial fitting to estimate the step length from the heel projection cloud point laser data as the subject walks forwards and compared the values with the visual inspection method. The results showed that the visual inspection method is accurate up to 6 cm while the polynomial method achieves 8 cm in the worst case (fast walking). With the accuracy difference estimated to be at most 2 cm, the polynomial method provides reliability of heel location estimation as compared with the observational gait analysis. The proposed method in this study presents an improvement accuracy of 4% as opposed to the proposed dual-laser range sensor method that reported 57.87 cm ± 10.48, an error of 10%. Meanwhile, our proposed method reported ±0.0633 m, a 6% error for normal walking.

【 授权许可】

Unknown   

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