Variations of pressure data from insoles in normal population during the 10meter walking test and an appropriate parameters’ extraction algorithm: a pilot study

D. Dimopoulos, Evangelos Kalogirou, D. Varvarousis, Vasilis Nakos, I. Manolis, Mohamed Hedi Boughariou, G. I. Vasileiadis, A. Ploumis
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Abstract

Our objective was to explore variations of pressure data from insole pressure sensors after a walking session and to produce an algorithm which extracts spatiotemporal gait parameters in close real time. In this study we performed a 10-meter stand up and walking test on 25 normal individuals. All subjects were walking at their comfortable speed during the test. The subjects were wearing in-soles equipped with 9 pressure sensors on each foot (the W-inshoe system by Medicapteurs). The W-inshoe system is simple, relatively cheap and reliable. System’s software is quite outdated, has multiple bugs and does not produce the appropriate numerical gait parameters, so we developed an algorithm to process the raw data from the insoles using MATLAB. The developed algorithm can successfully process the pressure data, remove noise, and produce the appropriate gait parameters accurately. Using the algorithm on our sampling pool, we procured the following results: Average peak pressure range was 644 to 1555 gram force (average: 1000gf, average stance period range was 0.64 to 0.85 seconds (average: 0. 76s) and double support period range was 0.17 to 22s (average: 0. 18s). Even though there were only 9 sensors in every insole, the data were sufficient to develop the algorithm. In the future, the algorithm could be used on a cloud-based application to extract pressure and spatiotemporal gait parameters from a simple and reliable insole system.
正常人10米步行测试中鞋垫压力数据的变化及合适的参数提取算法:一项试点研究
我们的目标是探索步行后鞋垫压力传感器压力数据的变化,并产生一种算法,该算法可以近实时地提取时空步态参数。在这项研究中,我们对25名正常人进行了10米站立和行走测试。在测试过程中,所有受试者都以自己舒适的速度行走。受试者穿着每只脚上装有9个压力传感器的内底(由Medicapteurs设计的W-inshoe系统)。W-inshoe系统简单,相对便宜且可靠。由于系统的软件比较落后,存在很多缺陷,不能产生合适的数值步态参数,因此我们利用MATLAB开发了一种算法来处理来自鞋垫的原始数据。该算法能够成功地对压力数据进行处理,去除噪声,并准确地生成合适的步态参数。在我们的采样池中使用该算法,我们得到了以下结果:平均峰值压力范围为644至1555克力(平均:1000gf),平均站立时间范围为0.64至0.85秒(平均:0。76秒),双支撑期范围为0.17至22秒(平均:0.76秒)。18岁)。尽管每个鞋垫只有9个传感器,但这些数据足以开发算法。未来,该算法可用于基于云的应用程序,从简单可靠的鞋垫系统中提取压力和时空步态参数。
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期刊介绍: Computer Engineering and Design is supervised by China Aerospace Science and Industry Corporation and sponsored by the 706th Institute of the Second Academy of China Aerospace Science and Industry Corporation. It was founded in 1980. The purpose of the journal is to disseminate new technologies and promote academic exchanges. Since its inception, it has adhered to the principle of combining depth and breadth, theory and application, and focused on reporting cutting-edge and hot computer technologies. The journal accepts academic papers with innovative and independent academic insights, including papers on fund projects, award-winning research papers, outstanding papers at academic conferences, doctoral and master's theses, etc.
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