• Low-Cost Multisensor Integrated System for Online Walking Gait Detection

      Academic Editor: Ruiz, Carlos; email: carlos.ruiz@unavarra.es; Yan, Lingyun; orcid: 0000-0002-9986-2182; email: lingyun.yan@manchester.ac.uk; Wei, Guowu; orcid: 0000-0003-2613-902X; email: g.wei@salford.ac.uk; Hu, Zheqi; email: zheqi.hu@manchester.ac.uk; Xiu, Haohua; email: xiuhh@jlu.edu.cn; Wei, Yuyang; email: yuyang.wei@manchester.ac.uk; Ren, Lei; orcid: 0000-0003-3222-2102; email: lei.ren@manchester.ac.uk (Hindawi, 2021-08-14)
      A three-dimensional motion capture system is a useful tool for analysing gait patterns during walking or exercising, and it is frequently applied in biomechanical studies. However, most of them are expensive. This study designs a low-cost gait detection system with high accuracy and reliability that is an alternative method/equipment in the gait detection field to the most widely used commercial system, the virtual user concept (Vicon) system. The proposed system integrates mass-produced low-cost sensors/chips in a compact size to collect kinematic data. Furthermore, an x86 mini personal computer (PC) running at 100 Hz classifies motion data in real-time. To guarantee gait detection accuracy, the embedded gait detection algorithm adopts a multilayer perceptron (MLP) model and a rule-based calibration filter to classify kinematic data into five distinct gait events: heel-strike, foot-flat, heel-off, toe-off, and initial-swing. To evaluate performance, volunteers are requested to walk on the treadmill at a regular walking speed of 4.2 km/h while kinematic data are recorded by a low-cost system and a Vicon system simultaneously. The gait detection accuracy and relative time error are estimated by comparing the classified gait events in the study with the Vicon system as a reference. The results show that the proposed system obtains a high accuracy of 99.66% with a smaller time error (32 ms), demonstrating that it performs similarly to the Vicon system in the gait detection field.