Low-Cost Multisensor Integrated System for Online Walking Gait Detection

From Hindawi via Jisc Publications RouterHistory: publication-year 2021, received 2021-04-21, rev-recd 2021-07-02, accepted 2021-07-25, pub-print 2021-08-14, archival-date 2021-08-14Publication status: PublishedA 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

Low-cost multisensor integrated system for online walking gait detection

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

Design and Evaluation of a Smooth-Locking-Based Customizable Prosthetic Knee Joint

Limb loss affects many people from a variety of backgrounds around the world. The most advanced commercially available prostheses for transfemoral amputees are fully active (powered) designs but remain very expensive and unavailable in the developing world. Consequently, improvements of low-cost, passive prostheses have been made to provide high-quality rehabilitation to amputees of any background. This study explores the design and evaluation of a smooth-locking-based bionic knee joint to replicate the swing phase of the human gait cycle. The two-part design was based on the condyle geometry of the interface between the femur and tibia obtained from magnetic resonance (MR) images of the human subject, while springs were used to replace the anterior and posterior cruciate ligaments. A flexible four-bar linkage mechanism was successfully achieved to provide not only rotation along a variable instantaneous axis but also slight translation in the sagittal plane, similar to the anatomical knee. We systematically evaluated the effects of different spring configurations in terms of stiffness, position, and relaxion length on knee flexion angles during walking. A good replication of the swing phase was achieved by relatively high stiffness and increased relaxation length of springs. The stance phase of the gait cycle was improved compared to some models but remained relatively flat, where further verification should be conducted. In addition, 3D printing technique provides a convenient design and manufacturing process, making the prosthesis customizable for different individuals based on subject-specific modeling of the amputee’s knee

Study on the factors affecting the mechanical properties and recovery force of PLA/PEEK blends

It has been found that PLA/PEEK blends have excellent mechanical properties and shape memory properties. In this article, the properties of PLA/PEEK blends were further studied. The mechanical properties of PLA/PEEK blends may be directly or indirectly affected by the molding temperature, molding method and heat treatment conditions. In this paper, PLA/PEEK blends were prepared under different processing conditions (molding temperature, molding method and heat treatment conditions) to evaluate the effects of different processing conditions on the mechanical properties of PLA/PEEK blends. In order to determine the lifting force of PLA/PEEK blends under different conditions, the effects of blends proportion and deformation temperature on the deformation force during the shape memory process were investigated. The experimental results show that the mechanical properties of PLA/PEEK blends can be improved by controlling the preparation conditions, and the deformation time and force can be effectively controlled by the proportion of the blends and recovery temperature

An Efficient Hybrid Algorithm for Multiobjective Optimization Problems with Upper and Lower Bounds in Engineering

Generally, the inconvenience of establishing the mathematical optimization models directly and the conflicts of preventing simultaneous optimization among several objectives lead to the difficulty of obtaining the optimal solution of a practical engineering problem with several objectives. So in this paper, a generate-first-choose-later method is proposed to solve the multiobjective engineering optimization problems, which can set the number of Pareto solutions and optimize repeatedly until the satisfactory results are obtained. Based on Frisch’s method, Newton method, and weighed sum method, an efficient hybrid algorithm for multiobjective optimization models with upper and lower bounds and inequality constraints has been proposed, which is especially suitable for the practical engineering problems based on surrogate models. The generate-first-choose-later method with this hybrid algorithm can calculate the Pareto optimal set, show the Pareto front, and provide multiple designs for multiobjective engineering problems fast and accurately. Numerical examples demonstrate the effectiveness and high efficiency of the hybrid algorithm. In order to prove that the generate-first-choose-later method is rapid and suitable for solving practical engineering problems, an optimization problem for crash box of vehicle has been handled well

Theoretical and Experimental Investigations into a Crawling Robot Propelled by Piezoelectric Material

Conventional motors with complicated electromagnetic structures are difficult to miniaturise for millimetre- and centimetre-sized robots. Instead, small-scale robots are actuated using a variety of functional materials. We proposed a novel robot propelled by a piezoelectric ceramic in this work. The robot advances due to the asymmetric friction created by the spikes on the surface. The structural modelling was completed, static and dynamic models were established to predict the moving characteristics, the prototype was built using three dimensional (3D) printing technology, and the models were evaluated via experiments. Compared with conventional inchworm-type robots, the proposed robot is superior in simple structure because the clamping components are replaced by spikes with asymmetric friction. Compared with SMA (shape memory alloy) actuating inchworm-type robots, it has a faster velocity with higher resolution. Meanwhile, the components are printed through an additive manufacturing process that is convenient and avoids assembly errors. This design could make contributions to many areas, such as pipe inspection, earthquake rescue, and medicine delivery

An Improved Extreme Learning Machine (ELM) Algorithm for Intent Recognition of Transfemoral Amputees With Powered Knee Prosthesis

To overcome the challenges posed by the complex structure and large parameter requirements of existing classification models, the authors propose an improved extreme learning machine (ELM) classifier for human locomotion intent recognition in this study, resulting in enhanced classification accuracy. The structure of the ELM algorithm is enhanced using the logistic regression (LR) algorithm, significantly reducing the number of hidden layer nodes. Hence, this algorithm can be adopted for real-time human locomotion intent recognition on portable devices with only 234 parameters to store. Additionally, a hybrid grey wolf optimization and slime mould algorithm (GWO-SMA) is proposed to optimize the hidden layer bias of the improved ELM classifier. Numerical results demonstrate that the proposed model successfully recognizes nine daily motion modes including low-, mid-, and fast-speed level ground walking, ramp ascent/descent, sit/stand, and stair ascent/descent. Specifically, it achieves 96.75% accuracy with 5-fold cross-validation while maintaining a real-time prediction time of only 2 ms. These promising findings highlight the potential of onboard real-time recognition of continuous locomotion modes based on our model for the high-level control of powered knee prostheses