Lingling Chen

Study of the Control Mechanism of Robot-Prosthesis Based-on the EMG Processed

This paper proposes a new-type prosthesis model and control mechanism, represents an ongoing investigation of voluntary and natural control of lower limb prosthesis using the myoelectric signals. First of all, myoelectric signals, which are sampled from the lower limb during the subjects walked normally on the three kinds terrains, such as flat, slop and stair, are extracted the motion features with wavelet packet decomposition. And then these features are sent into LVQ neural network to classify. In the end sending the new signals into the network, the high identification ratio was obtained. The greatest characteristic of the robot-prosthesis is that it can be controlled at will, when the active control should offered corresponding parameter to the execution part for different terrain

Gait Optimization of Biped Robot Based on Mix-encoding Genetic Algorithm

A seven-link biped robot model with 12 rotational DOF was chosen for gait optimization. The vector describing robots position and pose was established, then the vectors expected locus during a regular step was modeled by the 5th order polynomials. The mathematic descriptions of geometry restriction, stabilization, energy dissipation, and impact to swaying leg from floor were analyzed respectively, and then the optimal gait was worked out with genetic algorithm mixing binary number encoding and floating point number encoding. Experimental results show that the optimal gait maximizes dynamic stabilization while it minimizes both energy dissipation and impact to swaying leg from floor.

Movement recognition by electromyography signal for transfemoral prosthesis control

The surface electromyography signal extracted from the stump was applied to recognize the movement, and be translated into on-off signal to fulfill the conversion from standing to walking. According to the different situation of stump, the signals extracted from different muscles were applied to control the prosthesis. Factor analysis was applied to find the relationship between different muscle groups, and to reduce the number of muscles. Hilbert-Huang transform was applied to extract the frequency features, and time and frequency features were applied to recognize the beginning of barycenter transfer movement. The result of this study indicates that this method can recognize the movement with a higher identification rate.

Path planning for tractor-trailer mobile robot system based on equivalent size

Tractor-trailer wheeled mobile robot is a complicated system, which is composed of a tractor and multiple trailers. As the path width changes with the different turning angles, as its path planning is complicated accordingly. On the base of presenting the kinematics equations of the tractor-trailer mobile robot, the maximum path width is deduced when the robot runs at the maximum turning angle. And this path width is named as equivalent size. Then genetic algorithmic is applied for the path planning method of tractor-trailer mobile robot. Firstly, the barriers are enlarged step by step with equivalent size. Then the vicinities around the barriers and the block neck zone are analyzed and labeled. The fitness function is defined according to both the path length and path width. Finally, the genetic algorithm is adopted to solve the whole path planning problem.

Fuzzy Support Vector Machine for EMG Pattern Recognition and Myoelectrical Prosthesis Control

For the optional control to the trans-femoral prosthesis and natural gait, an ongoing investigation of lower limb prosthesis model with myoelectrical control was presented. In this research, the surface electromyographic signals of lower limb were extracted to be switch signal, and translate into movement information. Considering every muscles different physiologic tendency, fuzzy support vector regression method was applied to establish an intelligent black box that can interpret the physiological signals to accurate information of knee joint angle. It achieves a comparable or better performance than other methods, and provides a more native gait to the prosthesis user.

A study on control mechanism of above knee robotic prosthesis based on CPG model

With the development of biomedicine and microcontroller technology, above knee prosthesis has been improved rapidly. However most current researches just focus on the single knee joint, and ignore the coupling between knee joint and ankle joint, which do not meet the needs of patients who need to perform multi-joint coordinated movement. This paper presents a new control method using bipedal robotics technology, bio-inspiration based on CPG net. According to this method, primary controller embedded in knee\ankle joint can receive the command from subject, recognize the movement mode, and send the start command to lower which realize the movement of above knee prosthesis. The previous findings show that sEMG can be employed to identify the movement mode based on SVM. And nonlinear oscillator, used for controlling multi-legged robot, can be employed to realize the lower limb movement. Further this paper explores the biodynamic effect of multi-joint, and tries to find the coupling rule and identify the MIMO neuromuscular model.

Electromyogram signal analysis and movement recognition based on wavelet packet transform

For recognizing the movement intent of amputee, surface electromyogram signals which can reflect movement intent and can be measured without invasion were applied to identify movement transition. Wavelet packet transform was applied to analyze the electromyogram signal, extract its frequency feature and recognize movement. The result of this study indicates that if the suitable coefficients were selected, the movement transition from standing to sitting and from sitting to standing can be recognized with a higher identification rate, and has a great potential in practical application of artificial lower limb.

The influence of walking speed on muscle activity of thigh and application in prostheses control

Changes in walking speed may eventually result in modifications of the patterning of muscle activity. The surface electromyography (EMG) signals provide easy and noninvasive access to physiological processes that cause the contraction of muscles. The influence of walking speed on muscle and EMG activity of amputees thigh was analyzed, the speed pattern recognition approach based on the combination of surface EMG signal and knee angle was applied to recognize the walking speed of amputee, and the walking speed control strategy of above knee prostheses was proposed. The result of experiment demonstrated that the phasing of muscle activity remained relatively stable over every walking speed despite substantial changes in EMGs amplitude. Adjusting the swing velocity of prosthesis knee can improve the performance of prosthesis and decrease the energy consumption. The outcome of this investigation could promote the future design of neural-controlled artificial legs.

Research on path planning method of multi mobile robot in dynamic environment

A path planning structure based on hierarchical idea was adopted in this paper. In this structure, the global path planning is done firstly by the robot and the local online adjusting is done afterward. This kind of structure can debase the calculation complexity of path planning. Then, aiming at the problem of local motion planning, a conflict-resolution strategy based on forecast was presented. It can decompose the restrictions of obstacle avoidance problem by establishing rules so as to debase the complexity of the problem. The reasoning process of this local path planning method is simple and practical. The experiments show that the robots can avoid the obstacles which are not only static ones but also moving ones accurately and effectively and the local path planning method is suitable to the conflict-resolution of multi mobile robots.

Artificial Lower Limb with Myoelectrical Control Based on Support Vector Machine

For the optional control to artificial lower limb and natural gait, an artificial limb model with myoelectrical control was presented, and the recognition method based on support vector machine was discussed. The electromyography signal after pretreating and wavelet packet analyzing was stored in company with the motion of lower limb. Then support vector machine was used to build a model and found the relationship between electromyography signal and motion of leg. Finally, continuous angles of knee joint were used to control artificial limb device. Simulation results show that electromyography signal and angles of knee joint have strong relationship, and this algorithm obtains preferable forecast result