Qining Wang

Passive dynamic walking with flat feet and ankle compliance

This paper presents a bipedal locomotion model for passive dynamic walking with flat feet and compliant ankles. The two-dimensional seven-link model extends the simplest walking model with the addition of hip actuation, knee joints, flat feet and torsional springs based compliance on ankle joints, concerning heel-strike and toe-strike transitions, to achieve adaptive bipedal locomotion on level ground with controllable walking speed. We investigate the effects of foot geometric parameters and ankles stiffness on bipedal walking. The model achieves satisfactory walking results not only on even ground but also on uneven terrain with no active control and on different walking velocities. In addition, from the view of stability, there is an optimal foot-ankle ratio of the passivity-based walker. The results can be used to explore further understanding of bipedal walking, and help the design of future intelligent ankle-foot prosthesis and passivity-based robot prototypes towards more practical uses.

Step Length and Velocity Control of a Dynamic Bipedal Walking Robot With Adaptable Compliant Joints

Controlled passive walking is an approach that extends the passive walking by adapting the compliance of the joints. Natural motions can be chosen in order to obtain a controllable and energy-efficient walking motion. In this paper, actuators with online adaptable compliance are used based on the concept of controlled passive walking, to obtain adjustable step length and velocity during dynamic bipedal walking. We designed and constructed a bipedal walking robot Veronica which is actuated by the MACCEPA actuators, in which the compliance and equilibrium position can be controlled independently. In addition, a 2-D seven-link bipedal model for simulated walking of Veronica is built to analyze the relation between joint compliance and walking characteristics. Experimental results show that effective walking transitions between different walking speeds and step lengths are realized in both simulations and physical robot experiments.

Concept, Principle and Application of Dynamic Configuration for Intelligent Algorithms

Since genetic algorithm (GA) presented decades ago, large amount of intelligent algorithms and their improvements and mixtures have been putting forward one after another. However, little works have been done to extend their applications and verify their competence in different problems. For each specific complex problem, people always take a long time to find appropriate intelligent algorithm and develop improvements. To overcome these shortcomings, new dynamic configuration methods for intelligent algorithms (DC-IA) is presented in this paper on the basis of the requirements of three kinds of algorithm users. It separates the optimization problems and intelligent algorithms, modularizes each step of algorithms and extracts their core operators. Based on the coarse-grained operator modules, three-layer dynamical configurations, i.e., parameter-based configuration, operator-based configuration and algorithm-based configuration, are fully exploited and implemented. Under these methods, dozens of hybrid and improved intelligent algorithms can be easily produced in a few minutes just based on several configurable operator modules. Also, problem-oriented customizations in configurations can further extend the application range and advance the efficiency of the existing operators enormously. Experiments based on the established configuration platform verify the new configuration ways of applying and improving intelligent algorithm for both numerical and combinatorial optimization problems in industries on aspects of flexibility, robustness, and reusability.

Locomotion Mode Classification Using a Wearable Capacitive Sensing System

Locomotion mode classification is one of the most important aspects for the control of powered lower-limb prostheses. We propose a wearable capacitive sensing system for recognizing locomotion modes as an alternative solution to popular electromyography (EMG)-based systems, aiming to overcome drawbacks of the latter. Eight able-bodied subjects and five transtibial amputees were recruited for automatic classification of six common locomotion modes. The system measured ten channels of capacitance signals from the shank, the thigh, or both. With a phase-dependent linear discriminant analysis classifier and selected time-domain features, the system can achieve a satisfactory classification accuracy of 93.6% ±0.9% and 93.4% ±0.8% for able-bodied subjects and amputee subjects, respectively. The classification accuracy is comparable with that of EMG-based systems. More importantly, we verify that neuro-mechanical delay inherent in capacitive sensing does not affect the timeliness of classification decisions as the system, similar to EMG-based systems, can make multiple judgments during a gait cycle. Experimental results also indicate that capacitance signals from the thigh alone are sufficient for mode classification for both able-bodied and transtibial subjects. Our investigations demonstrate that capacitive sensing is a promising alternative to myoelectric sensing for real-time control of powered lower-limb prostheses.

Adaptive changes of foot pressure in hallux valgus patients.

BACKGROUND Hallux valgus (HV) is one of the most common deformities in podiatric and orthopedic practice. Plantar pressure technology has been widely used in studying the pressure distribution in HV patients for better assessment to plan interventions. However, previous studies produced an array of controversial findings and most of them only focused on the forefoot. METHODS We examined the dynamic changes of foot pressure of the whole foot with a large-sample investigation (229 patients and 35 controls). Foot pain, which has been largely neglected previously, was used to group the participants. RESULTS Compared to healthy controls, patients had significantly higher loading of the first and second metatarsals, where the transverse arch usually collapses, and significantly less loading of the hallux. Moreover, forces in most regions reached their maximum late, indicating a slow build-up of loading. Patients shortened the loading duration on their forefoot, loaded more on the medial foot starting from early foot contact, and delayed the medial-to-lateral load transition. Notably, nearly all these changes were more pronounced in patients with pain. CONCLUSIONS Biomechanical changes in HV patients are not only caused by physical deformity but also by modified neural control strategies, possibly to alleviate discomfort and to accommodate the foot deformity. Our results suggest that dynamic evaluation of the whole foot and consideration of foot pain are necessary for the functional assessment of foot pressure in HV patients. The foot balance changes have important clinical implications.

Fuzzy-Logic-Based Terrain Identification with Multisensor Fusion for Transtibial Amputees

Terrain identification is essential for the control of robotic transtibial prostheses to realize smooth locomotion transitions. In this paper, we present a real-time fuzzy-logic-based terrain identification method with multisensor fusion. Five locomotion features, including the foot inclination angle at the first strike, the shank inclination angle at the first strike, foot strike sequence, the foot inclination angle at mid-stance, and the shank inclination angle at toe-off, are used to identify different terrains and terrain transitions. These features are measured by the fusion of two triaxis gyroscopes, two triaxis accelerometers, two force sensitive resistors, and a timer, which can be embedded into the prosthesis. Based on these features, a fuzzy-logic-based identification method is proposed to identify five terrains: level ground, stair ascent, stair descent, ramp ascent, and ramp descent. Moreover, a transition constraint function is developed to improve the identification performance. The execution time of the identification method is 0.79 ms ± 0.02 ms (mean ± standard error of mean) and continuous terrain identification results show that the method can be operated online in real time. The average identification accuracy of 98.74% ± 0.32% is obtained from experiments with six able-bodied and three amputee subjects during steady locomotion periods (no terrain transition). In locomotion transition periods, all the eight transitions we studied are correctly identified and the average identification delay is 9.06% ± 3.46% of one gait cycle.

Serotonin affects movement gain control in the spinal cord

A fundamental challenge for the nervous system is to encode signals spanning many orders of magnitude with neurons of limited bandwidth. To meet this challenge, perceptual systems use gain control. However, whether the motor system uses an analogous mechanism is essentially unknown. Neuromodulators, such as serotonin, are prime candidates for gain control signals during force production. Serotonergic neurons project diffusely to motor pools, and, therefore, force production by one muscle should change the gain of others. Here we present behavioral and pharmaceutical evidence that serotonin modulates the input–output gain of motoneurons in humans. By selectively changing the efficacy of serotonin with drugs, we systematically modulated the amplitude of spinal reflexes. More importantly, force production in different limbs interacts systematically, as predicted by a spinal gain control mechanism. Psychophysics and pharmacology suggest that the motor system adopts gain control mechanisms, and serotonin is a primary driver for their implementation in force production.

PANTOE 1: Biomechanical design of powered ankle-foot prosthesis with compliant joints and segmented foot

This paper presents the design of a novel powered ankle-foot prosthesis with compliant ankle and segmented foot. The powered compliant ankle is proposed to replace the able-bodied ankle which can provide sufficient power to propel the body upward and forward during bipedal walking. In order to make the walking gaits of the amputees more stable and natural, we introduce segmented foot with toe joint to the prosthesis. The segmented foot decreases the torque of the ankle and makes the amputees effort-saving. Both the ankle and toe joints are driven by two series-elastic actuators (SEA), which not only provide enough torque, but also tolerance shocks. The sensory system of the prosthesis includes angle sensors, touch sensors and force sensors. The sensory system can detect and feed back the position and torque of the joints real-time. Preliminary experiments have been carried out to evaluate the safety and functionality of the proposed powered prosthesis. The experimental results show that the powered prosthesis with compliant ankle and segmented foot can reproduce the human walking gait and be easily used in walking rehabilitation.

A Noncontact Capacitive Sensing System for Recognizing Locomotion Modes of Transtibial Amputees

This paper presents a noncontact capacitive sensing system (C-Sens) for locomotion mode recognition of transtibial amputees. C-Sens detects changes in physical distance between the residual limb and the prosthesis. The sensing front ends are built into the prosthetic socket without contacting the skin. This novel signal source improves the usability of locomotion mode recognition systems based on electromyography (EMG) signals and systems based on capacitance signals obtained from skin contact. To evaluate the performance of C-Sens, we carried out experiments among six transtibial amputees with varying levels of amputation when they engaged in six common locomotive activities. The capacitance signals were consistent and stereotypical for different locomotion modes. Importantly, we were able to obtain sufficiently informative signals even for amputees with severe muscle atrophy (i.e., amputees lacking of quality EMG from shank muscles for mode classification). With phase-dependent quadratic classifier and selected feature set, the proposed system was capable of making continuous judgments about locomotion modes with an average accuracy of 96.3% and 94.8% for swing phase and stance phase, respectively (Experiment 1). Furthermore, the system was able to achieve satisfactory recognition performance after the subjects redonned the socket (Experiment 2). We also validated that C-Sens was robust to load bearing changes when amputees carried 5-kg weights during activities (Experiment 3). These results suggest that noncontact capacitive sensing is capable of circumventing practical problems of EMG systems without sacrificing performance and it is, thus, promising for automatic recognition of human motion intent for controlling powered prostheses.

A Wearable Plantar Pressure Measurement System: Design Specifications and First Experiments with an Amputee

In this paper, we present a wearable plantar pressure measurement system for locomotion mode recognition. The proposed system is implemented with four force sensors in each shoe to measure different given position pressure. By phase-dependent pattern recognition, we get reliable classification results of the six investigated modes for a below-knee amputee subject. The satisfactory recognition performances show the prospect of the integration of the proposed system with powered prostheses used for lower-limb amputees.