In order to improve the motion fluency and coordination of lower extremity exoskeleton robots and wearers, a pace recognition method of exoskeleton wearer is proposed base on inertial sensors. Firstly, the triaxial acceleration and triaxial angular velocity signals at the thigh and calf were collected by inertial sensors. Then the signal segment of 0.5 seconds before the current time was extracted by the time window method. And the Fourier transform coefficients in the frequency domain signal were used as eigenvalues. Then the support vector machine (SVM) and hidden Markov model (HMM) were combined as a classification model, which was trained and tested for pace recognition. Finally, the pace change rule and the human-machine interaction force were combined in this model and the current pace was predicted by the model. The experimental results showed that the pace intention of the lower extremity exoskeleton wearer could be effectively identified by the method proposed in this article. And the recognition rate of the seven pace patterns could reach 92.14%. It provides a new way for the smooth control of the exoskeleton.
ObjectiveTo explore the effectiveness difference between titanium elastic intramedullary nail internal fixation and bone plate internal fixation in the treatment of adult Galeazzi fracture.MethodsNinety-seven patients of Galeazzi fracture according with the selection criteria were divided into 2 groups by prospective cohort study, who were admitted between January 2012 and November 2015. In the patients, 59 were treated with open reduction and bone plate internal fixation (plate group), and 38 with titanium elastic intramedullary nail internal fixation (minimally invasive group). There was no significant difference in the gender, age, cause of injury, fracture site, type of fracture, and time from injury to operation between 2 groups (P>0.05). The operation time, intraoperative blood loss, fracture healing time, and complications were recorded and compared between 2 groups, and the forearm function was evaluated by Anderson score.ResultsAll the patients were followed up 12-23 months (mean, 17 months). The operation time, intraoperative blood loss, fracture healing time of minimally invasive group were significantly less than those in plate group (P<0.05). There were 1 case of fracture nonunion, 1 case of wound infection in plate group, and 1 case of nail tail slight infection in minimally invasive group, which were all cured after the corresponding treatment. The remaining patients had good fracture healing, and no vascular injury, internal fixation failure, deep infection, or other complications occurred. According to Anderson score at 12 months after operation, the forearm function results were excellent in 46 cases, good in 12 cases, and poor in 1 case, with an excellent and good rate of 98.3% in plate group; and the results were excellent in 26 cases, good in 11 cases, and poor in 1 case, with an excellent and good rate of 97.4% in minimally invasive group; showing no significant difference (χ2=0.10, P=0.75).ConclusionMinimally invasive fixation with titanium elastic nail has such advantages as small damage, quick recovery, no skin scarring, etc. As long as the correct indication is selected, minimally invasive titanium intramedullary nail internal fixation of Galeazzi fractures can also get good effectiveness.
Exoskeleton nursing robot is a typical human-machine co-drive system. To full play the subjective control and action orientation of human, it is necessary to comprehensively analyze exoskeleton wearer’s surface electromyography (EMG) in the process of moving patients, especially identifying the spatial distribution and internal relationship of the EMG information. Aiming at the location of electrodes and internal relation between EMG channels, the complex muscle system at the upper limb was abstracted as a muscle functional network. Firstly, the correlation characteristics were analyzed among EMG channels of the upper limb using the mutual information method, so that the muscle function network was established. Secondly, by calculating the characteristic index of network node, the features of muscle function network were analyzed for different movements. Finally, the node contraction method was applied to determine the key muscle group that reflected the intention of wearer’s movement, and the characteristics of muscle function network were analyzed in each stage of moving patients. Experimental results showed that the location of the myoelectric collection could be determined quickly and efficiently, and also various stages of the moving process could effectively be distinguished using the muscle functional network with the key muscle groups. This study provides new ideas and methods to decode the relationship between neural controls of upper limb and physical motion.