Aiming at the problem of low recognition accuracy of motor imagery electroencephalogram signal due to individual differences of subjects, an individual adaptive feature representation method of motor imagery electroencephalogram signal is proposed in this paper. Firstly, based on the individual differences and signal characteristics in different frequency bands, an adaptive channel selection method based on expansive relevant features with label F (ReliefF) was proposed. By extracting five time-frequency domain observation features of each frequency band signal, ReliefF algorithm was employed to evaluate the effectiveness of the frequency band signal in each channel, and then the corresponding signal channel was selected for each frequency band. Secondly, a feature representation method of common space pattern (CSP) based on fast correlation-based filter (FCBF) was proposed (CSP-FCBF). The features of electroencephalogram signal were extracted by CSP, and the best feature sets were obtained by using FCBF to optimize the features, so as to realize the effective state representation of motor imagery electroencephalogram signal. Finally, support vector machine (SVM) was adopted as a classifier to realize identification. Experimental results show that the proposed method in this research can effectively represent the states of motor imagery electroencephalogram signal, with an average identification accuracy of (83.0±5.5)% for four types of states, which is 6.6% higher than the traditional CSP feature representation method. The research results obtained in the feature representation of motor imagery electroencephalogram signal lay the foundation for the realization of adaptive electroencephalogram signal decoding and its application.
ObjectiveTo evaluate the effectiveness of channel-assisted minimally invasive repair (CAMIR) for acute closed Achilles tendon ruptures. MethodsBetween January 2011 and June 2012, 30 patients (30 sides)with acute closed Achilles tendon ruptures were treated with CAMIR technique. Among 30 patients, 18 were male and 12 were female with an average age of 30.4 years (range, 22-50 years); the locations were left side in 10 cases and right side in 20 cases. All the causes were sports injury. B-ultrasound was used to confirm the diagnosis, with the average distance from the rupture site to the Achilles tendon insertion of 4.4 cm (range, 2-8 cm). The time from injury to operation was 3 hours to 9 days (median, 4 days). All injuries were repaired by CAMIR technique. ResultsThe average operation time was 17.0 minutes (range, 10-25 minutes), and the mean incision length was 2.0 cm (range, 1.5-2.5 cm). All the incisions healed by first intention. There was no complication of wound problem, deep vein thrombosis, re-rupture, or sural nerve injury. All cases were followed up 12-24 months with an average of 16 months. At last follow-up, the patients could walk normally with powerful raising heels and restored to normal activity level. MRI imaging suggested the continuity and healing of ruptured tendon. The circumference difference between affected leg and normal leg was less than 1 cm, and the ankle dorsi-extension was 20-30°, plantar flexion was 20-30°. Arner Lindholm score showed that the surgical results were excellent in 28 cases and good in 2 cases, with an excellent and good rate of 100%. ConclusionCAMIR is a safe and reliable method to repair acute closed Achilles tendon rupture, with many advantages of minimal injury, low re-rupture and infection. Sural nerve injury can be minimized using CAMIR by carefully placing the suture channel with a stab incision and special trocar based on a modified Bunnel suture technique.
The electroencephalogram (EEG) signal is the key signal carrier of the brain-computer interface (BCI) system. The EEG data collected by the whole-brain electrode arrangement is conducive to obtaining higher information representation. Personalized electrode layout, while ensuring the accuracy of EEG signal decoding, can also shorten the calibration time of BCI and has become an important research direction. This paper reviews the EEG signal channel selection methods in recent years, conducts a comparative analysis of the combined effects of different channel selection methods and different classification algorithms, obtains the commonly used channel combinations in motor imagery, P300 and other paradigms in BCI, and explains the application scenarios of the channel selection method in different paradigms are discussed, in order to provide stronger support for a more accurate and portable BCI system.