Objective To assess the long-time results of reconstruction of the extensor pollicis longus (EPL) function by transfer of the extensorindicis(EI). Methods From August 1978 to March 2003, 46 cases of loss of the EPL function were treatedby transfer of the extensor indicis. Of 46 cases, there were 32 males and 14 females, aged 16-51 years with an average of 36 years; there were 24 cases of oldtraumatic rupture and 22 cases of secondary rupture. The disease course was 2 days to 5 months, averaged 74 days. A specific EIEPL evaluation method (SEEM) wasused to measure the EPL function after transfer.Results Fortyone cases were followed up 9 years and 3 months on average (7 months to 23 years). Based on the SEEM, the results were excellent and good in 39 of 41 patients. The elevation deficit and combined flexion deficit were 0-2.2 cm (1.8 cm on average) and 0-3 cm (1.6 cm on average); the independent extension deficit was 0°-8° (5° on average). Conclusion Restoration of the extensor pollicis function by transfer of the extensor indicis is an effective and safe treatment option and the SEEM is a valid method for assessing EPL function.
OBJECTIVE To investigate the therapeutical effect of treatment of ischemic necrosis of femoral head by the transfer of vascular pedicled iliac periosteum. METHODS From June 1983 to August 1997, 106 cases with ischemic necrosis of femoral head (II stage in 64 cases, III stage in 39 cases, IV stage in 3 cases) were treated by the transfer of vascular pedicled iliac periosteum with ascending branch of lateral femoral circumflex vessel or deep circumflex iliac vessel pedicle. RESULTS Followed up 2 years and 4 months to 16 years, there were excellent in 54 cases, better in 38 cases, moderate in 9 cases, poor in 5 cases, and 86.8% in excellent rate according to the criterion of the therapeutical effect on the repair and reconstruction of adult ischemic necrosis of femoral head. CONCLUSION Treating ischemic necrosis of femoral head by the transfer of vascular pedicled iliac periosteum has the advantage of constant pedicle, easily drawing materials and reliable therapeutical effect.
Greater omentum was chosen to treat chronic osteomyelitis in 12 cases. The involved bones included cranium in 5, tibia and fibula in 4 and metatarsus in 3. After thorough debridement, all patients had partial defects of bone, skin and soft tissue. The defect was filled with vascularized autogenous greater omentum by anastomosing with the host vessels. Theskin defect was covered with medium-thickness skin graft. After 3～9 years follw-up, no recurrence of osteomyelitis and no abdominal symptoms were observed in 11 cases. The osteomyelitis recurred in 1 case at 4 months after operation and died of squamous carcinoma 1 year later. It was suggested that transfer of vascularizedautogenous greater omentum was valuable in treating chronic osteomyelitis.
Objective To study the method and effect of transferring the pedicled second metatarsal base for repairing bone defect of lateral malleolus. Methods Thirty lower limb specimens were anatomized to observe the morphology, structure and blood supply of the second metatarsal bone . Then transferring of thepedicled second metatarsal base was designed and used in 6 patients clinically.All cases were male, aged from 24 to 48 years old, and the area of bone defect was 3-4 cm. Results Followed up for 3-11 months, all patients healed primarily both in donor and recipient sites. There were excellent results in 4 cases and good results in 2 cases . The morphology and function of the malleoli were satisfactory. Conclusion Transferring of the pedicled second metatarsal base for repairing bone defect of lateral malleolus is an effective and reliable operative method.
The existing automatic sleep staging algorithms have the problems of too many model parameters and long training time, which in turn results in poor sleep staging efficiency. Using a single channel electroencephalogram (EEG) signal, this paper proposed an automatic sleep staging algorithm for stochastic depth residual networks based on transfer learning (TL-SDResNet). Firstly, a total of 30 single-channel (Fpz-Cz) EEG signals from 16 individuals were selected, and after preserving the effective sleep segments, the raw EEG signals were pre-processed using Butterworth filter and continuous wavelet transform to obtain two-dimensional images containing its time-frequency joint features as the input data for the staging model. Then, a ResNet50 pre-trained model trained on a publicly available dataset, the sleep database extension stored in European data format (Sleep-EDFx) was constructed, using a stochastic depth strategy and modifying the output layer to optimize the model structure. Finally, transfer learning was applied to the human sleep process throughout the night. The algorithm in this paper achieved a model staging accuracy of 87.95% after conducting several experiments. Experiments show that TL-SDResNet50 can accomplish fast training of a small amount of EEG data, and the overall effect is better than other staging algorithms and classical algorithms in recent years, which has certain practical value.
Methodological quality and transferability will be important issues for the credibility and usefulness of both published studies and administrative methods for evaluating the socio-economic value of marketed medicines in China. This paper critically examines factors commonly contributing to, or inhibiting, the quality and transferability of socio-economic evidence of the value of medicines, with specific reference to the Chinese community. It discusses appropriate approaches to design, performance, and reporting of published economic evaluation studies, as well as guides on assessment of quality of economic evaluations and recommends two internationally established methods that may be suitable for training in this setting.
In recent years, epileptic seizure detection based on electroencephalogram (EEG) has attracted the widespread attention of the academic. However, it is difficult to collect data from epileptic seizure, and it is easy to cause over fitting phenomenon under the condition of few training data. In order to solve this problem, this paper took the CHB-MIT epilepsy EEG dataset from Boston Children's Hospital as the research object, and applied wavelet transform for data augmentation by setting different wavelet transform scale factors. In addition, by combining deep learning, ensemble learning, transfer learning and other methods, an epilepsy detection method with high accuracy for specific epilepsy patients was proposed under the condition of insufficient learning samples. In test, the wavelet transform scale factors 2, 4 and 8 were set for experimental comparison and verification. When the wavelet scale factor was 8, the average accuracy, average sensitivity and average specificity was 95.47%, 93.89% and 96.48%, respectively. Through comparative experiments with recent relevant literatures, the advantages of the proposed method were verified. Our results might provide reference for the clinical application of epilepsy detection.
This paper proposes a motor imagery recognition algorithm based on feature fusion and transfer adaptive boosting (TrAdaboost) to address the issue of low accuracy in motor imagery (MI) recognition across subjects, thereby increasing the reliability of MI-based brain-computer interfaces (BCI) for cross-individual use. Using the autoregressive model, power spectral density and discrete wavelet transform, time-frequency domain features of MI can be obtained, while the filter bank common spatial pattern is used to extract spatial domain features, and multi-scale dispersion entropy is employed to extract nonlinear features. The IV-2a dataset from the 4th International BCI Competition was used for the binary classification task, with the pattern recognition model constructed by combining the improved TrAdaboost integrated learning algorithm with support vector machine (SVM), k nearest neighbor (KNN), and mind evolutionary algorithm-based back propagation (MEA-BP) neural network. The results show that the SVM-based TrAdaboost integrated learning algorithm has the best performance when 30% of the target domain instance data is migrated, with an average classification accuracy of 86.17%, a Kappa value of 0.723 3, and an AUC value of 0.849 8. These results suggest that the algorithm can be used to recognize MI signals across individuals, providing a new way to improve the generalization capability of BCI recognition models.
Objective To introduce the clinical experience of localdistally based turnover adipofascial flap for small to medium size wound of the extremities. Methods From 1994 to 2003, 33 cases of distally based longitudinal neuro-veno-adipofascial turnover adipofascial flap (axial perforator pattern in26, random pattern in 7) were transferred in the forearm (19) and lower leg (14).These flaps were all raised in the forearm or lower leg as local flaps. The length (pedicle plus flap) was 9 to 18 cm and the width was 3 to 4 cm, with L/W ratio of 3 to 5∶1. After transferring by 180° turnover, a splitthickness skin graft was used tocover the fascia surface. Results All the 33 flaps survived. The donor sites were closed directly, and the recipient sites were covered with full-or splitthickness skin grafts. Both donor and recipient sites healed primarily. Conclusion Turnover adipofascial flap is a simple and reliable method for small to medium size wound of the extremities.
OBJECTIVE: To evaluate the clinical application of primary transfer of pectoralis major to reconstruct the elbow flexion and shoulder abduction. METHODS: 12 cases of old injury of branchial plexus with dysfunction of both elbow and shoulder joints were received surgical operation to reconstruct the palsy joints by primary transfer of pectoralis major, shoulder abduction was reconstructed by clavicular head and elbow flexion by sternal head respectively. All cases were followed up for 5 to 18 months. RESULTS: The function of both joints recovered obviously, the total superior rate is 91.7%. CONCLUSION: Only if the palsy joints, shoulder or elbow, remained normal or almost normal passive motion, and the muscle power of pectoralis major over 4 degrees, the primary transfer of pectoralis major should be a simple, reliable and convenient technique to reconstruct the palsy joints.