1.Clinicopathological analysis on goblet cell carcinoid of the appendix
Weiwei CHENG ; Junhong LI ; Huixing ZHOU ; Sujiao WEI
Cancer Research and Clinic 2014;26(10):679-682
Objective To explore the clinicopathologic features,diagnostic criteria and clinical prognostic factors of Goblet cell carcinoid (GCC) of the appendix.Methods The clinical and pathological data from 6 GCC patients were analyzed including age,clinical stage,surgical procedure,outcome,macroscopic features,histological sections and immunohistochemistry.Results The median age was 49.67 years old.Clinically,4 patients presented the signs and symptoms of acute appendicitis,while 2 patients presented the signs and symptoms of abdominal pain.4 patients of them undergone the simple appendectomy,the other 2 undergone the right hemicolectomy.All patients who had undergone the operation treatment survived.One patient was lost to the follow-up.Macroscopically,no masses were found in the appendix.Microscopically,4 cases showed that the tumor cells were identical to the goblet cell normal small intestinal crypts morphologically.The atypia,necrosis and mitotic figures of neoplasm cells were absent.2 cases were composed of small,discrete acini,tubules lined by a single layer of cuboidal or columnar cell,the signet-ring cells were uniform with pattern of infiltration being nests,rosrttes,or clumps without a dintinct lumen.All GCC cases were positive to Syn,4 cases were positive to CgA,some cases expressed NSE,CD56,CK7,CK20,Ki-67 index of 5 cases was under 2 %,the other 1 was 3 %.None had lymph node metastases,intestinal metastases or ovary metastases.Conclusions GCC of appendix is a rare neoplasm,and has more aggressive behaviour than classic carcinoids.Positive expression of Syn and CgA is necessory for the diagnosis of GCC,Ki-67 index may suggest the grading of tumor.
2.A qualitative study on the cognition of the first group of nurses to protect against instrument-related stress injury in the novel coronavirus pneumonia
Wenjun GUO ; Sujiao WANG ; Shuhong NI ; Yi LI
Chinese Journal of Practical Nursing 2021;37(5):380-384
Objective:To explore the protective cognition of the first batch of nurses against novel coronavirus pneumonia on apparatus-related stress injury, so as to provide reference for formulating and implementing relevant training and improving management measures.Methods:Using the phenomenological method of qualitative research, from January 20, 2020 to February 17, 2020, a half structured in-depth interview was conducted among the echelon nurses who completed the first batch of nurses against novel coronavirus pneumonia on apparatus-related stress injury. A total of 13 nurses in isolation wards were interviewed for the study.Results:Using the method of Colaizzi phenomenology to analyze the interview data, the related knowledge cognition was low, the identification of risk factors was limited, the risk assessment was not carried out, the treatment measures were not timely, the awareness of protection was lacking, the management training was not perfect, and the medical protection materials were not enough.Conclusion:The first batch of nurses to fight against novel coronavirus pneumonia had a low awareness of the prevention of medical device-related stress injury. Hospital managers should strengthen the training of related knowledge, improve management strategies, enhance the awareness of protection, and identify risk factors early, take preventive measures to ensure the safety and health of front-line medical staff in a timely manner.
3.Research progress on intelligent assessment system for upper limb function of stroke patients.
Sujiao LI ; Kun WU ; Qiaoling MENG ; Hongliu YU
Journal of Biomedical Engineering 2022;39(3):620-626
At present, the upper limb function of stroke patients is often assessed clinically using a scale method, but this method has problems such as time-consuming, poor consistency of assessment results, and high participation of rehabilitation physicians. To overcome the shortcomings of the scale method, intelligent upper limb function assessment systems combining sensors and machine learning algorithms have become one of the hot research topics in recent years. Firstly, the commonly used clinical upper limb functional assessment methods are analyzed and summarized. Then the researches on intelligent assessment systems in recent years are reviewed, focusing on the technologies used in the data acquisition and data processing parts of intelligent assessment systems and their advantages and disadvantages. Lastly, the current challenges and future development directions of intelligent assessment systems are discussed. This review is hoped to provide valuable reference information for researchers in related fields.
Algorithms
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Humans
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Physical Therapy Modalities
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Stroke/diagnosis*
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Stroke Rehabilitation
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Upper Extremity
4.Research progress on analysis methods in electroencephalography-electromyography synchronous coupling.
Sujiao LI ; Su LIU ; He LAN ; Hongliu YU
Journal of Biomedical Engineering 2019;36(2):334-337
The motor nervous system transmits motion control information through nervous oscillations, which causes the synchronous oscillatory activity of the corresponding muscle to reflect the motion response information and give the cerebral cortex feedback, so that it can sense the state of the limbs. This synchronous oscillatory activity can reflect connectivity information of electroencephalography-electromyography (EEG-EMG) functional coupling. The strength of the coupling is determined by various factors including the strength of muscle contraction, attention, motion intention etc. It is very significant to study motor functional evaluation and control methods to analyze the changes of EEG-EMG synchronous coupling caused by different factors. This article mainly introduces and compares coherence and Granger causality of linear methods, the mutual information and transfer entropy of nonlinear methods in EEG-EMG synchronous coupling, and summarizes the application of each method, so that researchers in related fields can understand the current research progress on analysis methods of EEG-EMG synchronous systematically.
Electroencephalography
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Electromyography
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Humans
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Motor Cortex
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physiology
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Muscle, Skeletal
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physiology
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Research
5.Assessment of Postoperative Surface Electromyography and Joint Angle in Children with Spastic Cerebral Palsy
Yuanmin TANG ; Xueqin LUO ; Jiming SUN ; Hongliu YU ; Qingyun MENG ; Sujiao LI
Journal of Medical Biomechanics 2022;37(4):E726-E732
Objective To analyze and assess the postoperative motor function in children with spastic cerebral palsy (SCP) by surface electromyography (sEMG) and joint angle. Methods Sixteen children with SCP were involved in this study. The sEMG of rectus femoris, biceps femoris, semitendinosus, tibialis anterior, lateral gastrocnemius and medial gastrocnemius muscles and joint angles of the hip, knee and ankle during straight walking were collected preoperatively and postoperatively. In every gait phase, the mean values of joint angles, root mean square and integrated electromyography of sEMG were calculated, to evaluate muscle strength and muscular tension quantitatively. Results The muscle tension of lower limbs was significantly decreased (P<0.05). The muscle strength of rectus femoris and biceps femoris was decreased in the swing phase. At the midswing and terminal swing phase, the strength of tibialis anterior increased significantly (P<0.05). The flexion angle of hip and knee decreased significantly (P<0.05). The dorsiflexion angle of ankle increased significantly (P<0.05), and the varus angle decreased significantly (P<0.05). Conclusions After operation, the crouching gait and clubfoot were improved positively. Therefore, the motor function of children was improved. Combining sEMG and joint angle can evaluate the muscle function of patients quantitatively, and it also can provide references for clinical diagnosis.
6.Continuous Motion Estimation of Elbow Joint Based on Multi-Modal Information Fusion
Sujiao LI ; Yue ZHU ; Kun WU ; Chunyu ZHU ; Hongliu YU
Journal of Medical Biomechanics 2023;38(2):E324-E330
Objective Aiming at the problems of lacking initiative in upper limb rehabilitation training equipment, single training mode, and low active participation of patients, an upper limb continuous motion estimation algorithm model based on multi-modal information fusion was proposed, so to realize accurate estimation of elbow joint torque. Methods Firstly, the surface electromyography (sEMG) signal and posture signal of participants were collected at four angular velocities, and the time domain characteristics of the signal were extracted. The principal component analysis was adopted to multi-feature fusion. The back propagation neural network (BPNN) was optimized through the additional momentum and the adaptive learning rate method. The particle swarm optimization (PSO) algorithm was used to optimize the neural network and a continuous motion estimation model based on PSO-BPNN was constructed. Finally, the joint torque calculated by the second type of Lagrangian equation was used as the accurate value to train the model. The performance of the model was compared with the traditional BP neural network model. Results The root mean square error (RMSE) of the traditional BP neural network model was 558.9 N·m, and the R2 coefficient was 77.19%, Whereas the RMSE and the R2 coefficient of the optimized model were 113.6 mN·m and 99.12%, respectively.Thereby, the accuracy of torque estimation was improved apparently. Conclusions The method for continuous motion estimation of the elbow joint proposed in this study can estimate the motion intention accurately, and provide a practical scheme for the active control of upper exoskeleton rehabilitation robot.
7.Study on the center-driven multiple degrees of freedom upper limb rehabilitation training robot.
Xiaohai HUANG ; Hongliu YU ; Jinchao WANG ; Qi DONG ; Linling ZHANG ; Qiaoling MENG ; Sujiao LI ; Duojin WANG
Journal of Biomedical Engineering 2018;35(3):452-459
With the aging of the society, the number of stroke patients has been increasing year by year. Compared with the traditional rehabilitation therapy, the application of upper limb rehabilitation robot has higher efficiency and better rehabilitation effect, and has become an important development direction in the field of rehabilitation. In view of the current development status and the deficiency of upper limb rehabilitation robot system, combined with the development trend of all kinds of products of the upper limb rehabilitation robot, this paper designed a center-driven upper limb rehabilitation training robot for cable transmission which can help the patients complete 6 degrees of freedom (3 are driven, 3 are underactuated) training. Combined the structure of robot with more joints rehabilitation training, the paper choosed a cubic polynomial trajectory planning method in the joint space planning to design two trajectories of eating and lifting arm. According to the trajectory equation, the movement trajectory of each joint of the robot was drawn in MATLAB. It laid a foundation for scientific and effective rehabilitation training. Finally, the experimental prototype is built, and the mechanical structure and design trajectories are verified.