神经信号控制假肢研究

在开发研制高效多自由度上肢假肢中，信息源的合理选择对提高控制性能有着重要的影响。神经内传导的冲动能够充分反映患者的意志，信号清晰度高、重复再现性强、不易疲劳，是一种理想的控制信息源。通过首例残肢者纵行神经束内微电极检测周围神经信号的实验研究，以及受试者神经信号驱动7自由度假肢模拟装置的现场试验，探讨采用三大主神经（尺神经、桡神经和正中神经）的神经束内的募集自主运动信号控制上肢假肢的有关问题。     

上肢假肢控制模式的信息源研究

合理选择上肢假肢的控制信息源是发展高效能多自由度上肢假肢的前提，本文综述了当前各种上肢假肢控制所采用的信息源模式，对现有的各种控制信息源模式的特性和存在问题作了系统探讨。     

神经信号经皮传输的电路设计与仿真实验

本研究旨在实现利用神经动作电信号控制多自由度假肢。针对植入的神经信号电极,研究了神经信号的放大。为了使植入电极测得的神经信号能无线地传至体外,作者借助E类功率放大器的输出功率受负载电阻影响的特点,通过时分复用技术实现了多路神经信号的经皮传输与识别。文中叙述的植入体内的放大电路、经皮发射电路均是通过体外E类功率放大器发射的射频磁场经感应线圈而获得工作电源。最后用本研究研制的电路模拟神经信号控制多自由度假肢,验证了神经信号的放大、经皮传输、识别控制的过程。     

基于FMG信号的假手比例控制系统研究

假手控制方法的研究一直是假肢研究技术的一个热点问题。针对现有皮肤表面电信号作为控制源的假手存在的问题,本系统采用前臂上肢肌肉膨胀收缩产生的压力信号作为控制信息源,设计了基于肌肉力(FMG)信号的假手控制系统,包括信号采集调理、微控制器控制、电机驱动等部分。通过采集残臂端两路FMG信号,提取信号的时域信息并采用阈值算法实现了手部2个自由5个动作。根据FMG信号均值的大小,改变假手驱动电路中PWM的占空比,从而实现电动假手速度的比例调节。实验结果表明本控制系统能够有效控制假手执行动作,实现速度的调节。另外,利用LabVIEW搭建了FMG信号采集标定平台,实现了FMG信号的实时数据采集和标定。     

表面肌电信号的分析与应用

表面肌电信号的检测是一种无创电检测方法 ,它的检测分析对临床诊断及康复医学、运动医学等具有重要意义。本文介绍了表面肌电的信号分析方法 (时域分析法、频域分析法、时频分析法及人工神经网络等方法 ) ,并介绍了表面肌电信号检测分析技术的应用状况和前景展望     

动力型智能假肢膝关节的研究进展

当前和今后一个时期,残疾人对动力型智能假肢膝关节的需求日益迫切。为厘清国内外对动力型智能假肢膝关节的研究进展,本文主要从假肢膝关节的仿生结构和驱动结构设计、控制机制和算法,以及对复杂非结构环境下运动意图识别等方面的研究现状和主要成果进行了归纳总结,并提出动力型智能假肢膝关节在当前研究中面临的问题和挑战,展望了未来的发展方向。     

基于肌动图与肌电图信号的假肢控制系统的研究

目的验证使用肌动图（mechanomyography,MMG）和肌电图（electromyography,EMG）两种信号共同作为假肢控制信号时,是否能提高假肢控制系统分类的准确度。方法本文采用信号融合方法,通过融合6通道的MMG信号与2通道的EMG信号,以及基于模式识别的线性判别分析（linear discriminant analysis,LDA）算法,研制了基于MMG和EMG信号的假肢控制系统。结果该系统能对采集到的信号进行处理并得出动作分类结果,然后控制假肢完成相应动作。对6位测试者的腕屈、腕伸、张开、握拳4类动作以及静止状态进行假肢控制的动作分类准确度实验,准确度达94．6％,比单独用MMG信号的精度88．5％或EMG信号精度90．4％效果更好。结论基于MMG与EMG信号的假肢控制系统可以更好地实现假肢控制动作的有效分类,未来可应用于上臂截肢的残疾人。     

上臂肌电假肢驱电路

作者介绍肌电控制上臂假肢的工作原理和肌电信号的分析处理。提出一种抗干扰力强、稳定可靠、功耗低、结构紧凑的实用电路。实践表明该电路工作稳定，性能良好。     

主动型仿生踝关节假肢的设计

背景:与髋、膝关节假肢设计相对比较成熟的技术相比,踝关节作为人体下肢关节的重要组成部分,也是最为灵活的部分,一直以来研究都比较滞后,相关的假肢踝关节产品未能很好的满足假肢患者的需求.目的:从生物力学、解剖学和生理学角度出发,设计和研制出能在矢状面内做屈伸运动的主动型仿生踝关节假肢装置.方法:根据仿生学原理和人体踝关节在...     

上臂肌电假肢驱动电路

作者介绍肌电控制上臂假肢的工作原理和肌电信号的分析与处理。提出一种抗干扰力强、稳定可靠、功耗低、结构紧凑的实用电路。实践表明该电路工作稳定，性能良好。     

Control of neural prostheses for grasping and reaching

In recent years several neural prostheses have been developed and tested as orthoses or as therapeutic systems for hemiplegic and tetraplegic subjects aiming to improve the upper extremities function. The use of neural prostheses demonstrated that the targeted group of subjects could significantly benefit from functional electrical stimulation that is integrated in goal directed movements. In this paper the control for neural prostheses is explained using available systems that apply either surface or implantable interfaces to sensory-motor systems. Further more, a new strategy that has been tested for control of reaching and grasping within a neural prosthesis especially designed for neurorehabilitation is described. This, so-called, coordination strategy was based on mimicking the output space model of natural control determined in reach/grasp/release movements of healthy humans.     

An exploratory study to design a novel hand movement identification system

Electromyogram signal (EMG) is an electrical manifestation of contractions of muscles. Surface EMG (sEMG) signal collected from the surface of skin has been used in diverse applications. One of its usages is in pattern recognition of hand prosthesis movements. The ability of current prosthesis devices has been generally limited to simple opening and closing tasks, minimizing their efficacy compared to natural hand capabilities. In order to extend the abilities and accuracy of prosthesis arm movements and performance, a novel sEMG pattern recognizing system is proposed. To extract more pertinent information we extracted sEMGs for selected hand movements. These features constitute our main knowledge of the signal for different hand movements. In this study, we investigated time domain, time-frequency domain and combination of these as a compound representation of sEMG signal's features to access required signal information. In order to implement pattern recognition of sEMG signals for various hand movements, two intelligent classifiers, namely artificial neural network (ANN) and fuzzy inference system (FIS), were utilized. The results indicate that our approach of using compound features with principle component analysis (PCA) as dimensionality reduction technique, and FIS as the classifier, provides the best performance for sEMG pattern recognition system.     

Review of visual prosthesis (I)--retinal prosthesis

Research on how to totally or partially restore the vision has attracted more attention in the fields of neural engineering and tissue engineering. Neural interface and visual prosthesis offer alternative ways for partially repairing the visual impairment. The most widely used visual prosthetics are based on retinal stimulation. This article is a state-of-art review of the principles, technical details and the limitations of retinal prosthesis.     

三维打印技术在骨组织工程领域的应用研究进展

综述了三维(3D)打印技术的出现、分类与优势等.介绍了该技术在骨组织工程领域的应用,包括光固化立体印刷、熔融沉积成型、选择性激光烧结和3D喷印的工作原理、存在的优缺点以及国内外学者在该领域的研究进展.目前骨组织工程支架的制备大多应用了3D打印技术,以生物可降解的活性材料为原料制备而成.在我国该领域虽然发展迅速,利用3D打印技术进行人工骨合成、骨科术前模拟等已经越来越普遍,亦取得了令人满意的效果,但要研发出合适的生物材料以及设备精度的改进仍是亟待解决的问题.目前,仿生器官的功能化已成为3D打印技术领域的一大困难,其中多细胞共培养、血管化及支架的制备是实现功能化必须克服的问题,相信通过努力,该项技术将会为器官的再生与修复带来更多令人瞩目的成果.     

A Miniaturized System for Neural Signal Acquiring and Processing

To collect neural activity data from awake, behaving freely animals, we develop miniaturized implantable recording system by the modern chip:Programmable System on Chip(PSoC) and through chronic electrodes in the cortex. With PSoC family member CY8C29466,the system completed operational and instrument amplifiers, filters, timers, AD convertors, and serial communication, etc. The signal processing was dealt with virtual instrument technology. All of these factors can significantly affect the price and development cycle of the project. The result showed that the system was able to record and analyze neural extrocellular discharge generated by neurons continuously for a week or more. This is very useful for the interdisciplinary research of neuroscience and information engineering technique.The circuits and architecture of the devices can be adapted for neurobiology and research with other small animals.     

The evolution of clinical applications of biodegradable implants in arthroscopic surgery

Arthroscopic surgery is the most recent orthopaedic discipline to embrace biodegradable implant technology. Osteochondral fractures have been shown to be amenable to arthroscopic fixation with biodegradable pins. The areas of most recent interest have been biodegradable interference screw fixation for ACL reconstruction in the knee, biodegradable suture anchors for rotator cuff repair and capsulolabral repair in the shoulder. Biodegradable implants have allowed a paradigm shift away from bionic (mechanical replacement) engineering and toward true biologic solutions to reconstructive problems in arthroscopic surgery.     

神经束内微电极提取大鼠坐骨神经信号的实验研究

基于已设计完成的植入式筛型微电极和神经信号调理电路,组成一个完整的系统,用于提取大鼠坐骨神经信号,以探索获取周围神经信息的方法.用显微外科技术将微电极植入于大鼠坐骨神经束中,通过微电极传导出神经束电信号,经信号调理电路处理后记录.已成功稳定导出的电信号波形经分析具有神经动作电位特征,验证了神经束内微电极可以获取大鼠坐骨神经信号.