本文選題：運(yùn)動(dòng)控制 + 虛擬手臂模型　； 參考：《上海交通大學(xué)》2015年博士論文

【摘要】：研究生理和病理運(yùn)動(dòng)控制,是我們認(rèn)識(shí)感覺運(yùn)動(dòng)系統(tǒng),尤其是大腦脊髓中樞神經(jīng)系統(tǒng)的結(jié)構(gòu)和生理功能的重要內(nèi)容,也是為運(yùn)動(dòng)功能障礙患者提供運(yùn)動(dòng)功能補(bǔ)償和康復(fù)的基礎(chǔ)。神經(jīng)運(yùn)動(dòng)控制的研究方法分實(shí)驗(yàn)觀測(cè)分析與計(jì)算模型仿真兩種:實(shí)驗(yàn)研究對(duì)感覺運(yùn)動(dòng)系統(tǒng)中各層次回路的辨識(shí)和行為功能認(rèn)識(shí),是建立計(jì)算模型的基礎(chǔ);而計(jì)算模型仿真結(jié)果,又可以提供在實(shí)驗(yàn)條件下無法觀測(cè)的系統(tǒng)狀態(tài)的神經(jīng)信息。因此,實(shí)驗(yàn)分析和模型仿真方法在認(rèn)識(shí)中樞神經(jīng)系統(tǒng)感知運(yùn)動(dòng)功能中起到互補(bǔ)的作用。本論文探討的科學(xué)問題是,在姿態(tài)和運(yùn)動(dòng)雙重控制的理論框架下,大腦和脊髓中各神經(jīng)回路在整合感覺信息、控制運(yùn)動(dòng)執(zhí)行過程中的模塊化功能。本論文的工作突破了現(xiàn)階段研究方法的瓶頸,將感覺運(yùn)動(dòng)系統(tǒng)各子系統(tǒng)部分的大量數(shù)據(jù)和已知信息整合成為多尺度計(jì)算模型,從系統(tǒng)層面研究生理和病理運(yùn)動(dòng)的神經(jīng)控制機(jī)制。本論文在前期工作的基礎(chǔ)上,完善了多尺度虛擬手臂模型的仿真平臺(tái),并驗(yàn)證了虛擬手臂模型的真實(shí)性和有效性;利用虛擬手臂模型,分析并提出了肌梭伽馬神經(jīng)支配的中樞非線性編碼假設(shè);搭建人體上肢運(yùn)動(dòng)實(shí)驗(yàn)采集分析平臺(tái),并分析了帕金森病肢體震顫中,肌群的協(xié)同發(fā)放與震顫幅度的相關(guān)關(guān)系,為使用虛擬手臂模型進(jìn)一步探索帕金森病震顫的神經(jīng)病理機(jī)制提供了實(shí)驗(yàn)數(shù)據(jù)。本論文的主要研究?jī)?nèi)容和成果包括以下四個(gè)方面:1.在前期工作基礎(chǔ)上開發(fā)多尺度整合的虛擬手臂模型。我們將前期工作中開發(fā)的上肢肌骨系統(tǒng)生物力學(xué)模型、虛擬肌肉、肌梭、高爾基腱器官等模塊,和新增的脊髓反射回路和脊髓固有神經(jīng)元網(wǎng)絡(luò)模型模塊整合起來,移植到SIMULINK建模仿真平臺(tái)中,優(yōu)化參數(shù),統(tǒng)一接口,整合為一個(gè)具有真實(shí)生理特征的虛擬手臂系統(tǒng)模型。我們采用了模塊化的模型結(jié)構(gòu),使其具有模塊易于更新替換,拓展性強(qiáng),可根據(jù)需要定制化和個(gè)性化等特點(diǎn)。該模型在模擬正常和病理神經(jīng)運(yùn)動(dòng)行為,研究神經(jīng)運(yùn)動(dòng)控制機(jī)制中有巨大潛力,并為康復(fù)應(yīng)用的開發(fā)和臨床前評(píng)估提供了一個(gè)可靠且高效的仿真平臺(tái)和環(huán)境。2.驗(yàn)證虛擬手臂模型神經(jīng)力學(xué)行為的真實(shí)性和有效性,定量評(píng)估前饋和反饋控制對(duì)維持上肢端點(diǎn)姿態(tài)穩(wěn)定性的貢獻(xiàn)。手剛度反映了手的阻抗特性,手的運(yùn)動(dòng)變異性描述了固有神經(jīng)噪聲影響下的手的穩(wěn)定范圍,這兩個(gè)神經(jīng)力學(xué)行為指標(biāo)可以定量評(píng)價(jià)姿態(tài)控制下的手穩(wěn)定性。將系統(tǒng)模型仿真的神經(jīng)力學(xué)行為(手剛度與變異性)與人體實(shí)驗(yàn)測(cè)量數(shù)據(jù)比較,確認(rèn)虛擬手臂模型的真實(shí)性和有效性。由于實(shí)驗(yàn)測(cè)量手段的局限性,現(xiàn)階段我們還無法在系統(tǒng)層面準(zhǔn)確測(cè)量脊髓反射回路對(duì)上肢端點(diǎn)的姿態(tài)穩(wěn)定性的貢獻(xiàn),因而在不同的運(yùn)動(dòng)控制理論中,對(duì)本體感覺反饋在運(yùn)動(dòng)控制中的作用有不同解釋。虛擬手臂模型使我們可以通過設(shè)計(jì)開環(huán)和閉環(huán)條件下的仿真實(shí)驗(yàn),定量評(píng)估多關(guān)節(jié)系統(tǒng)中,閉環(huán)感覺反饋對(duì)系統(tǒng)阻抗特性和穩(wěn)定性的影響。結(jié)果表明,在穩(wěn)態(tài)的閉環(huán)感覺反饋?zhàn)饔孟?手剛度橢圓的面積增大35.75±16.99%(均值±標(biāo)準(zhǔn)差,下同),手變異性橢圓的面積縮小49.41±21.19%,顯示出本體感覺反饋在脊髓層面的閉環(huán)姿態(tài)控制中,對(duì)抗內(nèi)部神經(jīng)噪聲和外界環(huán)境擾動(dòng),維持多關(guān)節(jié)肢體穩(wěn)定性的顯著貢獻(xiàn)。3.研究肌梭運(yùn)動(dòng)神經(jīng)控制中可能的關(guān)節(jié)角度編碼模式,及其對(duì)外周本體感覺傳入中關(guān)節(jié)角度編碼的影響。實(shí)驗(yàn)證據(jù)表明下行的肌梭運(yùn)動(dòng)神經(jīng)發(fā)放活動(dòng)與關(guān)節(jié)運(yùn)動(dòng)軌跡相關(guān),以某種形式編碼了關(guān)節(jié)角度信息作為中樞對(duì)外周姿態(tài)控制的參考信號(hào)。同時(shí)肌梭運(yùn)動(dòng)神經(jīng)起到維持不同姿態(tài)下肌梭梭內(nèi)肌纖維張力的作用,調(diào)節(jié)感覺末梢的靈敏度以控制本體感覺發(fā)放頻率中對(duì)關(guān)節(jié)角度的線性編碼。由于人體正常運(yùn)動(dòng)狀態(tài)下的肌梭運(yùn)動(dòng)神經(jīng)元發(fā)放模式無法通過電生理技術(shù)手段測(cè)量,我們尚不了解肌梭運(yùn)動(dòng)神經(jīng)中的關(guān)節(jié)角度編碼模式�；谔摂M手臂模型仿真實(shí)驗(yàn)平臺(tái),我們提出并檢驗(yàn)了三種可能的肌梭運(yùn)動(dòng)控制編碼模態(tài)假設(shè)。各假設(shè)的正確性通過檢驗(yàn)假定的肌梭運(yùn)動(dòng)神經(jīng)編碼模態(tài)下,仿真的初級(jí)感覺傳入神經(jīng)發(fā)放是否與實(shí)驗(yàn)測(cè)量相匹配的方法驗(yàn)證。研究結(jié)果表明,在姿態(tài)控制中,神經(jīng)系統(tǒng)可能采取了對(duì)肌梭靈敏度的非線性控制策略,使肌梭運(yùn)動(dòng)神經(jīng)承擔(dān)起中樞向外周系統(tǒng)傳輸關(guān)節(jié)角度編碼信息的功能。4.研究肌肉間同步活動(dòng)對(duì)上肢帕金森震顫運(yùn)動(dòng)的貢獻(xiàn),及其產(chǎn)生的大腦和脊髓神經(jīng)回路基礎(chǔ)。建立實(shí)驗(yàn)采集帕金森震顫運(yùn)動(dòng)和肌電圖的方法,采用相干和互相關(guān)等方法分析帕金森震顫中各肌肉的節(jié)律性發(fā)放活動(dòng),提出“paired coherence”和“pool-averaged coherence”兩種評(píng)價(jià)指標(biāo)定量評(píng)估肌群間活動(dòng)的同步水平,并分析其與關(guān)節(jié)震顫運(yùn)動(dòng)幅度間的相關(guān)性。分析顯示,不同患者的上肢肌群震顫活動(dòng)的同步水平存在較大差異,且與上肢關(guān)節(jié)的震顫幅度成正相關(guān)。該結(jié)果表明,肌肉非自主發(fā)放活動(dòng)在肌群間的同步,是驅(qū)動(dòng)帕金森震顫運(yùn)動(dòng)的重要因素。這一研究為最新的解釋帕金森震顫運(yùn)動(dòng)產(chǎn)生機(jī)制的“調(diào)制-開關(guān)模型”假說提供了支持,并進(jìn)一步提出源自小腦和基底節(jié)系統(tǒng)的中樞振蕩信號(hào),經(jīng)過脊髓固有神經(jīng)元網(wǎng)絡(luò)的傳輸、整合和處理,支配對(duì)抗肌群中的交替發(fā)放活動(dòng),導(dǎo)致震顫運(yùn)動(dòng)產(chǎn)生的神經(jīng)模型。綜上,本論文建立了一個(gè)基于模型仿真和實(shí)驗(yàn)運(yùn)動(dòng)分析的神經(jīng)運(yùn)動(dòng)控制研究平臺(tái),并應(yīng)用于研究生理和病理狀態(tài)下,中樞脊髓神經(jīng)網(wǎng)絡(luò)在運(yùn)動(dòng)控制中的作用。研究結(jié)果為認(rèn)識(shí)神經(jīng)運(yùn)動(dòng)控制開辟了新思路和新方法,也對(duì)運(yùn)動(dòng)康復(fù)治療和臨床前評(píng)估具有理論指導(dǎo)意義。
[Abstract]:The study of physiological and pathological exercise control is an important content of understanding the structure and physiological functions of the sensory motor system, especially the central nervous system of the brain spinal cord. It is also the basis of providing exercise function compensation and rehabilitation for the patients with motor dysfunction. The research method of neural motion control is divided into experimental observation analysis and calculation model simulation The two: the experimental study of the identification of all levels of the loop in the sensorimotor system and the understanding of the behavior function is the basis for the establishment of the computational model, and the simulation results of the computational model can provide the neural information of the state of the system that can not be observed under the experimental conditions. Therefore, the experimental analysis and model simulation methods are aware of the perception of the central nervous system. The scientific problem discussed in this paper is that, under the theoretical framework of dual control of attitude and motion, each nerve loop in the brain and spinal cord is integrated with sensory information to control the modularized function in the process of motion execution. The work of this thesis breaks through the bottleneck of the present research method and the sensory system will be used. A large number of data and known information are integrated into a multi-scale computing model, and the neural control mechanism of physiological and pathological movements is studied from the system level. On the basis of earlier work, this paper improves the simulation platform of multi scale virtual arm model, and verifies the authenticity and effectiveness of the virtual arm model. The virtual arm model is used to analyze and propose the hypothetical central nonlinear coding hypothesis of the muscle spindle gamma nerve innervation, to build an experimental collection and analysis platform for the human upper limb movement experiment, and to analyze the correlation between the synergistic distribution of the muscle group and the amplitude of the tremor in the limb tremor of Parkinson's disease, and to further explore the God of the tremor of Parkinson's disease by using the virtual arm model. The main research contents and results of this paper include the following four aspects: (1.) developing a multi scale integrated virtual arm model on the basis of earlier work. We have developed a biomechanical model of the upper limb skeletal system, virtual muscle, muscle spindle, and Golgi tendon organ, and new new models. The spinal reflex loop and the spinal intrinsic neuron network model module are integrated and transplanted into the SIMULINK modeling and simulation platform. The parameters are optimized and the interface is integrated into a virtual arm system model with real physiological characteristics. We adopt a modular model structure to make it easy to update and replace the module, and have strong expansibility. According to the characteristics of customization and individuation, the model has great potential in simulating normal and pathological neural motion behavior, studying the mechanism of neural motion control, and providing a reliable and efficient simulation platform and environment.2. for the development of rehabilitation application and preclinical evaluation to verify the true neural behavior of the virtual arm model. The contribution of feedforward and feedback control to the stability of the upper limb endpoint attitude is quantitatively evaluated. The hand stiffness reflects the impedance characteristics of the hand, and the motion variability of the hand describes the stability of the hand under the influence of the intrinsic neural noise. These two indicators can quantitatively evaluate the stability of the hand under the attitude control. The neural behavior of the system model simulation (hand stiffness and variability) is compared with the experimental data of the human body to confirm the authenticity and validity of the virtual arm model. Because of the limitations of the experimental measurement methods, we can not accurately measure the contribution of the spinal reflex loop to the posture stability of the upper extremity at the present stage. In different motion control theories, there are different interpretations of the role of the proprioceptive feedback in motion control. The virtual arm model enables us to quantitatively evaluate the effect of closed loop sensory feedback on the resistance and stability of the system by designing the simulation experiments under open and closed loop conditions. Under the action of closed loop sensory feedback, the area of the hand stiffness ellipse increases by 35.75 + 16.99% (mean mean deviation, the same below), and the area of the hand variable ellipse is reduced by 49.41 + 21.19%. It shows that the noumenon sensory feedback in the closed loop attitude control of the spinal cord can resist the noise of the internal nerve and the disturbance of the external environment and maintain the stability of the multiple joints. .3. is a significant contribution to the study of the possible joint angle coding pattern in the muscle spindle motor control and the influence of the joint angle encoding in the peripheral proprioceptive afferent. Experimental evidence indicates that the downward movement of the muscle spindle motor nerve is related to the trajectory of the joint movement, and the joint angle information is coded as a central peripheral posture in some form. A reference signal of state control. At the same time, the muscle spindle motor plays the role of maintaining the muscle fiber tension of the muscle spindle in the different posture, regulating the sensitivity of the sensory endings to control the linear coding of the joint angle in the frequency of the proprioception. We do not understand the coding mode of the joint angle in the muscle spindle motor nerve. Based on the virtual arm model simulation experiment platform, we have proposed and tested three possible coding mode assumptions of the muscle spindle motion control. The correctness of each hypothesis is verified by the hypothesis of the assumed muscle spindle motor neural coding mode. The results show that in attitude control, the neural system may take a nonlinear control strategy for the sensitivity of the muscle spindle in the attitude control, which makes the muscle spindle motor function.4. to study the intermuscular synchronization activity in the central peripheral peripheral system to transmit the joint angle information. The contribution of the Parkinson tremor movement of the upper limb and the basis of the neural circuit of the brain and spinal cord produced by the upper limb. A method of experimental acquisition of Parkinson's tremor movement and electromyography is established. The rhythmic activities of the muscles in Parkinson's tremor are analyzed by means of coherence and cross correlation, and "paired coherence" and "pool-averaged coherence" are proposed. The two evaluation indexes quantified the synchronous level of inter group activity and analyzed its correlation with the motion amplitude of joint tremor. The analysis showed that the synchronization level of the tremor activity of the upper limbs of the different patients was different, and was closely related to the amplitude of the tremor of the upper limb joints. The synchronization between the muscle groups is an important factor in driving the Parkinson tremor movement. This study provides support for the latest "modulation switching model" hypothesis to explain the mechanism of Parkinson's tremor movement, and further proposes the central oscillation signals derived from the cerebellum and basal ganglia system, through the transmission of the neural network of the spinal cord and the integration of the spinal cord. In this paper, a research platform for neural motion control based on model simulation and experimental motion analysis is established, and the role of the middle spinal cord neural network in motion control is studied under physiological and pathological conditions. The results have opened up new ideas and new methods for understanding neural motor control, and also have theoretical guiding significance for exercise rehabilitation and pre clinical assessment.

【學(xué)位授予單位】：上海交通大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2015
【分類號(hào)】：R742.5

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