北京生物醫(yī)學工程

康復機器人訓練效果客觀評價方法的研究進展

Research progress on objective evaluation methodsof training effect of rehabilitation robot

作者：李瑩華李貞蘭陳曉偉徐國興連雅雯

單位：吉林大學第一醫(yī)院康復醫(yī)學科（長春 130021） <p>通訊作者：李貞蘭，教授。[email protected]</p>

關鍵詞：康復機器人；評價方法；傳感器；表面肌電信號；體感交互；數(shù)學建模

分類號：R318  <p> </p>

出版年·卷·期（頁碼）：2022·41·2（202-207）

摘要：

近年來，機器人技術不斷應用于康復醫(yī)學領域，因康復機器人具有提高康復效率、保證康復質(zhì)量、降低人力成本等優(yōu)勢，在臨床應用中受到越來越多的關注。然而，目前康復機器人臨床療效的評價仍依賴于傳統(tǒng)的量表評價法，無法實時提供準確的運動功能評價指標來有效指導和提供康復治療方案。因此，研發(fā)出與治療系統(tǒng)相匹配的、客觀定量的康復療效評價系統(tǒng)顯得尤為重要。本文就信息獲取的類型，從基于康復機器人內(nèi)部傳感器、基于表面肌電信號、基于體感交互設備對目前國內(nèi)外康復機器人訓練效果的客觀評價方法予以綜述，以期為康復機器人臨床療效評價系統(tǒng)方面的研究提供參考。

In recent years, robot technology has been widely used in the field of rehabilitation medicine. Because rehabilitation robot has the advantages of improving rehabilitation efficiency, ensuring rehabilitation quality and reducing labor cost, it has attracted more and more attention in clinical application. However, at present, the evaluation of the clinical efficacy of rehabilitation robot still depends on the traditional scale evaluation method, which can not provide accurate motor work evaluation indexes in real time, so as to effectively guide and provide rehabilitation treatment plans. Therefore, it is particularly important to develop an objective and quantitative rehabilitation efficacy evaluation system matching with the treatment system. Based on the types of information acquisition, this paper summarizes the objective evaluation methods of rehabilitation robot training effect from the internal sensors of rehabilitation robot, surface EMG signal and somatosensory interactive equipment, in order to provide reference for the research of rehabilitation robot clinical efficacy evaluation system.

參考文獻：

[1]?Li X,?Zhong J. Upper limb rehabilitation robot system based on internet of things remote control?[J]. IEEE Access,2020, 8:154461-154470.

[2]?田偉.醫(yī)用機器人的發(fā)展現(xiàn)狀[J]. 中華醫(yī)學雜志,?2021,?101(5):?374-378.

[3]?勵建安. 人機共融,天人合一——關于康復機器人應用與發(fā)展的思考 [J]. 中國康復醫(yī)學雜志,2020,35(8):897-899.

[4]?錢葉葉,吳毅. 腦卒中后上肢及手運動功能定量評定方法的研究進展 [J]. 中華物理醫(yī)學與康復雜志,2019,41(6):469-472.

[5]?Brihmat N,?Loubinoux I,?Castel-Lacanal E, et al. Kinematic parameters obtained with the ArmeoSpring for upper-limb assessment after stroke: a reliability and learning effect study for guiding parameter use?[J]. Journal of?NeuroEngineering and Rehabilitation,?2020,17(1):?130.

[6]?牛傳欣,崔立軍,鮑勇,等. 上肢康復機器人用于神經(jīng)康復的研究進展[J].中國康復醫(yī)學雜志,?2020,?35(8):?916-920.

[7]?Colombo R,?Pisano F,?Mazzone A, et al. Design strategies to improve patient motivation during robot-aided rehabilitation?[J].?Journal of?NeuroEngineering and Rehabilitation,2007,4:?3.

[8]?Longhi M,?Merlo A,?Prati P, et al. Instrumental indices for upper limb function assessment in stroke patients: a validation study?[J]. Journal of?NeuroEngineering and Rehabilitation,2016,13:?52.

[9]?Koeppel T,?Pila O. Test-retest reliability of kinematic assessments for upper limb robotic rehabilitation?[J].?IEEE?Transactions on Neural Systems and Rehabilitation Engineering,?2020,28(9):?2035-2042.

[10]?Huang J,?Tu X,?He J. Design and evaluation of the RUPERT wearable upper extremity exoskeleton robot for clinical and in-home therapies?[J].?IEEE?Transactions on Systems,Man?and Cybernetics: Systems,?2016,?46(7):?926-935.

[11]?Vergaro E,?Casadio M,?Squeri V, et al. Self-adaptive robot training of stroke survivors for continuous tracking movements[J].?Journal of?NeuroEngineering and Rehabilitation,?2010,?7:?13.

[12]?Lambercy?O,Dovat?L,Yun?H,?et?al.?Effects?of?a?robot-assisted?training?of?grasp?and?pronation/supination?in?chronic?stroke:?a?pilot?study[J].?Journal?of?NeuroEngineering?and?Rehabilitation,2011,8:?63.

[13]?Schwarz A,?Kanzler CM,?Lambercy O, et al. Systematic review on kinematic assessments of upper limb movements after stroke?[J]. Stroke,?2019,?50(3):?718-727.

[14]?張海燕,吳方超,李建華,等. 上肢康復機器人輔助訓練對腦卒中患者上肢功能的影響 [J]. 中國運動醫(yī)學雜志,2019,38(10):859-863.

Zhang HY, Wu FC, Li JH, et al.?Effect of?upper limb rehabilitation robot assisted training on upper limb function of stroke survivors?[J]. Chinese Journal of Sports Medicine,2019,38(10):859-863.

[15]?朱琳,席艷玲,黃海霞,等.機器人輔助訓練對腦卒中患者上肢屈肌痙攣的療效觀察及表面肌電圖分析[J].中國康復醫(yī)學雜志,2020,35(8):954-958.

[16]?Liparulo?L,?Zhang?Z,?Panella?M, et al. A novel fuzzy approach for automatic Brunnstrom stage classification using surface electromyography[J].?Medical?&?Biological?Engineering?&?Computing,?2017,?55:?1367-1378.

[17]?王豐焱,張道輝,李自由,等.適用不同Brunnstrom等級患者基于表面肌電信號的動作識別方法[J].機器人,?2020,?42(6):?661-671, 685.

Wang FY, Zhang DH, Li ZY, et al. Method for sEMG-based motion recognition for patients at different Brunnstrom stages[J]. Robot, 2020,42 (6):?661-671, 685.

[18]?西安交通大學. 一種基于虛擬誘導肌電定量狀態(tài)評估系統(tǒng)及方法：CN201910696491.0[P].?2019-11-29.

[19]?王博超,張新峰. 基于人工智能和臨床診斷的上肢康復評估方法研究進展 [J]. 北京生物醫(yī)學工程,2018,37(1):103-108.

Wang BC, Zhang XF. Research progress of assessment methods based on artificial?intelligence and clinical diagnosis in upper limb rehabilitation[J]. Beijing Biomedical Engineering,?2018,37(1):?103-108.

[20]?Chen L,?Lin M,?Deng Q, et al. Research on motion capture of upper limb rehabilitation robot?[C]//?2019 IEEE International Conference on Real-time Computing and Robotics. Naples, Italy: IEEE?Press,?2019:?48-52.

[21]?Zong C,?Clady X,?Chetouani M. An embedded human motion capture system for an assistive walking robot?[C]// IEEE?2011 ?International Conference on Rehabilitation Robotics,?2011, 2011:?5975439.

[22]?Murphy MA,?Willén C,?Sunnerhagen KS.?Kinematic variables quantifying upper-extremity performance after stroke during reaching and drinking from a glass?[J].?Neurorehabilitation and?Neural?Repair,?2011,?25(1):?71-80.

[23]?Brokaw EB,?Lum PS,?Cooper RA, et al. Using the Kinect to limit abnormal kinematics and compensation strategies during therapy with end effector robots?[C]//?2013 IEEE 13th?International Conference on Rehabilitation?Robotics. Seattle, WA, USA:?IEEE?Press,?2013.

[24]?韓志峰,曹磊,楊文璐,等. 基于體感技術上肢康復游戲系統(tǒng)的評價模塊 [J]. 中國康復理論與實踐,2017,23(11):1341-1345.

Han ZF, Cao L, Yang WL, et al. Upper?limb rehabilitation game system based on somatosensory technique:assessment module[J]. ?Chinese Journal of Rehabilitation Theory and Practice,2017,23(11):1341-1345.

[25]?劉朗,劉勇國,李巧勤,等.腦卒中患者運動功能自動化評定研究進展[J].中國康復理論與實踐,2020,26(9):1028-1032.

Liu L, Liu YG, Li QQ, et al. Advance in automatic assessment of motor function for patients with stroke(review)?[J]. ?Chinese Journal of Rehabilitation Theory and Practice,?2020,26(9):1028-1032.

[26]?Kim S,Park S,Lee O.?Development of a diagnosis and evaluation system for hemiplegic patients post-stroke based on motion recognition tracking and analysis of wrist joint kinematics?[J]. Sensors,?2020,?20(16):4548.

[27]?Li CG,Cheng?L,Yang?H, et al. An automatic rehabilitation assessment system for hand function based on leap motion and ensemble learning?[J]. Cybernetics and Systems,2020,52(1):?3-25.

[28]?楊文璐,程恒祺,夏斌,等.基于Leap Motion的手功能康復評估及游戲系統(tǒng)設計[J].傳感器與微系統(tǒng),2018,?37(10):?102-104.

Yang WL, Cheng HQ, Xia B, et al.?Design?of?hand function rehabilitation?assessment?and game system based on LeapMotion [J]. Transducer and Microsystem Technologiess,2018,37(10):?102-104.

[29]?王睿,朱業(yè)安,盧巍.骨骼關鍵點檢測技術在康復評估中的應用進展[J].中國康復醫(yī)學雜志,2020,35(7):?886-890.

[30]?Hennes M,?Bollue K,?Arenbeck H, et al. A proposal for patient-tailored supervision of movement performance during end-effector-based robot-assisted rehabilitation of the upper extremities?[J]. BioMedical Engineering OnLine,2014,60(3):193-197.

[31]?王建輝,張程,紀雯,等. 基于AHP-模糊綜合評判的上肢康復機器人康復評價方法 [J]. 沈陽大學學報(自然科學版),2012,24(3):47-51.

Wang JH, Zhang C, Ji W, et al. Rehabilitation evaluation method of upper limb rehabilitation robot based on AHP fuzzy comprehensive evaluation[J]. Journal of Shenyang University(Natural Science)?,?2012,?24(3):?47-51.

[32]?王彤. 五自由度上肢康復機器人康復評價系統(tǒng)的研究 [D]. 沈陽：東北大學，2015.

服務與反饋：

【文章下載】【加入收藏】

提示：您還未登錄，請登錄！點此登錄

51黑料吃瓜在线观看,51黑料官网|51黑料捷克街头搭讪_51黑料入口最新视频