北京生物醫(yī)學(xué)工程

基于多傳感器信息的新型穿戴式上肢外骨骼康復(fù)機(jī)器人

A new wearable upper limb exoskeleton rehabilitation robot based on multi-sensor information

作者：劉壯朱純煜朱越劉蘇喻洪流李素姣

單位：上海理工大學(xué)康復(fù)工程與技術(shù)研究所（上海 200093）上海康復(fù)器械工程技術(shù)研究中心（上海 200093）民政部神經(jīng)功能信息與康復(fù)工程重點(diǎn)實(shí)驗(yàn)室（上海 200093）

關(guān)鍵詞：多信息；上肢外骨骼；康復(fù)機(jī)器人；肌電信號；多模式

分類號：R318.01

出版年·卷·期（頁碼）：2021·40·3（273-278）

摘要：

目的設(shè)計(jì)基于多傳感器信息的新型穿戴式上肢外骨骼康復(fù)機(jī)器人，以解決上肢外骨骼康復(fù)機(jī)器人便攜性不佳、患者參與度較低、訓(xùn)練模式自適應(yīng)不足等問題，并探究受試者穿戴外骨骼時(shí)肌肉激活程度、肌電信號預(yù)測關(guān)節(jié)角度的準(zhǔn)確性以及實(shí)現(xiàn)上肢康復(fù)訓(xùn)練的可行性。方法該設(shè)備機(jī)械結(jié)構(gòu)包括肘關(guān)節(jié)和腕關(guān)節(jié)，采用模塊化設(shè)計(jì)并結(jié)合3D打印技術(shù)；控制系統(tǒng)包括肌電采集、應(yīng)力采集、姿態(tài)采集等單元，并設(shè)計(jì)主動、被動和助動三種訓(xùn)練模式。受試者穿戴外骨骼機(jī)器人后進(jìn)行屈-伸肘實(shí)驗(yàn)，對比有、無輔助力時(shí)手臂肌肉激活程度；分析肘關(guān)節(jié)角度，并對比肌電信號預(yù)測的關(guān)節(jié)運(yùn)動角度；驗(yàn)證機(jī)器人運(yùn)行性能與應(yīng)力檢測效果。結(jié)果受試者穿戴外骨骼康復(fù)機(jī)器人安全可靠地完成了屈-伸肘動作，受試者肱二頭肌、肱三頭肌肌肉激活程度在有、無輔助力時(shí)分別減弱約32%、11%，肌電信號預(yù)測關(guān)節(jié)角度準(zhǔn)確度約95%，應(yīng)力測量值誤差均低于5%。結(jié)論上肢外骨骼機(jī)器人可以給人體提供輔助力、預(yù)測關(guān)節(jié)角度，機(jī)器人通過肌電、應(yīng)力以及位置信息輔助患者實(shí)現(xiàn)上肢康復(fù)訓(xùn)練具有可行性。

Objective To design new wearable arm exoskeleton rehabilitation robots based on multi-sensor information, in order to solve problems of poor portability of upper limb exoskeleton rehabilitation robots, the low degree of participation for patients and insufficient training mode adaptability, and to explore the muscle activation degree of participants wearing exoskeletons, accuracy of electromyographic signal predicting the joint angle and the feasibility of the upper limb rehabilitation training. Methods The mechanical structure of the device, which included elbow and wrist joints, was modular and combines 3D printing technology; the control system included electromyography (EMG) acquisition, stress acquisition, attitude acquisition and other units, and three training modes of active, passive and assisted were designed. After the subjects wore the exoskeleton robot, the elbow flexion and extension experiment was conducted to compare the activation degree of arm muscles with and without auxiliary force; the elbow angle was analyzed and the joint motion angle predicted by EMG signal was compared. The running performance and stress detection effect of robots were verified. Results The subjects with the exoskeleton rehabilitation robot completed the flexion and elbow extension movement safely and reliably. The muscle activation degrees of the biceps and triceps of the subjects were reduced by 32% and 11% with and without assistance, respectively. The accuracy of EMG signal in predicting the joint angle was about 95%, and the error of stress measurement was less than 5%. Conclusion The upper extremity exoskeleton robot can provide human bodies with auxiliary force and predict the joint angle. It is feasible for the robot to assist patients to achieve upper extremity rehabilitation training with EMG, stress and position information.

參考文獻(xiàn)：

[1] Mazzoleni S, Battini E, Crecchi R, et al. Upper limb robot-assisted therapy in subacute and chronic stroke patients using an?innovative end-effector haptic device:?a pilot study[J].Neuro‐Rehabilitation,2018,42(1):43-52.

[2] 張曉玉,王凱旋.機(jī)器人輔助技術(shù)、康復(fù)機(jī)器人與智能輔具[J].中國康復(fù),2013,04:246-248.

???Zhang XY, Wang KX. Robot-assisted technology, Rehabilitation robot and Intelligent Auxiliaries [J]. Rehabilitation in China, 2013,04:246-248.

[3] Bai YL, Hu?YS, Wu?Y, et al.?A?prospective, randomized, single-blinded trial on the effect of early rehabilitation on daily activities and motor function of patients with hemorrhagic stroke [J]. Journal of Clinical Neuroscience ,2012,19(10):1376-1379.

[4] 周娃妮,邴建華.肌電反饋治療技術(shù)在腦卒中患者中的應(yīng)用及對認(rèn)知功能的影響研究[J].按摩與康復(fù)醫(yī)學(xué),2019,10(20):21-22.

[5] Mehrholz J ,Platz T ,Kugler J ,et al .Electromechanical and robot-assisted arm training for improving arm function and activities of daily living after stroke[J].Stroke ,2008,40(4):CD006876

[6] Fellag?R?,Benyahia T ,Drias?M?et al?.Sliding mode control?of a 5 dofs upper limb exoskeleton robot [C]//The 5th International Conference on Electrical Engineering-Boumerdes ,Boumerdes :IEEE,2017: 5-10.

[7] 許祥.基于外骨骼的上肢康復(fù)機(jī)器人設(shè)計(jì)與研究[D].南京：南京理工大學(xué),2014.

???Xu X. Design and Research of upper limb Rehabilitation robot based on exoskeleton [D]. Nanjing：Nanjing University of Science and Technology, 2014.

[8] 張神權(quán)．表面肌電模式識別的新控制策略研究［D］．合肥:中國科學(xué)技術(shù)大學(xué)，2017．

???Zhang SQ. A new control strategy for surface EMG pattern Recognition [D]. Hefei: University of Science and Technology of China, 2017.

[9] Lloyd DG, Besier TF. An EMG-driven musculoskeletal model to estimate muscle forces and knee joint moments in vivo[J]. Journal of Biomechanics, 2003, 36(6): 765-776.

[10] 王露露,胡鑫,胡杰,等.一種上肢外骨骼康復(fù)機(jī)器人的控制系統(tǒng)研究[J].生物醫(yī)學(xué)工程學(xué)雜志,2016,33(6):1168-1175.

Wang LL?,Hu X?,Hu J,et al. Research on control system of an exoskeleton upper-limb rehabilitation robot[J].?Journal of Biomedical Engineering,2016,33(6):1168-1175.

[11] Daunoraviciene K?,Adomaviciene A?,Grigonyte A?,et al?.Effects of robot-assisted training on upper limb functional recovery during the rehabilitation of poststroke patients [J] .TechnolHealth Care ,2018, 26(S2): 533-542.

[12] Lenzi T ,De Rossi S M M ,Vitiello N ,et al.Intention-Based EMG Control for Powered Exoskeletons[J].IEEE Transactions on Biomedical Engineering,2012, 59(8):2180-2190.

[13] 張蔚然.上肢外骨骼康復(fù)機(jī)器人控制系統(tǒng)研究[D].?濟(jì)南:山東建筑大學(xué), 2019.

Zhang WR . Research on control system of upper-limb exoskeleton rehabilitation robot [D] .Jinan：Shandong Jianzhu University,2019.

?[14] 張琳琳．人體上肢生物力學(xué)建模和典型運(yùn)動的生物力學(xué)研究［D］．上海:上海交通大學(xué)，2009．

????Zhang LL. Biomechanical modeling of human upper limbs and biomechanical studies of typical movements [D]. Shanghai: Shanghai Jiaotong University,2009.

[15] 潘禮正,宋愛國,徐國政,等.上肢康復(fù)機(jī)器人實(shí)時(shí)安全控制[J].機(jī)器人,2012,34(2):197-203.

Pan LZ ,Song AG ,Xu GZ ,et al .Real-time safety control of upper-limb rehabilitation robot[J] .Robot ,2012,34(02):197-203.

[16] 王亞峰,陳昊,張軍,等.基于CAN的分布式機(jī)器人控制系統(tǒng)設(shè)計(jì)[J].電子設(shè)計(jì)工程, 2017,25(14): 148-151

Wang?YF ,Chen H ,Zhang J ,et al .The design of distributed robot control system based on CAN bus[J] . Electronic Design Engineering ,2017,25(14): 148-151.

[17] 陳思媛,曾富榮,陳靈聰,等.便攜式肘關(guān)節(jié)康復(fù)訓(xùn)練機(jī)器人[J].科學(xué)技術(shù)創(chuàng)新,2019（1）:65-68.

[18] Kumar P ,Potluri C ,Sebastian A ,et al .Adaptive multi sensor based nonlinear identification of skeletal muscle force[J].WSEAS Transactions on Systems , 2010, 9(10/12):1050-1062.

[19] 胡成彬.上肢康復(fù)機(jī)器人機(jī)電系統(tǒng)研制[D].北京：北京化工大學(xué), 2019.

Hu?CB?.Development?of?electromechanical?system?for?upper?limb?rehabilitation?robot[D]?.Beijing：Beijing?University?of?Chemical?Technology?,2019.

[20] Gilliaux M ,Lejeune T M ,Detrembleur C ,et al .Using the robotic device reaplan as a valid ,reliable , and sensitive tool to quantify upper limb impairments in stroke patients[J] .Journal of Rehabilitation Medicine ,2014, 46(2): 117-125

[21] Anam K?,Rosyadi?A A ,Sujanarko?B?,et al?.Myoelectric control systems for hand rehabilitation device: A review [C]//2017 4th International Conference on Electrical Engineering ,Computer Science and Informatics ( EECSI).Yogyakarta: IEEE，2017: 1-6．

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