Cooperation control of a hybrid lower limb rehabilitation robot
This study presents a model of cooperation between two planar manipulators including an orthosis and a programmable plate in form of a hybrid lower limb rehabilitation robot, which was designed and built at the University of Guilan. The aims of cooperation are to distribute the power required to move between the cooperative manipulators and also reduce the interaction forces between orthosis and leg. The cooperation is performed with two modes using the adjustment of the plate forces, a constant force in the vertical direction (CFV) and variant force proportional to orthosis torque (VFPOT). Kinematic and dynamic analysis of the hybrid lower limb rehabilitation robot and its control are also discussed in this study. The performance and effectiveness of the proposed hybrid robot are demonstrated on a healthy person in real-time. Each walking trial lasted 60 s and repeated 20 times for every mode. The walking speed was considered to be 1.5 km/h and weight compensator was adjusted with a constant weight unloading level of 70%. The results show that the VFPOT mode leads to a 45% reduction in the driving torque of the hip and knee joints compared to orthosis-only. This reduction is expected to reduce interaction force at the connection straps. So, it provides more patient comfort and safety, which can be effective in improving the time and process of rehabilitation.
CleryABhallaARuddAG, et al. Trends in prevalence of acute stroke impairments: a population-based cohort study using the South London Stroke Register. PLoS Med2020; 17: e1003366.
2.
SrivastavaSKaoPCReismanDS, et al. Robotic assist-as-needed as an alternative to therapist-assisted gait rehabilitation. Int J Phys Med Rehabil2016; 4: 370.
3.
TakeuchiNIzumiS. Rehabilitation with poststroke motor recovery: a review with a focus on neural plasticity. Stroke Res Treat2013; 2013: 128641.
4.
RochaLSOGamaGCBRochaRSB, et al. Constraint induced movement therapy increases functionality and quality of life after stroke. J Stroke Cerebrovasc Dis2021; 30: 105774.
5.
MengWLiuQZhouZ, et al. Recent development of mechanisms and control strategies for robot-assisted lower limb rehabilitation. Mechatronics2015; 31: 132–145.
6.
BragoniMBroccoliMIosaM, et al. Influence of psychologic features on rehabilitation outcomes in patients with subacute stroke trained with robotic-aided walking therapy. Am J Phys Med Rehabil2013; 92: e16–e25.
7.
MoroneGPaolucciSCherubiniA, et al. Robot-assisted gait training for stroke patients: current state of the art and perspectives of robotics. Neuropsychiatr Dis Treat2017; 13: 1303–1311.
8.
WangJLiuJZhangG, et al. Periodic event-triggered sliding mode control for lower limb exoskeleton based on human-robot cooperation. ISA Trans2022; 123: 87–97.
9.
HobbsBArtemiadisP. A review of robot-assisted lower-limb stroke therapy: unexplored paths and future directions in gait rehabilitation. Front Neurorobot2020; 14: 19.
10.
CardonaMDestaracMGarcíaC. Exoskeleton robots for rehabilitation: state of the art and future trends. In: 2017 IEEE 37th central America and panama convention (CONCAPAN XXXVII), 2017, pp.1–6. New York: IEEE.
11.
van SilfhoutLVáňaZPĕtiokýJ, et al. Highest ambulatory speed using Lokomat gait training for individuals with a motor-complete spinal cord injury: a clinical pilot study. Acta Neurochir2020; 162: 951–956.
12.
ChenGChanCKGuoZ, et al. A review of lower extremity assistive robotic exoskeletons in rehabilitation therapy. Crit Rev Biomed Eng2013; 41: 343–363.
13.
KalitaBNarayanJDwivedySK. Development of active lower limb robotic-based orthosis and exoskeleton devices: a systematic review. Int J Soc Robot2021; 13: 775–793.
14.
LiYChenWWangJ, et al. Mechanical design and optimization on lower extremity rehabilitation robot. In: 2020 15th IEEE conference on industrial electronics and applications (ICIEA), 2020, pp.1612–1617. New York: IEEE.
15.
MiaoMGaoXZhuW. A construction method of lower limb rehabilitation robot with remote control system. Appl Sci2021; 11: 867.
16.
HidlerJWismanWNeckelN. Kinematic trajectories while walking within the Lokomat robotic gait-orthosis. Clin Biomech2008; 23: 1251–1259.
17.
NarayanJKumar DwivedyS. Preliminary design and development of a low-cost lower-limb exoskeleton system for paediatric rehabilitation. Proc IMechE, Part H: J Engineering in Medicine2021; 235: 530–545.
18.
YanoHTamefusaSTanakaN, et al. Gait rehabilitation system for stair climbing and descending. In: 2010 IEEE haptics symposium, 2010, pp.393–400. New York: IEEE.
19.
KalitaBDwivedySK. Nonlinear dynamic response of pneumatic artificial muscle: a theoretical and experimental study. Int J Non Linear Mech2020; 125: 103544.
20.
ChoiSKimSWJeonHR, et al. Feasibility of robot-assisted gait training with an end-effector type device for various neurologic disorders. Brain Neurorehabil2020; 13:1.
21.
TagliamonteNLSergiFCarpinoG, et al. Human-robot interaction tests on a novel robot for gait assistance. In: 2013 IEEE 13th international conference on rehabilitation robotics (ICORR), 2013, pp.1–6. New York: IEEE.
22.
VasanthakumarMVinodBMohantaJK, et al. Design and robust motion control of a planar 1P-2P RP hybrid manipulator for lower limb rehabilitation applications. J Intell Robot Syst2019; 96: 17–30.
23.
ChenJHuangYGuoX, et al. Parameter identification and adaptive compliant control of rehabilitation exoskeleton based on multiple sensors. Measurement2020; 159: 107765.
24.
AlmaghoutKTarvirdizadehBAlipourK, et al. Design and control of a lower limb rehabilitation robot considering undesirable torques of the patient’s limb. Proc IMechE, Part H: J Engineering in Medicine2020; 234: 1457–1471.
25.
MohantaJKSaxenaCGuptaG, et al. Kinematic analysis of a passive sitting/lying type lower limb rehabilitation robot. In: Proceedings of the 2nd international conference on machines and mechanisms, Kanpur, India, 2015, pp.1–12. Kanpur: Indian Institute of Technology.
26.
LiJZuoSXuC, et al. Influence of a compatible design on physical human-robot interaction force: a case study of a self-adapting lower-limb exoskeleton mechanism. J Intell Robot Syst2020; 98: 525–538.
27.
YangJHeYShiP, et al. A review on human intent understanding and compliance control strategies for lower limb exoskeletons. Proc IMechE, Part I: J Systems and Control Engineering2022; 236: 1067–1086.
28.
Baye-WallaceLThalmanCMLeeH. Entrainment during human locomotion using a lightweight soft robotic hip exosuit (SR-HExo). IEEE Robot Autom Lett2022; 7: 6131–6138.
29.
HussainFGoeckeRMohammadianM. Exoskeleton robots for lower limb assistance: a review of materials, actuation, and manufacturing methods. Proc IMechE, Part H: J Engineering in Medicine2021; 235: 1375–1385.
30.
SlootLBaeJBakerL, et al. O 089 - A soft robotic exosuit assisting the paretic ankle in patients post-stroke: effect on muscle activation during overground walking. Gait Posture2022; 95: 217–218.
31.
WuQZhangYChenY. Design, control, and experimental verification of a soft knee exoskeleton for rehabilitation during walking. Proc IMechE, Part I: J Systems and Control Engineering2022; 236: 138–152.
32.
WangY-LWangK-YZhangZ-X. Design, comprehensive evaluation, and experimental study of a cable-driven parallel robot for lower limb rehabilitation. J Braz Soc Mech Sci Eng2020; 42: 1–20.
33.
WangYWangKZhangZ, et al. Control strategy and experimental research of a cable-driven lower limb rehabilitation robot. Proc IMechE, Part C: J Mechanical Engineering Science2021; 235: 2468–2481.
34.
ShiDZhangWZhangW, et al. A review on lower limb rehabilitation exoskeleton robots. Chin J Mech Eng2019; 32(1): 11.
35.
RienerRLünenburgerLJezernikS, et al. Patient-cooperative strategies for robot-aided treadmill training: first experimental results. IEEE Trans Neural Syst Rehabil Eng2005; 13: 380–394.
36.
ErdmannW. Geometry and inertia of the human body. Acta Phys Pol A2019; 135: 961–964.
37.
WhittleMW. Gait analysis: an introduction. Edinburgh: Butterworth-Heinemann, 2014.
