Human muscle fatigue is identified as one of the causes to musculuskeletal disorder (MSD). The objective of this paper is to investigate the effect of an exoskeleton in dealing with muscle fatigue in a virtual environment. The focus of this work is, for the exoskeleton to provide support as needed by human joint. A (Proportional, Integration and Derivative) controller is used for both human and exoskeleton. Simmechanics and Simulink are used to evaluate the performance of the exoskeleton. Experiments show that human is able to maintain doing the job by wearing the exoskeleton

Ali, SK

Tokhi, MO

LSBU Research Open

August 1, 2017 16:34 ws-procs9x6-9x6 CLAWAR 2017-Proceedings Sec2-6p56 page 5656UPPER-LIMB EXOSKELETONFOR HUMAN MUSCLE FATIGUES. K. ALI∗Autmomatic Control and System Engineering, University of Sheﬃeld,Sheﬃeld, United Kingdom∗E-mail: skali1@sheﬃeld.ac.ukM. O. TOKHISchool of Engineering, London South Bank UniversityLondon, United KingdomHuman muscle fatigue is identiﬁed as one of the causes to musculuskeletaldisorder (MSD). The objective of this paper is to investigate the eﬀect ofan exoskeleton in dealing with muscle fatigue in a virtual environment. Thefocus of this work is, for the exoskeleton to provide support as needed byhuman joint. A (Proportional, Integration and Derivative) controller is used forboth human and exoskeleton. Simmechanics and Simulink are used to evaluatethe performance of the exoskeleton. Experiments show that human is able tomaintain doing the job by wearing the exoskeleton.Keywords: Predictive fatigue model; upper-limb exoskeleton; virtual environ-ment.1. IntroductionMuscle fatigue is a well-known problem to human. Many factors could becontributed to human fatigue such as heavy physical activities, repetitiveworks, dealing with above-head work and duration of exposure to work-ing environment. Muscle fatigue could eﬀect human’s quality of life andperformance degradation. In a worse scenario, fatigue could lead to muscu-luskeletal disorder (MSD). There are two sectors that could lead human tocritical fatigue: industry and rehabilitation.Exoskeleton is one of the solution to solve human fatigue problem. Sev-eral works have been done such as in.1,2 Most current works related to mus-cle fatigue and exoskeleton use electromyography (EMG) signal to identifythe fatigue. Another ways to measure fatigue is by adding the fatigue modelAugust 1, 2017 16:34 ws-procs9x6-9x6 CLAWAR 2017-Proceedings Sec2-6p56 page 5757to the developed muscle model.2–4 However, a limitation to the second ap-proach is, it is diﬃcult to acquire an accurate force distribution for eachindividu muscle.4,5 Hence,5 proposed a new fatigue model which using aninformation from joint level. The torque of human joint could be acquiredusing inverse dynamics. Due to this reason, an investigation is done to seethe eﬀect of joint fatigue model developed by Ma et.al (2009) to human jointand to evaluate the performance of an exoseleton in dealing with humanfatigue during movements.To achieve the investigation, the joint fatigue model developed by5 isapplied to human joint. Then, an algorithm is developed to activate theexoskeleton using the reading from human joint. In the Section (2), thejoint fatigue model is introduced, and an observation is done. Then, in theSection (3), the performance of the exoskeleton with human joint fatiguemodel is presented.2. Human Joint Fatigue ModelAs mention in Section (1), joint fatigue model by5 is used. The joint fatiguemodel is an extension from muscle fatigue model, which also developed byMa et. al. Initially, Ma et. al developed fatigue index which presented as inEq.(1). The basis new fatigue muscle model is presented in Eq.(2). Furtherexplanation could be referred to.4dU(t)dt=MVCFcem(t)FloadFcem(t)(1)dFcem(t)dt= −kFcem(t)MVCFload(t) (2)dτcem(t)dt= −k τcem(t)τMVCτjoint(t) (3)Since this paper is applying joint fatigue model, thus Eq. (2) could berewriten as in Eq. (3). The deﬁnition for each term in Eq.(1), (2) and (3)are presented in Table (1). Simulink is used as a platform to apply the jointfatigue model and Simmechanic is used as a platform for human simulation.Fig. (1) shows human fatigue model system. As shown in Fig. (1)(a),there are three main blocks: fatigue model, human-exoskeleton and per-formance. The fatigue model block contains Eq.(3). Fig.(1)(b) shows anAugust 1, 2017 16:34 ws-procs9x6-9x6 CLAWAR 2017-Proceedings Sec2-6p56 page 5858Table 1. Parameters in muscle and joint fatigue model.4,5Muscle-fatigue Model Unit DeﬁnitionMVC / τmax Newton(N) Muscle Maximum voluntary contractionFcem / τcem Newton(N) Muscle force capacity at time instant tFload / τload Newton(N) Muscle load at time instant tJoint-fatigue Model Unit Deﬁnitionτmax Newton meter (Nm) Maximum joint strengthτcem Newton meter (Nm) Joint strength at time instant tτload Newton meter (Nm) Torque load at time instant tk min−1 Fatigue ratet min Timeintegration between the joint fatigue to human model. Revolute joint isused to present human joint. Thus, it is essential to have a controller tocontrol the joint. In this paper, conventional PID controller is used for theshoulder joint. A conventional PID controller is chosen because of its easy-ness in tuning the parameter. The parameters for Kp, Ki and Kd werechosen by a known PID tuning method.Fig. 1. (a) Human with fatigue model (b) fatigue model.3. Integration of Human Joint Fatigue and ExoskeletonFig.(2)(a) presents the overall system for exoskeleton with human andFig.(2)(b) presents the integration of the exoskeleton with the human fa-tigue model. There are three main blocks: PID, human-exoskeleton andperformance block. Similar as in Section (2), both human and exoskeletonwere controlled by using PID controller, and iterative approach is used toacquire the parameters.’PID’ block contains controller for human and exoskeleton. It also hastwo important blocks: Calculate Fatigue and Decide Assistive Torque block.August 1, 2017 16:34 ws-procs9x6-9x6 CLAWAR 2017-Proceedings Sec2-6p56 page 5959Fig. 2. (a) Human-exoskeleton system (b) Integration of exoskeleton and fatigue model.Table 2. Parameters for (PID).Parameter Shoulder JointProportional 10.0Integration 1.0Derivative 0.1In these two blocks, the algorithm for the activation process is presented.The ﬁrst algorithm in ‘Calculate Fatigue’ block is presented as follows:(i) To measure the human fatigue in joint level, there are three importantinformation: maximum voluntary contraction of joint torque (τMVC),integrated joint torque (∫τ(u, θ, θ˙, θ¨)) and angle for θ3 and θ4.(ii) To calculate (τMVC), the formula is obtained from [6]. The formula ispresented in Eq.(4). This value presents the maximum torque valuesfor shoulder joint at t = 0.τMVC = (227.338 + 0.525θ3 − 0.296θ4)0.2854 (4)(iii) Then, the fatigue could be measured by using Eq. 3. In this work,the value of fatigue rate (k) is set to equal 1. After applying fatigueequation, it is expected that the value of τMVC is reducing.The algorithm in ‘Decide Assistive Torque’ block is presented as follows:(i) A condition is set up to determine when human is fatigue. In this work,fatigue is identiﬁed when the maxmimum vountary contraction of thetorque is reducing up to 80 %.(ii) Once the joint fatigue is identiﬁed, an exoskeleton is sent torque sup-port to maintain human in desired position.if fatigue <= 0.8*τMVCthenAugust 1, 2017 16:34 ws-procs9x6-9x6 CLAWAR 2017-Proceedings Sec2-6p56 page 6060asstor = pidexohumantorque = asstor − fatigueelseasstor = pidexohumantorque = pidhuman(iii) To maintain the position of human shoulder joint, the value of asstor issent to an exoskeleton joint and humantorque is sent to human shoulderjoint.In the next section, the results and discussion of the experiment is pre-sented.Table 3. Parameters for (PID).Parameter Shoulder Joint Exoskeleton Joint (θ3)Proportional 10.0 10.0Integration 1.0 5.0Derivative 0.1 0.54. Result and DiscussionAs mentioned in Section (2), the parameters for P, I and D for humanshoulder were found by iteratively. The parameters are presented in Table(2). Fig. (3)(a) shows that human is able to maintain at desired positionbut, small oscillations occur at this joint. By looking at the oscillation inFig. (3)(a) and Fig.(3)(b), we could said that, the oscillation is actuallypresenting the fatigue condition. This also could be seen in Fig. 3(c). Asmentioned in Algorithm 1 of Section (3), fatigue is identiﬁed when the jointstrength is reached to 80% of the τMVC . Hence, the fatigue level is reducingbut, when it reached to 80% of the τMVC , it start to maintain at that value.As mentioned earlier in Section 3, the parameters for PID controller isobtained with a known tuning PID approach and is presented as in Table(3). For the integration system (Exoskeleton-Human), the PID parameterfor shoulder joint use the same values as in Table (2). These values werechosen to ensure that both system (human with joint fatigue model andexoskeleton-human model) are in the same condition. Hence, any changesthat occur could be compared.August 1, 2017 16:34 ws-procs9x6-9x6 CLAWAR 2017-Proceedings Sec2-6p56 page 6161Fig. 3. Results of human with fatigue model: (a) Desired and actual trajectory of human(b) torque of human (c) fatigue level.Fig. 4. Results of human fatigue with the existense of an exoskeleton: (a) Desiredand actual trajectory of exoskeleton and human (b) torque of exoskeleton and human(c) human fatigue level.Fig. (4)(a) shows the movement of human and an exoskeleton. The jointfatigue model is included in human model. As shown in Fig. (4)(a) whentime reached at approximately to 6.70 s, a small undershoot occur. Thereare two observations can be found here.First, after shoulder joint is reached to 90 degree, shoulder joint is ableto sustain at this trajectory approximately 3.70 s. A small undershoot occurat 6.70 s. At this point, it can be seen that shoulder joint is approaching atthe maximum point of fatigue level and thus, it moves downward. Fig.(4)(a)also shows that the exoskeleton is moving downward following the humanjoint (the black circle), but eventually, both human and exoskeleton weremoving to the desired trajectory back. From here, it shows that, exoskeletonis actually, supporting human to maintain at the desired point. Secondobservation is, human with an exoskeleton, took time to fatigue. This couldbe happened due to the support that is given by the exoskeleton from thebeginning of the motion.Fig.(4)(b) shows the torque required by the shoulder joint and exoskele-ton joint. As shown here, an exoskeleton has high torque compared to shoul-der joint, which shows that the exoskeleton is supporting the human upper-limb by providing an assistive torque. This could be seen clearly when thetime is extended to 300 s (Fig.(5)). An exoskeleton is providing an assistivetorque to ensure human could prolong doing the activities even tough, thestrength of human joint has reach to 0 Nm (Fig.(4)(c)).August 1, 2017 16:34 ws-procs9x6-9x6 CLAWAR 2017-Proceedings Sec2-6p56 page 6262Fig. 5. Torque for exoskeleton and human.5. ConclusionInvestigation into the impact of deploying an exoskleeton to compensatefor human muscle fatigue have been presented using a virtual environment.A mechanism for monitoring and assessment of muscle fatigue has beenpresented. The information thus gathered allows the exoskeleton controlto provide the required level of compensation to conteract the muscle fa-tigue. Future work will focus on incorporating fatigue compensation intothe cotroller and further assessment of fatigue and corresponding compen-sation at various levels.AcknowledgmentsS. K. Ali is on study leave and supported ﬁnancially by the Malaysia ofHigher Education (MOHE) and Universiti Putra Malaysia.References1. F. P. Bonnet V., Colledani F. and S. N., J. Industrial Ergonomics 44, 475(2014).2. C. B. Xu W. and R. E., J. Control Engineering Practice 31, 63 (2014).3. D. L. M. G. Carmichael and K. J. Waldron, Investigation of reducing fatigueand musculoskeletal disorder with passive actuators, in Proc. IEEE/RSJ Int.Conference on Intelligent Robots and Systems (MEMS’97), (Taipei, Taiwan,2010).4. B. F. Ma L., Chablat D. and Z. W., J. Industrial Ergonomics 39, 211 (2009).5. B. F. Z. W. Ma L., Chablat D. and G. F., J. Virtual and Physical Prototyping,1 (2010).6. M. R. Sakka S., Chablat D. and B. F., J. Human Factors Modelling andSimulation, 1 (2015).

Upper-limb exoskeleton for human muscle fatigue

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Upper-limb exoskeleton for human muscle fatigue

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