A Hardware-in-the-loop Simulation Study of a Mechatronic System for Anterior Cruciate Ligament Injuries Rehabilitation

Yepes, Juan C.; Saldarriaga, Alvaro J.; Velez, Jorge; Pérez, Vera Z.; Betancur, Manuel J.

doi:10.5220/0006252800690080

Cited by 5 publications

(4 citation statements)

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“…We require the robot to move in a certain way so that it allows us to excite the system and its dynamics to estimate the parameters or the human-robot torque. Therefore, we have used the Computed Torque Control (CTC) algorithm reported in previous works by Yepes et al [42,43].…”

Section: Control Algorithmmentioning

confidence: 99%

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Human-Robot Interaction Torque Estimation Methods for a Lower Limb Rehabilitation Robotic System with Uncertainties

et al. 2022

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Lower limb rehabilitation robot (LLRR) users, to successfully conduct isotonic exercises, require real-time feedback on the torque they exert on the robot to meet the goal of the treatment. Still, direct torque measuring is expensive, and indirect encoder-based estimation strategies, such as inverse dynamics (ID) and Nonlinear Disturbance Observers (NDO), are sensitive to Body Segment Inertial Parameters (BSIPs) uncertainties. We envision a way to minimize such parametric uncertainties. This paper proposes two human–robot interaction torque estimation methods: the Identified ID-based method (IID) and the Identified NDO-based method (INDO). Evaluating in simulation the proposal to apply, in each rehabilitation session, a sequential two-phase method: (1) An initial calibration phase will use an online parameter estimation to reduce sensitivity to BSIPs uncertainties. (2) The torque estimation phase uses the estimated parameters to obtain a better result. We conducted simulations under signal-to-noise ratio (SNR) = 40 dB and 20% BSIPs uncertainties. In addition, we compared the effectiveness with two of the best methods reported in the literature via simulation. Both proposed methods obtained the best Coefficient of Correlation, Mean Absolute Error, and Root Mean Squared Error compared to the benchmarks. Moreover, the IID and INDO fulfilled more than 72.2% and 88.9% of the requirements, respectively. In contrast, both methods reported in the literature only accomplish 27.8% and 33.3% of the requirements when using simulations under noise and BSIPs uncertainties. Therefore, this paper extends two methods reported in the literature and copes with BSIPs uncertainties without using additional sensors.

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Section: Control Algorithmmentioning

confidence: 99%

“…We have developed a lower limb rehabilitation robot (LLRR) called "Nukawa". This system has its antecedents in the LegSys system [42,[46][47][48]. Figure A1 presents the current version of the LLRR Nukawa.…”

Section: Appendix a Nukawamentioning

confidence: 99%

Human-Robot Interaction Torque Estimation Methods for a Lower Limb Rehabilitation Robotic System with Uncertainties

et al. 2022

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“…Exogames is integrated with the Nukawa lower limb rehabilitation robot (LLRR) [ 15 , 16 , 17 , 18 ], and together they constitute the overarching Kina system, see Figure 1 and Figure 2 .…”

Section: Introductionmentioning

confidence: 99%

“…The design consists of two limbs, each one composed of a three-link mechanism and an electronic position and force control, i.e., each leg has 3 degrees of freedom (3DOF). The design also has brushless DC motors, power drivers, and position sensors to perform a control strategy capable of generating multiple rehabilitation patterns [ 15 , 16 , 17 , 18 ]. When users are strapped into Nukawa , position sensors detect the angles of their joints as they interact with the Exogames virtual world, and the data are analyzed to generate reports and graphs based on their performance…”

Section: Introductionmentioning

confidence: 99%

Virtual Reality Game for Physical and Emotional Rehabilitation of Landmine Victims

Pérez

Yepes

Vargas

et al. 2022

Sensors

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Landmine victims require an engaging and immersive rehabilitation process to maintain motivation and therapeutic adherence, such as virtual reality games. This paper proposes a virtual reality exercise game called Exogames, which works with Nukawa, a lower limb rehabilitation robot (LLRR). Together, they constitute the general Kina system. The design and development process of Exogames is reported, as well as the evaluation of its potential for physical and emotional rehabilitation. In an initial survey designed ad-hoc, 13 health professionals evaluated compliance with various requirements. They agreed that Exogames would help the user focus on rehabilitation by providing motivation; 92.3% said that the user will feel safe in the virtual world, 66.7% of them agreed or totally agreed that it presents characteristics that may enhance the physical rehabilitation of lower limbs for amputees, 83.3% stated that it would promote the welfare of landmine victims, and 76.9% responded that the graphical interface and data report are useful for real-time assessment, and would be helpful for four interventional areas in all rehabilitation stages. In a second evaluation, using standardized surveys, five physical therapists and one lower limb amputee tried the Kina system as users. They filled out the System Usability Scale (SUS), the Physical Activity Enjoyment Scale (PACES), and the Game Experience Questionnaire (GEQ). The usability of the Kina system overall score was 69 (66, 79) out of 100, suggesting an acceptable though improvable usability. The overall PACES score of 110 (108, 112) out of 126 suggests that users enjoyed the game well. Finally, users indicated a positive effect with a good sense of immersion and smooth of gameplay during the tests, as indicated by the GEQ results. In summary, the evaluations showed that Exogames has the potential to be used as a virtual reality game for the physical and emotional rehabilitation of landmine victims.

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Evaluation plan of a mechatronic system for Anterior Cruciate Ligament rehabilitation

Portela

Zapata

Arango

et al. 2017

2017 IEEE 3rd Colombian Conference on Automatic Control (CCAC)

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A Hardware-in-the-loop Simulation Study of a Mechatronic System for Anterior Cruciate Ligament Injuries Rehabilitation

Cited by 5 publications

References 0 publications

Human-Robot Interaction Torque Estimation Methods for a Lower Limb Rehabilitation Robotic System with Uncertainties

Human-Robot Interaction Torque Estimation Methods for a Lower Limb Rehabilitation Robotic System with Uncertainties

Virtual Reality Game for Physical and Emotional Rehabilitation of Landmine Victims

Evaluation plan of a mechatronic system for Anterior Cruciate Ligament rehabilitation

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