@article{10792937,

title = {Comparison of Solo and Collaborative Trimanual Operation of a Supernumerary Limb in Tasks With Varying Physical Coupling},

author = {Jonathan Eden and Mahdi Khoramshahi and Yanpei Huang and Alexis Poignant and Etienne Burdet and Nathana\"{e}l Jarrass\'{e}},

doi = {10.1109/LRA.2024.3515734},

issn = {2377-3766},

year  = {2025},

date = {2025-02-01},

urldate = {2025-02-01},

journal = {IEEE Robotics and Automation Letters},

volume = {10},

number = {2},

pages = {860-867},

abstract = {Through the use of robotic supernumerary limbs, it has been proposed that a single user could perform tasks like surgery or industrial assembly that currently require a team. Although validation studies, often conducted in virtual reality, have demonstrated that individuals can learn to command supernumerary limbs, comparisons typically suggest that a team initially outperforms a supernumerary limb operating individual. In this study, we examined (i) the impact of using a commercially available physical robot setup instead of a virtual reality system and (ii) the effect of limb couplings on user performance during a series of trimanual operations. Contrary to previous findings, our results indicate no clear difference in user performance when working as a trimanual user, in the pick and place of three objects, compared to when working as a team. Additionally, for this task we observe that while users prefer working with a partner when they control most limbs, we find no clear difference in their preference between solo trimanual operation and when they work with a partner and control the third limb. These findings indicate that factors typically not present in virtual reality such as visual occlusion and haptic feedback may be vital to consider for the effective operation of supernumerary limbs, and provide initial evidence to support the viability of supernumerary limbs for a range of physical tasks.},

keywords = {Physical Human Robot Interaction},

pubstate = {published},

tppubtype = {article}

}

@article{dubois2024Short,

title = {Short term after-effects of small force fields applied by an upper-limb exoskeleton on inter-joint coordination},

author = {Oc\'{e}ane Dubois and Agn\`{e}s Roby-Brami and Ross Parry and Nathana\"{e}l Jarrass\'{e}},

doi = {10.1109/ICRA57147.2024.10610645},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

journal = {IEEE International Conference on Robotics and Automation},

pages = {959-965},

abstract = {Exoskeleton technologies have numerous potential applications, ranging from improving human motor skills to aiding individuals in their daily activities. While exoskeletons are increasingly viewed, for example, as promising tools in industrial ergonomics, the effect of using them on human motor control, particularly on inter-joint coordination, remains relatively uncharted. This paper investigates the effects of generic low-amplitude force fields applied by an exoskeleton on motor strategies in asymptomatic users. The force fields mimic common perturbations encountered in exoskeletons, such as residual friction, over/under-tuned assistance, or structural elasticity. Fifty-five participants performed reaching tasks while connected to an arm exoskeleton, experiencing one of five tested force fields. Their movements before and after exposure to the exoskeleton force field were compared. The study focuses both on spatial and temporal changes in coordination using specific metrics. The results reveal that even brief exposure to a low- amplitude force field, or to uncompensated residual friction and dynamic forces, applied at the joint level can alter the interjoint coordination, while task performance remains unaffected. The tested force fields induced varying degrees of changes in joint contributions and synchronization. This study highlights the importance of monitoring coordination changes to fully understand the impact of exoskeletons on human motor control and thus enable safe and widespread adoption of those devices.},

keywords = {Human Motor Control, Kinematics, Physical Human Robot Interaction},

pubstate = {published},

tppubtype = {article}

}

@article{dubois2024Identifying,

title = {Identifying individual characteristics influencing post-adaptation of motor behavior in upper-limb exoskeleton users},

author = {Oc\'{e}ane Dubois and Agn\`{e}s Roby-Brami and Ross Parry and Nathana\"{e}l Jarrass\'{e}},

doi = {10.1109/Humanoids58906.2024.10769945},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

journal = {IEEE-RAS International Conference on Humanoid Robots},

pages = {359-366},

abstract = {Over the past decade, industrial ergonomics have made significant advances, leading to the development of various occupational exoskeletons. While beneficial, exoskeletons could disrupt motor control due to their distributed interaction with the human body. This study explores individual factors influencing different adaptation patterns following exoskeleton use in asymptomatic individuals. Fifty-five participants used a 4 Degree of Freedom (DoF) arm exoskeleton to perform reaching tasks under low-magnitude force fields. Pre- and post-exposure movements were recorded via motion capture, and personal characteristics were documented. Spectral clustering identified variations in inter-joint coordination after exposition to the exoskeleton, and a random forest classifier linked these patterns to individual anthropometric, demographic and kinematic traits. The model highlighted factors such as laterality, forearm length, and some spontaneous kinematics metrics as key predictors of post-adaptation behavior. These findings underscore the need to consider individual profiles to minimize disruptive motor adaptations and improve exoskeleton safe widespread in industrial applications.},

keywords = {Human Motor Control, Physical Human Robot Interaction},

pubstate = {published},

tppubtype = {article}

}

@article{dezman2023,

title = {A mechatronic leg replica to benchmark human\textendashexoskeleton physical interactions},

author = {Miha De\v{z}man and Stefano Massardi and David Pinto-Fernandez and Victor Grosu and Carlos Rodriguez-Guerrero and Jan Babi\v{c} and Diego Torricelli},

doi = {10.1088/1748-3190/accda8},

issn = {1748-3182},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

journal = {Bioinspiration \& Biomimetics},

volume = {18},

issue = {3},

pages = {036009},

abstract = {Evaluating human\textendashexoskeleton interaction typically requires experiments with human subjects, which raises safety issues and entails time-consuming testing procedures. This paper presents a mechatronic replica of a human leg, which was designed to quantify physical interaction dynamics between exoskeletons and human limbs without the need for human testing. In the first part of this work, we present the mechanical, electronic, sensory system and software solutions integrated in our leg replica prototype. In the second part, we used the leg replica to test its interaction with two types of commercially available wearable devices, i.e. an active full leg exoskeleton and a passive knee orthosis. We ran basic test examples to demonstrate the functioning and benchmarking potential of the leg replica to assess the effects of joint misalignments on force transmission. The integrated force sensors embedded in the leg replica detected higher interaction forces in the misaligned scenario in comparison to the aligned one, in both active and passive modalities. The small standard deviation of force measurements across cycles demonstrates the potential of the leg replica as a standard test method for reproducible studies of human-exoskeleton physical interaction.},

keywords = {Exoskeleton Design and Control, Neuromusculoskeletal Modelling, Physical Human Robot Interaction, Robot Design},

pubstate = {published},

tppubtype = {article}

}

@article{Diaz2023b,

title = {Human-in-the-Loop Optimization of Wearable Robotic Devices to Improve Human\textendashRobot Interaction: A Systematic Review},

author = {Mar\'{i}a Alejandra D\'{i}az and Matthias Vo\ss and Arnau Dillen and Bruno Tassignon and Louis Flynn and Joost Geeroms and Romain Meeusen and Tom Verstraten and Jan Babi\v{c} and Philipp Beckerle and Kevin De Pauw},

url = {https://ieeexplore.ieee.org/document/9994612/},

doi = {10.1109/TCYB.2022.3224895},

issn = {2168-2267},

year  = {2023},

date = {2023-01-01},

urldate = {2023-01-01},

journal = {IEEE Transactions on Cybernetics},

volume = {53},

issue = {12},

pages = {7483-7496},

abstract = {This article presents a systematic review on wear- able robotic devices that use human-in-the-loop optimization (HILO) strategies to improve human\textendashrobot interaction. A total of 46 HILO studies were identified and divided into upper and lower limb robotic devices. The main aspects from HILO were iden- tified, reviewed, and classified in four areas: 1) human\textendashmachine systems; 2) optimization methods; 3) control strategies; and 4) experimental protocols. A variety of objective functions (phys- iological, biomechanical, and subjective), optimization strategies, and optimized control parameters configurations used in differ- ent control strategies are presented and analyzed. An overview of experimental protocols is provided, including metrics, tasks, and conditions tested. Moreover, the relevance given to train- ing or adaptation periods was explored. We outline an HILO framework that includes current wearable robots, optimization strategies, objective functions, control strategies, and experimen- tal protocols. We conclude by highlighting current research gaps and defining future directions to improve the development of advanced HILO strategies in upper and lower limb wearable robots.},

keywords = {Exoskeleton Design and Control, Human Performance Augmentation, Human-in-the-Loop Control, Physical Human Robot Interaction},

pubstate = {published},

tppubtype = {article}

}

@article{Latella2022,

title = {Analysis of Human Whole-Body Joint Torques During Overhead Work With a Passive Exoskeleton},

author = {Claudia Latella and Yeshasvi Tirupachuri and Luca Tagliapietra and Lorenzo Rapetti and Benjamin Schirrmeister and Jonas Bornmann and Dasa Gorjan and Jernej \v{C}amernik and Pauline Maurice and Lars Fritzsche and Jose Gonzalez-Vargas and Serena Ivaldi and Jan Babi\v{c} and Francesco Nori and Daniele Pucci},

url = {https://ieeexplore.ieee.org/document/9647004/},

doi = {10.1109/THMS.2021.3128892},

issn = {2168-2291},

year  = {2022},

date = {2022-10-01},

urldate = {2022-10-01},

journal = {IEEE Transactions on Human-Machine Systems},

volume = {52},

number = {5},

pages = {1060--1068},

publisher = {IEEE},

abstract = {Overheadwork is classifiedas one of the major risk factors for the onset of shoulder work-related musculoskeletal disorders and muscle fatigue. Upper-limb exoskeletons can be used to assist workers during the execution of industrial overhead tasks to prevent such disorders. Twelve novice participants have been equipped with inertial and force/torque sensors to simultaneously estimate the whole-body kinematics and the joint torques (i.e., internal articular stress) by means of a probabilistic estimator, while performing an overhead task with a pointing tool. An evaluation has been performed to analyze the effect at the whole-body level by considering the conditions of wearing and not-wearing PAEXO, a passive exoskeleton for upper-limb support during overhead work. Results point out that PAEXO provides a reduction of the whole-body joint effort across the experimental task blocks (from 66% to 86%). Moreover, the analysis along with five different body areas shows that 1) the exoskeleton provides support at the human shoulders by reducing the joint effort at the targeted limbs, and 2) that part of the internal wrenches is intuitively transferred from the upper body to the thighs and legs, which is shown with an increment of the torques at the legs joints. The promising outcomes show that the probabilistic estimation algorithm can be used as a validation metric to quantitatively assess PAEXO performances, paving thus the way for the next challenging milestone, such as the optimization of the human joint torques via adaptive exoskeleton control.},

keywords = {Ergonomy, Exoskeleton Design and Control, Human Performance Augmentation, Physical Human Robot Interaction},

pubstate = {published},

tppubtype = {article}

}

@article{Li2022,

title = {A review on interaction control for contact robots through intent detection},

author = {Yanan Li and Aran Sena and Ziwei Wang and Xueyan Xing and Jan Babi\v{c} and Edwin Asseldonk and Etienne Burdet},

url = {https://iopscience.iop.org/article/10.1088/2516-1091/ac8193},

doi = {10.1088/2516-1091/ac8193},

issn = {2516-1091},

year  = {2022},

date = {2022-07-01},

urldate = {2022-07-01},

journal = {Progress in Biomedical Engineering},

volume = {4},

number = {3},

pages = {032004},

abstract = {Interaction control presents opportunities for contact robots physically interacting with their human user, such as assistance targeted to each human user, communication of goals to enable effective teamwork, and task-directed motion resistance in physical training and rehabilitation contexts. Here we review the burgeoning field of interaction control in the control theory and machine learning communities, by analysing the exchange of haptic information between the robot and its human user, and how they share the task effort. We first review the estimation and learning methods to predict the human user intent with the large uncertainty, variability and noise and limited observation of human motion. Based on this motion intent core, typical interaction control strategies are described using a homotopy of shared control parameters. Recent methods of haptic communication and game theory are then presented to consider the co-adaptation of human and robot control and yield versatile interactive control as observed between humans. Finally, the limitations of the presented state of the art are discussed and directions for future research are outlined.},

keywords = {Human-in-the-Loop Control, Physical Human Robot Interaction},

pubstate = {published},

tppubtype = {article}

}

@article{Takahashi2022,

title = {Human Stiffness Perception and Learning in Interacting With Compliant Environments},

author = {Chie Takahashi and Morteza Azad and Vijaykumar Rajasekaran and Jan Babi\v{c} and Michael Mistry},

url = {https://www.frontiersin.org/articles/10.3389/fnins.2022.841901/full},

doi = {10.3389/fnins.2022.841901},

issn = {1662-453X},

year  = {2022},

date = {2022-06-01},

urldate = {2022-06-01},

journal = {Frontiers in Neuroscience},

volume = {16},

number = {June},

pages = {1--13},

abstract = {Humans are capable of adjusting their posture stably when interacting with a compliant surface. Their whole-body motion can be modulated in order to respond to the environment and reach to a stable state. In perceiving an uncertain external force, humans repetitively push it and learn how to produce a stable state. Research in human motor control has led to the hypothesis that the central nervous system integrates an internal model with sensory feedback in order to generate accurate movements. However, how the brain understands external force through exploration movements, and how humans accurately estimate a force from their experience of the force, is yet to be fully understood. To address these questions, we tested human behaviour in different stiffness profiles even though the force at the goal was the same. We generated one linear and two non-linear stiffness profiles, which required the same force at the target but different forces half-way to the target; we then measured the differences in the learning performance at the target and the differences in perception at the half-way point. Human subjects learned the stiffness profile through repetitive movements in reaching the target, and then indicated their estimation of half of the target value (position and force separately). This experimental design enabled us to probe how perception of the force experienced in different profiles affects the participants' estimations. We observed that the early parts of the learning curves were different for the three stiffness profiles. Secondly, the position estimates were accurate independent of the stiffness profile. The estimation in position was most likely influenced by the external environment rather than the profile itself. Interestingly, although visual information about the target had a large influence, we observed significant differences in accuracy of force estimation according to the stiffness profile.},

keywords = {Compliance and Impedance Control, Human Motor Control, Neuromusculoskeletal Modelling, Physical Human Robot Interaction, Sensorimotor Learning},

pubstate = {published},

tppubtype = {article}

}

@article{Jamsek2021,

title = {Predictive Exoskeleton Control for Arm-Motion Augmentation Based on Probabilistic Movement Primitives Combined With a Flow Controller},

author = {Marko Jam\v{s}ek and Tja\v{s}a Kunavar and Urban Bobek and Elmar Rueckert and Jan Babi\v{c}},

url = {https://ieeexplore.ieee.org/document/9387088/},

doi = {10.1109/LRA.2021.3068892},

issn = {2377-3766},

year  = {2021},

date = {2021-07-01},

urldate = {2021-07-01},

journal = {IEEE Robotics and Automation Letters},

volume = {6},

number = {3},

pages = {4417--4424},

abstract = {There are many work-related repetitive tasks where the application of exoskeletons could significantly reduce the physical effort by assisting the user in moving the arms towards the desired location in space. To make such controlmore user acceptable, the controller should be able to predict the motion of the user and act accordingly. This letter presents an exoskeleton control method that utilizes probabilistic movement primitives to generate predictions of user movements in real-time. These predictions are used in a flow controller, which represents a novel velocity-field-based exoskeleton control approach to provide assistance to the user in a predictive way. We evaluated our approach with a haptic robot, where a group of twelve participants had to perform movements towards different target locations in the frontal plane. We tested whether we could generalize the predictions for new and unknown target locations whilst providing assistance to the user without changing their kinematic parameters. The evaluation showed that we could accurately predict user movement intentions while at the same time significantly decrease the overall physical effort exerted by the participants to achieve the task.},

keywords = {Exoskeleton Design and Control, Force Control, Human Performance Augmentation, Optimal Control, Physical Human Robot Interaction},

pubstate = {published},

tppubtype = {article}

}

@article{Kim2021,

title = {A Human-Robot Collaboration Framework for Improving Ergonomics During Dexterous Operation of Power Tools},

author = {Wansoo Kim and Luka Peternel and Marta Lorenzini and Jan Babi\v{c} and Arash Ajoudani},

url = {https://linkinghub.elsevier.com/retrieve/pii/S0736584520302945},

doi = {10.1016/j.rcim.2020.102084},

issn = {07365845},

year  = {2021},

date = {2021-04-01},

journal = {Robotics and Computer-Integrated Manufacturing},

volume = {68},

pages = {102084},

abstract = {In this work, we present a novel control approach to human-robot collaboration that takes into account ergonomic aspects of the human co-worker during power tool operations. The method is primarily based on estimating and reducing the overloading torques in the human joints that are induced by the manipulated external load. The human overloading joint torques are estimated and monitored using a whole-body dynamic state model. The appropriate robot motion that brings the human into the suitable ergonomic working configuration is obtained by an optimisation method that minimises the overloading joint torques. The proposed optimisation process includes several constraints, such as the human arm muscular manipulability and safety of the collaborative task, to achieve a task-relevant optimised configuration. We validated the proposed method by a user study that involved a human-robot collaboration task, where the subjects operated a polishing machine on a part that was brought to them by the collaborative robot. A statistical analysis of ten subjects as an experimental evaluation of the proposed control framework is provided to demonstrate the potential of the proposed control framework in enabling ergonomic and task-optimised human-robot collaboration.},

keywords = {Ergonomy, Human Performance Augmentation, Human-in-the-Loop Control, Physical Human Robot Interaction},

pubstate = {published},

tppubtype = {article}

}

@article{Kozinc2021,

title = {Human pressure tolerance and effects of different padding materials with implications for development of exoskeletons and similar devices},

author = {\v{Z}iga Kozinc and Jan Babi\v{c} and Nejc \v{S}arabon},

doi = {10.1016/j.apergo.2021.103379},

issn = {18729126},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {Applied Ergonomics},

volume = {93},

abstract = {In this study, we assessed pressure tolerance in 16 healthy participants at the thigh, chest, and pelvic area, using different surfaces (1 cm2, 20 cm2 and different components, used in exoskeleton design), and the effects of different padding materials. Our results showed substantial variability in pressure tolerance among the participants, as well as lower pressure tolerance in females. Regarding the force applied with the exoskeleton components, male participants had higher discomfort threshold (230.3 ± 44.9 N compared to females (116.1 ± 24.6 N) in the chest area. For the applications with 20 cm2 surface, the males also showed higher pain threshold at the thigh (89.3 ± 41.8 N vs. 34.6 ± 27.2 N) and the pelvis (97.6 ± 37.0 N vs. 56.1 ± 29.5 N). All padding materials increased pressure tolerance for 10\textendash38% (p \< 0.001), but little differences between materials were observed.},

keywords = {Ergonomy, Exoskeleton Design and Control, Physical Human Robot Interaction},

pubstate = {published},

tppubtype = {article}

}

@article{Fritzsche2021,

title = {Assessing the efficiency of exoskeletons in physical strain reduction by biomechanical simulation with AnyBody Modeling System},

author = {Lars Fritzsche and Pavel E. Galibarov and Christian Gartner and Jonas Bornmann and Michael Damsgaard and Rudolf Wall and Benjamin Schirrmeister and Jose Gonzalez-Vargas and Daniele Pucci and Pauline Maurice and Serena Ivaldi and Jan Babi\v{c}},

doi = {10.1017/wtc.2021.5},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {Wearable Technologies},

volume = {2},

abstract = {IntroductionRecently, many industrial exoskeletons for supporting workers in heavy physical tasks have been developed. However, the efficiency of exoskeletons with regard to physical strain reduction has not been fully proved, yet. Several laboratory and field studies have been conducted, but still more data, that cannot be obtained solely by behavioral experiments, are needed to investigate effects on the human body.MethodsThis paper presents an approach to extend laboratory and field research with biomechanical simulations using the AnyBody Modeling System. Based on a dataset recorded in a laboratory experiment with 12 participants using the exoskeleton Paexo Shoulder in an overhead task, the same situation was reproduced in a virtual environment and analyzed with biomechanical simulation.ResultsSimulation results indicate that the exoskeleton substantially reduces muscle activity and joint reaction forces in relevant body areas. Deltoid muscle activity and glenohumeral joint forces in the shoulder were decreased between 54 and 87%. Simultanously, no increases of muscle activity and forces in other body areas were observed.DiscussionThis study demonstrates how a simulation framework could be used to evaluate changes in internal body loads as a result of wearing exoskeletons. Biomechanical simulation results widely agree with experimental measurements in the previous laboratory experiment and supplement such by providing an insight into effects on the human musculoskeletal system. They confirm that Paexo Shoulder is an effective device to reduce physical strain in overhead tasks. The framework can be extended with further parameters, allowing investigations for product design and evaluation.},

keywords = {Ergonomy, Exoskeleton Design and Control, Human Performance Augmentation, Neuromusculoskeletal Modelling, Physical Human Robot Interaction},

pubstate = {published},

tppubtype = {article}

}

@article{Jamsek2020,

title = {Gaussian Mixture Models for Control of Quasi-Passive Spinal Exoskeletons},

author = {Marko Jam\v{s}ek and Tadej Petri\v{c} and Jan Babi\v{c}},

url = {https://www.mdpi.com/711802 https://www.mdpi.com/1424-8220/20/9/2705},

doi = {10.3390/s20092705},

issn = {1424-8220},

year  = {2020},

date = {2020-05-01},

urldate = {2020-05-01},

journal = {Sensors},

volume = {20},

number = {9},

pages = {2705},

publisher = {Multidisciplinary Digital Publishing Institute},

abstract = {Research and development of active and passive exoskeletons for preventing work related injuries has steadily increased in the last decade. Recently, new types of quasi-passive designs have been emerging. These exoskeletons use passive viscoelastic elements, such as springs and dampers, to provide support to the user, while using small actuators only to change the level of support or to disengage the passive elements. Control of such devices is still largely unexplored, especially the algorithms that predict the movement of the user, to take maximum advantage of the passive viscoelastic elements. To address this issue, we developed a new control scheme consisting of Gaussian mixture models (GMM) in combination with a state machine controller to identify and classify the movement of the user as early as possible and thus provide a timely control output for the quasi-passive spinal exoskeleton. In a leave-one-out cross-validation procedure, the overall accuracy for providing support to the user was 86 . 72 ± 0 . 86 % (mean ± s.d.) with a sensitivity and specificity of 97 . 46 ± 2 . 09 % and 83 . 15 ± 0 . 85 % respectively. The results of this study indicate that our approach is a promising tool for the control of quasi-passive spinal exoskeletons.},

keywords = {Exoskeleton Design and Control, Physical Human Robot Interaction},

pubstate = {published},

tppubtype = {article}

}

@article{Ugurlu2020,

title = {Active Compliance Control Reduces Upper Body Effort in Exoskeleton-Supported Walking},

author = {Barkan Ugurlu and Hironori Oshima and Emre Sariyildiz and Tatsuo Narikiyo and Jan Babi\v{c}},

url = {https://ieeexplore.ieee.org/document/8960446/},

doi = {10.1109/THMS.2019.2961969},

issn = {2168-2291},

year  = {2020},

date = {2020-04-01},

journal = {IEEE Transactions on Human-Machine Systems},

volume = {50},

number = {2},

pages = {144--153},

abstract = {This article presents a locomotion controller for lower limb exoskeletons so as to enable the combined robot and user system to exhibit compliant walking characteristics when interacting with the environment. This is of critical importance to reduce the excessive ground reaction forces during the walking task execution with the aim of improved environmental interaction capabilities. In robot-aided walking support for paraplegics, the user has to actively use his/her upper limbs via crutches to ensure overall balance. By virtue of this requisite, several issues may particularly arise during touchdown instants, e.g., upper body orientation fluctuates, shoulder joints are subject to excessive loading, and arms may need to exert extra forces to counterbalance these effects. In order to reduce the upper body effort via compliant locomotion, the controller is designed to manage the force/position tradeoff by using an admittance controller in each joint. For proof of concept, a series of exoskeleton-aided walking experiments were conducted with the participation of nine healthy volunteers, four of whom additionally walked on an irregular surface for further performance evaluation. The results suggest that the proposed locomotion controller is advantageous over conventional high-gain position tracking in decreasing undesired oscillatory torso motion and total arm force, adequately reducing the required upper body effort.},

keywords = {Compliance and Impedance Control, Exoskeleton Design and Control, Physical Human Robot Interaction, Postural Balance},

pubstate = {published},

tppubtype = {article}

}

@article{Rodriguez-Guerrero2020,

title = {Wearable Robots: Taking a Leap From the Lab to the Real World [From the Guest Editors]},

author = {Carlos Rodriguez-Guerrero and Jan Babi\v{c} and Domen Novak},

url = {https://ieeexplore.ieee.org/document/9040485/},

doi = {10.1109/MRA.2020.2967004},

issn = {1070-9932},

year  = {2020},

date = {2020-03-01},

journal = {IEEE Robotics \& Automation Magazine},

volume = {27},

number = {1},

pages = {20--21},

abstract = {The articles present a mix of mechanical design, control algorithms, and human-subject evaluations, thus providing insights into all aspects of wearable robotics for a varied engineering audience.},

keywords = {Exoskeleton Design and Control, Physical Human Robot Interaction},

pubstate = {published},

tppubtype = {article}

}

@article{Baltrusch2020,

title = {SPEXOR passive spinal exoskeleton decreases metabolic cost during symmetric repetitive lifting},

author = {Saskia J Baltrusch and Jaap H van Dieen and Axel S Koopman and Matthias Naf and Carlos Rodriguez-Guerrero and Jan Babi\v{c} and Han Houdijk},

url = {http://link.springer.com/10.1007/s00421-019-04284-6},

doi = {10.1007/s00421-019-04284-6},

issn = {1439-6319},

year  = {2020},

date = {2020-02-01},

journal = {European Journal of Applied Physiology},

volume = {120},

number = {2},

pages = {401--412},

abstract = {Besides mechanical loading of the back, physiological strain is an important risk factor for low-back pain. Recently a passive exoskeleton (SPEXOR) has been developed to reduce loading on the low back. We aimed to assess the effect of this device on metabolic cost of repetitive lifting. To explain potential effects, we assessed kinematics, mechanical joint work, and back muscle activity. We recruited ten male employees, working in the luggage handling department of an airline company and having ample experience with lifting tasks at work. Metabolic cost, kinematics, mechanical joint work and muscle activity were measured during a 5-min repetitive lifting task. Participants had to lift and lower a box of 10 kg from ankle height with and without the exoskeleton. Metabolic cost was significantly reduced by 18 % when wearing the exoskeleton. Kinematics did not change significantly, while muscle activity decreased by up to 16 %. The exoskeleton took over 18\textendash25 % of joint work at the hip and L5S1 joints. However, due to large variation in individual responses, we did not find a significant reduction of joint work around the individual joints. Wearing the SPEXOR exoskeleton decreased metabolic cost and might, therefore, reduce fatigue development and contribute to prevention of low-back pain during repetitive lifting tasks. Reduced metabolic cost can be explained by the exoskeleton substituting part of muscle work at the hip and L5S1 joints and consequently decreasing required back muscle activity.},

keywords = {Ergonomy, Exoskeleton Design and Control, Physical Human Robot Interaction},

pubstate = {published},

tppubtype = {article}

}

@article{Maurice2020b,

title = {Objective and Subjective Effects of a Passive Exoskeleton on Overhead Work},

author = {Pauline Maurice and Jernej \v{C}amernik and Da\v{s}a Gorjan and Benjamin Schirrmeister and Jonas Bornmann and Luca Tagliapietra and Claudia Latella and Daniele Pucci and Lars Fritzsche and Serena Ivaldi and Jan Babi\v{c}},

url = {https://ieeexplore.ieee.org/document/8856265/},

doi = {10.1109/TNSRE.2019.2945368},

issn = {1534-4320},

year  = {2020},

date = {2020-01-01},

journal = {IEEE Transactions on Neural Systems and Rehabilitation Engineering},

volume = {28},

number = {1},

pages = {152--164},

address = {Nancy},

abstract = {Overhead work is a frequent cause of shoulder work-related musculoskeletal disorders. Exoskeletons offering arm support have the potential to reduce shoulder strain, without requiring large scale reorganization of the workspace. Assessment of such systems however requires to take multiple factors into consideration. This paper presents a thorough in-lab assessment of PAEXO, a novel passive exoskeleton for arm support during overhead work. A list of evaluation criteria and associated performance metrics is proposed to cover both objective and subjective effects of the exoskeleton, on the user and on the task being performed. These metrics are measured during a lab study, where 12 participants perform an overhead pointing task with and without the exoskeleton, while their physical, physiological and psychological states are monitored. Results show that using PAEXO reduces shoulder physical strain as well as global physiological strain, without increasing low back strain nor degrading balance. These positive effects are achieved without degrading task performance. Importantly, participants' opinions of PAEXO are positive, in agreement with the objective measures. Thus, PAEXO seems a promising solution to help prevent shoulder injuries and diseases among overhead workers, without negatively impacting productivity.},

keywords = {Ergonomy, Exoskeleton Design and Control, Kinematics, Physical Human Robot Interaction, Postural Balance},

pubstate = {published},

tppubtype = {article}

}

@article{Maurice2019a,

title = {Evaluation of PAEXO, a novel passive exoskeleton for overhead work},

author = {Pauline Maurice and Jernej \v{C}amernik and Da\v{s}a Gorjan and Benjamin Schirrmeister and Jonas Bornmann and Luca Tagliapietra and Claudia Latella and Danielle Pucci and Lars Fritzsche and Serena Ivaldi and Jan Babi\v{c}},

url = {https://doi.org/10.1080/10255842.2020.1714977 https://www.tandfonline.com/doi/full/10.1080/10255842.2020.1714977},

doi = {10.1080/10255842.2020.1714977},

issn = {1025-5842},

year  = {2019},

date = {2019-10-01},

journal = {Computer Methods in Biomechanics and Biomedical Engineering},

volume = {22},

number = {sup1},

pages = {S448--S450},

publisher = {Taylor \& Francis},

abstract = {Assessment of physical, physiological, and psycho-logical aspects in the lab study suggest that PAEXO is a promising solution to reduce shoulder WMSDs among overhead workers. An inverse dynamics ana- lysis is being conducted to estimate joint torques from whole-body kinematics and ground reaction force to complement the present assessment. Data collected during field-testing with industrial workers are currently analyzed to evaluate the impact of PAEXO on real end-users.},

keywords = {Ergonomy, Exoskeleton Design and Control, Physical Human Robot Interaction},

pubstate = {published},

tppubtype = {article}

}

@article{Romano2018,

title = {The CoDyCo Project Achievements and Beyond: Toward Human Aware Whole-Body Controllers for Physical Human Robot Interaction},

author = {Francesco Romano and Gabriele Nava and Morteza Azad and Jernej Camernik and Stefano Dafarra and Oriane Dermy and Claudia Latella and Maria Lazzaroni and Ryan Lober and Marta Lorenzini and Daniele Pucci and Olivier Sigaud and Silvio Traversaro and Jan Babi\v{c} and Serena Ivaldi and Michael Mistry and Vincent Padois and Francesco Nori},

url = {http://ieeexplore.ieee.org/document/8093992/},

doi = {10.1109/LRA.2017.2768126},

issn = {2377-3766},

year  = {2018},

date = {2018-01-01},

journal = {IEEE Robotics and Automation Letters},

volume = {3},

number = {1},

pages = {516--523},

abstract = {The success of robots in real-world environments is largely dependent on their ability to interact with both humans and said environment.The FP7 EU project CoDyCo focused on the latter of these two challenges by exploiting both rigid and compliant contacts dynamics in the robot control problem. Regarding the former, to properly manage interaction dynamics on the robot control side, an estimation of the human behaviors and intentions is necessary. In this letter, we present the building blocks of such a human-in-the-loop controller, and validate them in both simulation and on the iCub humanoid robot using a human\textendashrobot interaction scenario. In this scenario, a human assists the robot in standing up from being seated on a bench.},

keywords = {Compliance and Impedance Control, Physical Human Robot Interaction},

pubstate = {published},

tppubtype = {article}

}

@article{Padois2017,

title = {Whole-body multi-contact motion in humans and humanoids: Advances of the CoDyCo European project},

author = {Vincent Padois and Serena Ivaldi and Jan Babi\v{c} and Michael Mistry and Jan Peters and Francesco Nori},

url = {http://linkinghub.elsevier.com/retrieve/pii/S0921889016304845},

doi = {10.1016/j.robot.2016.08.017},

issn = {09218890},

year  = {2017},

date = {2017-01-01},

journal = {Robotics and Autonomous Systems},

volume = {90},

pages = {97--117},

abstract = {Traditional industrial applications involve robots with limited mobility. Consequently, interaction (e.g. manipulation) was treated separately from whole-body posture (e.g. balancing), assuming the robot firmly connected to the ground. Foreseen applications involve robots with augmented autonomy and physical mobility. Within this novel context, physical interaction influences stability and balance. To allow robots to surpass barriers between interaction and posture control, forthcoming robotic research needs to investigate the principles governing whole-body motion and coordination with contact dynamics. There is a need to investigate the principles of motion and coordination of physical interaction, including the aspects related to unpredictability. Recent developments in compliant actuation and touch sensing allow safe and robust physical interaction from unexpected contact including humans. The next advancement for cognitive robots, however, is the ability not only to cope with unpredictable contact, but also to exploit predictable contact in ways that will assist in goal achievement. Last but not least, theoretical results needs to be validated in real-world scenarios with humanoid robots engaged in whole-body goal-directed tasks. Robots should be capable of exploiting rigid supportive contacts, learning to compensate for compliant contacts, and utilising assistive physical interaction from humans. The work presented in this paper presents state-of-the-art in these domains as well as some recent advances made within the framework of the CoDyCo European project.},

keywords = {Compliance and Impedance Control, Physical Human Robot Interaction},

pubstate = {published},

tppubtype = {article}

}

@article{Avila-Mireles2017b,

title = {Skill learning and skill transfer mediated by cooperative haptic interaction},

author = {Edwin Johnatan Avila-Mireles and Jacopo Zenzeri and Valentina Squeri and Pietro Morasso and Dalia {De Santis}},

url = {https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7921690; volume = 25},

doi = {10.1109/TNSRE.2017.2700839},

issn = {15344320},

year  = {2017},

date = {2017-01-01},

journal = {IEEE Transactions on Neural Systems and Rehabilitation Engineering},

number = {7},

pages = {832-843},

abstract = {It is known that physical coupling between two subjects may be advantageous in joint tasks. However, little is known about how two people mutually exchange information to exploit the coupling. Therefore we adopted a reversed, novel perspective to the standard one that focuses on the ability of physically coupled subjects to adapt to cooperative contexts that require negotiating a common plan: we investigated how training in pairs on a novel task affects the development of motor skills of each of the interacting partners. The task involved reaching movements in an unstable dynamic environment using a bilateral non-linear elastic tool that could be used bimanually or dyadically. The main result is that training with an expert leads to the greatest performance in the joint task. However, the performance in the individual test is strongly affected by the initial skill level of the partner. Moreover, practicing with a peer rather than an expert appears to be more advantageous for a naive; and motor skills can be transferred to a bimanual context, after training with an expert, only if the non-expert subject had prior experience of the dynamics of the novel task.},

keywords = {Human Motor Control, Physical Human Robot Interaction, Sensorimotor Learning},

pubstate = {published},

tppubtype = {article}

}

@article{Avila-Mireles2016h,

title = {Skill transfer and generalization after robot - mediated dyadic training},

author = {Edwin Johnatan Avila-Mireles and Dalia {De Santis} and Valentina Squeri and Pietro Morasso and Jacopo Zenzeri},

year  = {2016},

date = {2016-01-01},

journal = {Human Friendly Robotics},

number = {Human - Robot Interaction},

pages = {1-6},

abstract = {Several studies have investigated how the interaction between two people or between a person and a robot can be harnessed to improve the skills of the partners. Indeed, solving a task as a dyad can lead the individual to perform better than by himself. The goal of this work is to investigate how the skill level of the partner and different interactive conditions affect learning of a novel task. In particular we considered the case of partners with different initial skill level (na\"{i}ve or experts) and the influence of prior individual practice. Twenty two subjects trained in a joint stabilization task for 4 days. On the last day we tested their ability to perform the same task individually. The results show that training with a skilled partner, despite bringing to a faster learning in the joint task, does not facilitate skill transfer in the absence of individual prior practice. This suggests that the physical coupling with an expert partner may interfere with learning due to the formation of a non-veridical internal representation of the task},

keywords = {Human Motor Control, Physical Human Robot Interaction, Sensorimotor Learning},

pubstate = {published},

tppubtype = {article}

}

@article{Avila-Mireles2016g,

title = {Transferring knowledge during dyadic interaction: The role of the expert in the learning process},

author = {Edwin Johnatan Avila-Mireles and Dalia {De Santis} and Pietro Morasso and Jacopo Zenzeri},

url = {https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=\&arnumber=7591154},

doi = {10.1109/EMBC.2016.7591154},

issn = {1557170X},

year  = {2016},

date = {2016-01-01},

journal = {Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS},

volume = {2016-Octob},

pages = {2149-2152},

abstract = {Physical interaction between man and machines is increasing the interest of the research as well as the industrial community. It is known that physical coupling between active persons can be beneficial and increase the performance of the dyad compared to an individual. However, the factors that may result in performance benefits are still poorly understood. The aim of this work is to investigate how the different initial skill levels of the interacting partners influence the learning of a stabilization task. Twelve subjects, divided in two groups, trained in couples in a joint stabilization task. In the first group the couples were composed of two naive, while in the second a naive was trained together with an expert. Results show that training with an expert results in the greatest performance in the joint task. However, this benefit is not transferred to the individual when performing the same task bimanually.},

keywords = {Human Motor Control, Physical Human Robot Interaction, Sensorimotor Learning},

pubstate = {published},

tppubtype = {article}

}

@article{DeSantis2015a,

title = {Dealing with instability in bimanual and collaborative tasks},

author = {Dalia {De Santis} and Edwin Johnatan Avila-Mireles and Valentina Squeri and Pietro Morasso and Jacopo Zenzeri},

url = {https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=\&arnumber=7318635},

doi = {10.1109/EMBC.2015.7318635},

issn = {1557170X},

year  = {2015},

date = {2015-01-01},

journal = {Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS},

volume = {2015-Novem},

number = {i},

pages = {1417-1420},

publisher = {IEEE},

abstract = {In the context of unstable tasks, whenever the dynamics of the interaction are unknown, our ability to control an object depends on the predictability of the sensory feedback generated from the physical coupling at the interface with the object. In the case of physical human-human interaction, the haptic sensory feedback plays a primary role in the construction of a shared motor plan, being the channel for the mutual sharing of intentions. The present work addresses the issue of strategy selection in contexts in which instability is arising both from the environment, i.e. controlling a compliant object subject to nonlinear forces, and from the interaction with a partner, i.e. carrying out a bimanual balancing task in the presence of disturbing force-fields.},

keywords = {Human Motor Control, Physical Human Robot Interaction, Sensorimotor Learning},

pubstate = {published},

tppubtype = {article}

}

@article{Avila-Mireles2015a,

title = {Haptically Induced EMG Patterns for Upper Limb Neuromuscular Evaluation},

author = {Edwin Johnatan Avila-Mireles and Francisco J Ruiz-s\'{a}nchez},

year  = {2015},

date = {2015-01-01},

urldate = {2015-01-01},

journal = {Proceedings of 17th International Conference of the Engineering in Medicine and Biology Society},

volume = {43},

pages = {2012},

abstract = {In this paper, we present the upper-limb sEMG signals induced by a kinesthetic stimulation, provided by a haptic device in a guiding mode, with cyclic movements on the transverse plane. We show the existence of common patterns of muscular activation in healthy volunteers describing the desired sequence of signals to produce an appropriated and coordinated movement. These patterns introduce physiological information about the etiology of the movement, and a mean to improve the assessment of the neuromuscular state in a patient.},

keywords = {Physical Human Robot Interaction, Sensorimotor Learning},

pubstate = {published},

tppubtype = {article}

}

@article{Avila-Mireles2015b,

title = {Motor control strategies in the bimanual stabilization of an unstable virtual tool},

author = {Edwin Johnatan Avila-Mireles and Dalia {De Santis} and Valentina Squeri and Pietro Morasso and Jacopo Zenzeri},

url = {https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=\&arnumber=7319140},

doi = {10.1109/EMBC.2015.7319140},

issn = {1557170X},

year  = {2015},

date = {2015-01-01},

urldate = {2015-01-01},

journal = {Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS},

volume = {2015-Novem},

pages = {3472-3475},

abstract = {Previous works have shown that, when dealing with instabilities in a bimanual manipulation paradigm, humans modulate the stiffness of the arms according to feedforward or feedback mechanisms as a function of the dynamics of the task. The aim of this work is to complement these results getting insights on how the CNS controls the muscles to achieve the stabilization goal in the two aforementioned control strategies. Surface EMG was recorded from 13 muscles of each arm and trunk while three expert subjects performed bimanual balancing of a virtual underactuated tool immersed in an unstable force-field. Results suggest the existence of an intermittent muscle ensemble recruitment that follows two distinct activation patterns, namely synchronous co-contractions and independent activations. The observed EMG patterns were independent of the motor control strategy applied in the task. These findings therefore suggest the existence of separate control strategies for the tool stabilization and the control of hand movements at the muscular level during a bimanual postural task.},

keywords = {Human Motor Control, Physical Human Robot Interaction, Sensorimotor Learning},

pubstate = {published},

tppubtype = {article}

}

@article{Peternel2013b,

title = {Learning of compliant human\textendashrobot interaction using full-body haptic interface},

author = {Luka Peternel and Jan Babi\v{c}},

url = {http://www.tandfonline.com/doi/abs/10.1080/01691864.2013.808305},

doi = {10.1080/01691864.2013.808305},

issn = {0169-1864},

year  = {2013},

date = {2013-09-01},

journal = {Advanced Robotics},

volume = {27},

number = {13},

pages = {1003--1012},

publisher = {Taylor \& Francis},

abstract = {We present a novel approach where a human demonstrator can intuitively teach robot full-body skills. The aim of this approach is to exploit human sensorimotor ability to learn how to operate a humanoid robot in real time to perform tasks involving interaction with the environment. The human skill is then used to design a controller to autonomously control the robot. To provide the demonstrator with the robot?s state suitable for the full-body motion control, we developed a novel method that transforms robot?s sensory readings into feedback appropriate for the human. This method was implemented through a haptic interface that was designed to exert forces on the demonstrator?s centre of mass corresponding to the state of the robot?s centre of mass. To evaluate the feasibility of this approach, we performed an experiment where the human demonstrator taught the robot how to compliantly interact with another human. The results of the experiment showed that the proposed approach allowed the human to intuitively teach the robot how to compliantly interact with a human. We present a novel approach where a human demonstrator can intuitively teach robot full-body skills. The aim of this approach is to exploit human sensorimotor ability to learn how to operate a humanoid robot in real time to perform tasks involving interaction with the environment. The human skill is then used to design a controller to autonomously control the robot. To provide the demonstrator with the robot?s state suitable for the full-body motion control, we developed a novel method that transforms robot?s sensory readings into feedback appropriate for the human. This method was implemented through a haptic interface that was designed to exert forces on the demonstrator?s centre of mass corresponding to the state of the robot?s centre of mass. To evaluate the feasibility of this approach, we performed an experiment where the human demonstrator taught the robot how to compliantly interact with another human. The results of the experiment showed that the proposed approach allowed the human to intuitively teach the robot how to compliantly interact with a human.},

keywords = {Compliance and Impedance Control, Human-in-the-Loop Control, Physical Human Robot Interaction},

pubstate = {published},

tppubtype = {article}

}