@article{Kunavar2025,

title = {Influence of video gaming experience on motor adaptation during visuomotor and force field perturbations},

author = {Tjasa Kunavar and Niko Kroflic and Marko Jam\v{s}ek and Jan Babi\v{c}},

doi = {10.1016/j.heliyon.2025.e43109},

issn = {24058440},

year  = {2025},

date = {2025-01-01},

urldate = {2025-01-01},

journal = {Heliyon},

volume = {11},

issue = {10},

pages = {e43109},

abstract = {The capacity for quick and agile motor adaptations can be enhanced through related previous motor experience. This study explores the influence of prior long-term experience in playing action video games on the ability to adapt to novel motor beha viors. We compared motor adaptation between professional video game players, casual players who play video games on afrequent or infrequent basis, and non-gamers. Participants performed a tracking task where they had to adapt to novel visuomotor perturbation and an arm reaching task where they had to adapt to novel force field perturbation. Results showed that experience with action video games enhanced the process of adapting to novel complex visuomotor perturbation during a tracking task. On the other hand, the gaming experience had no effects on the process of adapting to force field perturbation during an arm reaching task. Since the tasks differ in the type of perturbation (and therefore the type of transformation needed for adaptation), the difficulty of perturbation, and the type of movement performed, the exact reason for the difference in the results should be further investigated. However, our results show that everyday experience with gaming can have an effect on the ability to adapt to certain types of novel motor behaviors. Our findings demonstrate the potential of everyday experiences in rehabilitation and training protocols, but highlight the need to consider the specific types of learning required.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Kunavar2024,

title = {The Effects of Different Motor Teaching Strategies on Learning a Complex Motor Task},

author = {Tjasa Kunavar and Marko Jam\v{s}ek and Edwin Johnatan Avila-Mireles and Elmar Rueckert and Luka Peternel and Jan Babi\v{c}},

doi = {10.3390/s24041231},

issn = {1424-8220},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

journal = {Sensors},

volume = {24},

issue = {4},

pages = {1231},

abstract = {During the learning of a new sensorimotor task, individuals are usually provided with instructional stimuli and relevant information about the target task. The inclusion of haptic devices in the study of this kind of learning has greatly helped in the understanding of how an individual can improve or acquire new skills. However, the way in which the information and stimuli are delivered has not been extensively explored. We have designed a challenging task with nonintuitive visuomotor perturbation that allows us to apply and compare different motor strategies to study the teaching process and to avoid the interference of previous knowledge present in the na\"{i}ve subjects. Three subject groups participated in our experiment, where the learning by repetition without assistance, learning by repetition with assistance, and task Segmentation Learning techniques were performed with a haptic robot. Our results show that all the groups were able to successfully complete the task and that the subjects’ performance during training and evaluation was not affected by modifying the teaching strategy. Nevertheless, our results indicate that the presented task design is useful for the study of sensorimotor teaching and that the presented metrics are suitable for exploring the evolution of the accuracy and precision during learning.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Design and Control of a Climbing Robot for Autonomous Vertical Gardening},

author = {Marko Jam\v{s}ek and Gal Sajko and Jurij Krpan and Jan Babi\v{c}},

doi = {10.3390/machines12020141},

issn = {2075-1702},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

journal = {Machines},

volume = {12},

issue = {2},

pages = {141},

abstract = {This paper focuses on the development of a novel climbing robot that is designed for autonomous maintenance of vertical gardens in urban environments. The robot, designed with a unique five-legged structure, is equipped with a range of electrical and mechanical components, enabling it to autonomously navigate and maintain a specially designed vertical garden wall facilitating interactive maintenance and growth monitoring. The motion planning and control of the robot were developed to ensure precise and adaptive movement across the vertical garden wall. Advanced algorithms were employed to manage the complex dynamics of the robot’s movements, optimizing its efficiency and effectiveness in navigating and maintaining the garden structure. The operation of the robot in maintaining the vertical garden was evaluated during a two-week trial where the robot successfully performed nearly 8000 leg movements, with only 0.6% requiring human intervention. This demonstrates a high level of autonomy and reliability. This study concludes that the pentapod robot demonstrates significant potential for automating the maintenance of vertical gardens, offering a promising tool for enhancing urban green spaces.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Kunavar2021,

title = {Effects of Local Gravity Compensation on Motor Control During Altered Environmental Gravity},

author = {Tja\v{s}a Kunavar and Marko Jam\v{s}ek and Marie Barbiero and Gunnar Blohm and Daichi Nozaki and Charalambos Papaxanthis and Olivier White and Jan Babi\v{c}},

url = {https://www.frontiersin.org/articles/10.3389/fncir.2021.750267/full},

doi = {10.3389/fncir.2021.750267},

issn = {1662-5110},

year  = {2021},

date = {2021-10-01},

urldate = {2021-10-01},

journal = {Frontiers in Neural Circuits},

volume = {15},

abstract = {Our sensorimotor control is well adapted to normogravity environment encountered on Earth and any change in gravity significantly disturbs our movement. In order to produce appropriate motor commands for aimed arm movements such as pointing or reaching, environmental changes have to be taken into account. This adaptation is crucial when performing successful movements during microgravity and hypergravity conditions. To mitigate the effects of changing gravitational levels, such as the changed movement duration and decreased accuracy, we explored the possible beneficial effects of gravity compensation on movement. Local gravity compensation was achieved using a motorized robotic device capable of applying precise forces to the subject's wrist that generated a normogravity equivalent torque at the shoulder joint during periods of microgravity and hypergravity. The efficiency of the local gravity compensation was assessed with an experiment in which participants performed a series of pointing movements toward the target on a screen during a parabolic flight. We compared movement duration, accuracy, movement trajectory, and muscle activations of movements during periods of microgravity and hypergravity with conditions when local gravity compensation was provided. The use of local gravity compensation at the arm mitigated the changes in movement duration, accuracy, and muscle activity. Our results suggest that the use of such an assistive device helps with movements during unfamiliar environmental gravity.},

keywords = {},

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 = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.3389/fncir.2021.750176,

title = {Effects of Simulated Microgravity and Hypergravity Conditions on Arm Movements in Normogravity},

author = {Marko Jam\v{s}ek and Tja\v{s}a Kunavar and Gunnar Blohm and Daichi Nozaki and Charalambos Papaxanthis and Olivier White and Jan Babi\v{c}},

url = {https://www.frontiersin.org/article/10.3389/fncir.2021.750176},

doi = {10.3389/fncir.2021.750176},

issn = {1662-5110},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {Frontiers in Neural Circuits},

volume = {15},

pages = {150},

abstract = {The human sensorimotor control has evolved in the Earth's environment where all movement is influenced by the gravitational force. Changes in this environmental force can severely impact the performance of arm movements which can be detrimental in completing certain tasks such as piloting or controlling complex vehicles. For this reason, subjects that are required to perform such tasks undergo extensive training procedures in order to minimize the chances of failure. We investigated whether local gravity simulation of altered gravitational conditions on the arm would lead to changes in kinematic parameters comparable to the full-body experience of microgravity and hypergravity onboard a parabolic flight. To see if this would be a feasible approach for on-ground training of arm reaching movements in altered gravity conditions we developed a robotic device that was able to apply forces at the wrist in order to simulate micro- or hypergravity conditions for the arm while subjects performed pointing movements on a touch screen. We analyzed and compared the results of several kinematic parameters along with muscle activity using this system with data of the same subjects being fully exposed to microgravity and hypergravity conditions on a parabolic flight. Both in our simulation and in-flight, we observed a significant increase in movement durations in microgravity conditions and increased velocities in hypergravity for upward movements. Additionally, we noted a reduced accuracy of pointing both in-flight and in our simulation. These promising results suggest, that locally simulated altered gravity can elicit similar changes in some movement characteristics for arm reaching movements. This could potentially be exploited as a means of developing devices such as exoskeletons to aid in training individuals prior to undertaking tasks in changed gravitational conditions.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Trost2021,

title = {A system to measure the human body asymmetries using accelerometers},

author = {Andrej Tro\v{s}t and Marko Jam\v{s}ek and Nejc \v{S}arabon and Jan Babi\v{c}},

url = {https://ev.fe.uni-lj.si/5-2021/Trost.pdf},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {Elektrotehniski Vestnik/Electrotechnical Review},

volume = {88},

number = {5},

pages = {267--272},

abstract = {In sports, acute and chronic injuries of athletes are common despite the growing knowledge and interest in the preventive activity in the sports practice. One of the main causes of injuries in athletes are their body asymmetries, which can only be dealt with if properly quantified. Despite the availability of several measuring systems, the majority of them do not allow segmental measurements and those that do are not portable. To solve the issue, a portable measuring system to measure the body asymmetries of the lower part of the human body was designed and manufactured. It measures and stores the data acquired by six accelerometers attached at the foot, tibia and pelvis of the human both legs. The system is compact, lightweight, portable and allowing a local data storage on the measuring device itself and triggering external signal to start the data acquisition. The system is driven by a sophisticated microcontroller that ensures data sampling at a high sampling rate. Results of a preliminary experimental system evaluation and validation are positive and encouraging for its further development and enhancement.},

keywords = {},

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 = {},

pubstate = {published},

tppubtype = {article}

}