Marko Jamšek
Postdoc
Email: marko.jamsek@ijs.si
Education
PhD in Robotics, Jožef Stefan International Postgraduate School (2022)
MSc in Mechatronics and Laser Technology, University of Ljubljana (2017)
BSc in Mechanical Engineering, University of Ljubljana (2014)
Research Interests
- exoskeletons
- human-robot interaction
- human movement prediction
Selected publications
Kunavar, Tjaša; Jamšek, Marko; Barbiero, Marie; Blohm, Gunnar; Nozaki, Daichi; Papaxanthis, Charalambos; White, Olivier; Babič, Jan
Effects of Local Gravity Compensation on Motor Control During Altered Environmental Gravity Journal Article
In: Frontiers in Neural Circuits, vol. 15, 2021, ISSN: 1662-5110.
@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.},
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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.
Jamšek, Marko; Kunavar, Tjaša; Bobek, Urban; Rueckert, Elmar; Babič, Jan
Predictive Exoskeleton Control for Arm-Motion Augmentation Based on Probabilistic Movement Primitives Combined With a Flow Controller Journal Article
In: IEEE Robotics and Automation Letters, vol. 6, no. 3, pp. 4417–4424, 2021, ISSN: 2377-3766.
@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.},
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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.
Petrič, Tadej; Jamšek, Marko; Babič, Jan
Exoskeleton Control Based on Network of Stable Heteroclinic Channels (SHC) Combined with Gaussian Mixture Models (GMM) Proceedings Article
In: Lenarčič, Jadran; Siciliano, Bruno (Ed.): Advances in Robot Kinematics 2020, pp. 341–348, Springer International Publishing, Cham, 2021, ISBN: 978-3-030-50975-0.
@inproceedings{Petric2020c,
title = {Exoskeleton Control Based on Network of Stable Heteroclinic Channels (SHC) Combined with Gaussian Mixture Models (GMM)},
author = {Tadej Petri\v{c} and Marko Jam\v{s}ek and Jan Babi\v{c}},
editor = {Jadran Lenar\v{c}i\v{c} and Bruno Siciliano},
url = {http://link.springer.com/10.1007/978-3-030-50975-0_42},
isbn = {978-3-030-50975-0},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
booktitle = {Advances in Robot Kinematics 2020},
pages = {341--348},
publisher = {Springer International Publishing},
address = {Cham},
abstract = {One of the major causes of disability and sick day leaves is lower back pain. Hence it can result in a decreased life quality and lower industrial productivity. One of the possible solutions to lower back pain could be the use of exoskeletons, which would reduce the spinal loading. One of such solutions is a quasi-passive spinal exoskeleton that engages and disengages the passive support depending on the movements performed by the user. This enables the spinal support for the user when lifting a heavy load and for all other tasks, the user motion is unobstructed. To achieve autonomous clutch activation, the main challenge is to properly classify the beginning of each motion. In this paper, we proposed a novel control method that uses Gaussian Mixture Models (GMM) for movement classifiers and a network of Stable Heteroclinic Channels (SHC) for designing a phase-state-machine. Integrating GMM into the SHC network enables a fast and reliable control of the clutch mechanism of the quasi-passive spinal exoskeleton. The control system capabilities were demonstrated in an experiment with a male subject wearing the quasi-passive exoskeleton while executing three different movements representative for an industrial working environment: walking, standing, and lifting.},
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One of the major causes of disability and sick day leaves is lower back pain. Hence it can result in a decreased life quality and lower industrial productivity. One of the possible solutions to lower back pain could be the use of exoskeletons, which would reduce the spinal loading. One of such solutions is a quasi-passive spinal exoskeleton that engages and disengages the passive support depending on the movements performed by the user. This enables the spinal support for the user when lifting a heavy load and for all other tasks, the user motion is unobstructed. To achieve autonomous clutch activation, the main challenge is to properly classify the beginning of each motion. In this paper, we proposed a novel control method that uses Gaussian Mixture Models (GMM) for movement classifiers and a network of Stable Heteroclinic Channels (SHC) for designing a phase-state-machine. Integrating GMM into the SHC network enables a fast and reliable control of the clutch mechanism of the quasi-passive spinal exoskeleton. The control system capabilities were demonstrated in an experiment with a male subject wearing the quasi-passive exoskeleton while executing three different movements representative for an industrial working environment: walking, standing, and lifting.
Jamšek, Marko; Kunavar, Tjaša; Blohm, Gunnar; Nozaki, Daichi; Papaxanthis, Charalambos; White, Olivier; Babič, Jan
Effects of Simulated Microgravity and Hypergravity Conditions on Arm Movements in Normogravity Journal Article
In: Frontiers in Neural Circuits, vol. 15, pp. 150, 2021, ISSN: 1662-5110.
@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.},
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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.
Trošt, Andrej; Jamšek, Marko; Šarabon, Nejc; Babič, Jan
A system to measure the human body asymmetries using accelerometers Journal Article
In: Elektrotehniski Vestnik/Electrotechnical Review, vol. 88, no. 5, pp. 267–272, 2021.
@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},
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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.
Jamšek, Marko; Petrič, Tadej; Babič, Jan
Gaussian Mixture Models for Control of Quasi-Passive Spinal Exoskeletons Journal Article
In: Sensors, vol. 20, no. 9, pp. 2705, 2020, ISSN: 1424-8220.
@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.},
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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.
Cevzar, Mišel; Petrič, Tadej; Jamšek, Marko; Babič, Jan
Real-Time Control of Quasi-Active Hip Exoskeleton Based on Gaussian Mixture Model Approach Book Section
In: Wearable Robotics: Challenges and Trends, pp. 244–248, Springer, Cham, 2019.
@incollection{Cevzar2019,
title = {Real-Time Control of Quasi-Active Hip Exoskeleton Based on Gaussian Mixture Model Approach},
author = {Mi\v{s}el Cevzar and Tadej Petri\v{c} and Marko Jam\v{s}ek and Jan Babi\v{c}},
url = {http://link.springer.com/10.1007/978-3-030-01887-0_47},
doi = {10.1007/978-3-030-01887-0_47},
year = {2019},
date = {2019-10-01},
booktitle = {Wearable Robotics: Challenges and Trends},
pages = {244--248},
publisher = {Springer, Cham},
abstract = {Lower back pain is a major cause of disability and sick day absences. As lower back pain can result in decreased life quality as well as lower industrial productivity, multiple research groups and companies are looking into possible solutions. One of such solutions could be exoskeletons, that engage and disengage the actuators depending on the movements performed by the user. Otherwise we risk hindering the users movements and increasing his metabolic costs. We implemented an exoskeleton control using finite state machine combined with a Gaussian mixture model movement classifier. By conducting a test battery with a subject wearing the exoskeleton we were able to engage the exoskeleton actuators when appropriate and keep them disengaged to allow a full and unhindered range of motion. The results show our exoskeleton control correctly engages and disengages actuators based on the movements being performed by the user.},
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Lower back pain is a major cause of disability and sick day absences. As lower back pain can result in decreased life quality as well as lower industrial productivity, multiple research groups and companies are looking into possible solutions. One of such solutions could be exoskeletons, that engage and disengage the actuators depending on the movements performed by the user. Otherwise we risk hindering the users movements and increasing his metabolic costs. We implemented an exoskeleton control using finite state machine combined with a Gaussian mixture model movement classifier. By conducting a test battery with a subject wearing the exoskeleton we were able to engage the exoskeleton actuators when appropriate and keep them disengaged to allow a full and unhindered range of motion. The results show our exoskeleton control correctly engages and disengages actuators based on the movements being performed by the user.
Jamšek, Marko; Babič, Jan
Human Trunk Stabilization with Hip Exoskeleton for Enhanced Postural Control Book Section
In: Wearable Robotics: Challenges and Trends, pp. 450–454, Springer, Cham, 2019.
@incollection{Jamsek2019,
title = {Human Trunk Stabilization with Hip Exoskeleton for Enhanced Postural Control},
author = {Marko Jam\v{s}ek and Jan Babi\v{c}},
url = {http://link.springer.com/10.1007/978-3-030-01887-0_87},
doi = {10.1007/978-3-030-01887-0_87},
year = {2019},
date = {2019-10-01},
booktitle = {Wearable Robotics: Challenges and Trends},
pages = {450--454},
publisher = {Springer, Cham},
abstract = {Tripping is a major cause of falls in elderly people. Considering that fall related injuries have severe consequences on their quality of life, there is an urgent need to develop preventive solutions. One such solution could be the use of assistive exoskeletons. In this work we investigated the effects of a hip exoskeleton on human posture under the influence of an external perturbation. During normal standing of a subject we applied a forward pulling force at the chest and then enabled or disabled the exoskeleton randomly. By analysing the kinematics of the human body we compared responses to perturbations when the exoskeleton was enabled or disabled. The results show that the exoskeleton efficiently reduced the forward inclination of the trunk by 40%.},
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Tripping is a major cause of falls in elderly people. Considering that fall related injuries have severe consequences on their quality of life, there is an urgent need to develop preventive solutions. One such solution could be the use of assistive exoskeletons. In this work we investigated the effects of a hip exoskeleton on human posture under the influence of an external perturbation. During normal standing of a subject we applied a forward pulling force at the chest and then enabled or disabled the exoskeleton randomly. By analysing the kinematics of the human body we compared responses to perturbations when the exoskeleton was enabled or disabled. The results show that the exoskeleton efficiently reduced the forward inclination of the trunk by 40%.
Bobek, Urban; Rueckert, Elmar; Jamšek, Marko; Barišić, Saša; Babič, Jan
Combining Foot Placement Prediction with Obstacle Detection to Detect Tripping Proceedings Article
In: Žemva, Andrej; Trost, Andrej (Ed.): Proceedings of the Twenty-eighth Electrotechnical and Computer Science Conference ERK 2019, pp. 110–113, Portorož, Slovenia, 2019, ISSN: 2591-0442.
@inproceedings{Bobek2019,
title = {Combining Foot Placement Prediction with Obstacle Detection to Detect Tripping},
author = {Urban Bobek and Elmar Rueckert and Marko Jam\v{s}ek and Sa\v{s}a Bari\v{s}i\'{c} and Jan Babi\v{c}},
editor = {Andrej \v{Z}emva and Andrej Trost},
url = {https://erk.fe.uni-lj.si/2019/program},
issn = {2591-0442},
year = {2019},
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booktitle = {Proceedings of the Twenty-eighth Electrotechnical and Computer Science Conference ERK 2019},
pages = {110--113},
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abstract = {Tripping is a major cause of fall related injuries, especialy among the elderly population. Some research has been done on the mechanics of tripping and strategies to gain balance afterwards. But what if you could detect a potential trip in advance and possibly prevent it? We pro- pose a system that involves detecting obstacles in front of the user and a method to predict whether they will hit it.},
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Tripping is a major cause of fall related injuries, especialy among the elderly population. Some research has been done on the mechanics of tripping and strategies to gain balance afterwards. But what if you could detect a potential trip in advance and possibly prevent it? We pro- pose a system that involves detecting obstacles in front of the user and a method to predict whether they will hit it.
Jamšek, Marko; Babič, Jan
Design and preliminary testing of a pneumatic exoskeleton for walking assistance Proceedings Article
In: 27th International Electrotechnical and Computer Science Conference ERK 2018, pp. 159–162, 2018.
@inproceedings{Jamsek2018,
title = {Design and preliminary testing of a pneumatic exoskeleton for walking assistance},
author = {Marko Jam\v{s}ek and Jan Babi\v{c}},
url = {https://erk.fe.uni-lj.si/2018/program.php},
year = {2018},
date = {2018-01-01},
urldate = {2018-01-01},
booktitle = {27th International Electrotechnical and Computer Science Conference ERK 2018},
pages = {159--162},
abstract = {Tripping is one of the major causes of falls in elderly people. Injuries that originate from falls usually have se- vere consequences on their quality of life. The best so- lution for this problem is prevention of such traumatic events which proves to be a challenge in the current state of elderly care. This is why we are in an urgent need of developing new solutions that could help in the preven- tion of falls and fall related injuries in this ever increas- ing part of our entire population. One possible preven- tive solution could be the use of assistive devices such as exoskeletons. In this work we present a design of a pneumatic exoskeleton for walking assistance primarily designed as a platform to study active control solutions for preventing falls caused by tripping. We also present a preliminary evaluation of the exoskeleton capabilities on affecting the gait characteristics of a subject during walking.},
keywords = {},
pubstate = {published},
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Tripping is one of the major causes of falls in elderly people. Injuries that originate from falls usually have se- vere consequences on their quality of life. The best so- lution for this problem is prevention of such traumatic events which proves to be a challenge in the current state of elderly care. This is why we are in an urgent need of developing new solutions that could help in the preven- tion of falls and fall related injuries in this ever increas- ing part of our entire population. One possible preven- tive solution could be the use of assistive devices such as exoskeletons. In this work we present a design of a pneumatic exoskeleton for walking assistance primarily designed as a platform to study active control solutions for preventing falls caused by tripping. We also present a preliminary evaluation of the exoskeleton capabilities on affecting the gait characteristics of a subject during walking.