المؤلفون: Braun, Jan-Matthias, Wörgötter, Florentin, Manoonpong, Poramate

المصدر: Frontiers in Neurorobotics; 1/24/2019, pN.PAG-N.PAG, 17p

مصطلحات موضوعية: GAIT in humans, KNEE physiology, ARTIFICIAL neural networks, STAIR climbing, PREDICTION models

مستخلص: Orthoses for the lower limbs support patients to perform movements that they could not perform on their own. In traditional devices, generic gait models for a limited set of supported movements restrict the patients mobility and device acceptance. To overcome such limitations, we propose a modular neural control approach with user feedback for personalizable Knee-Ankle-Foot-Orthoses (KAFO). The modular controller consists of two main neural components: neural orthosis control for gait phase tracking and neural internal models for gait prediction and selection. A user interface providing online feedback allows the user to shape the control output that adjusts the knee damping parameter of a KAFO. The accuracy and robustness of the control approach were investigated in different conditions including walking on flat ground and descending stairs as well as stair climbing. We show that the controller accurately tracks and predicts the user's movements and generates corresponding gaits. Furthermore, based on the modular control architecture, the controller can be extended to support various distinguishable gaits depending on differences in sensory feedback. [ABSTRACT FROM AUTHOR]

: Copyright of Frontiers in Neurorobotics is the property of Frontiers Media S.A. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

المؤلفون: Braun, Jan-Matthias, Manoonpong, Poramate, Xiong, Xiaofeng

المصدر: Frontiers in Neurorobotics; 11/13/2020, Vol. 14, pN.PAG-N.PAG, 3p

مصطلحات موضوعية: BIOENGINEERING, INSECT locomotion, SYNTHETIC biology, CENTRAL pattern generators, ROBOT hands, BIONICS

مستخلص: Keywords: biology-inspired engineering; engineering-inspired biology; bio-inspired computation; bio-inspired sensors; bio-inspired materials; bio-inspired structure EN biology-inspired engineering engineering-inspired biology bio-inspired computation bio-inspired sensors bio-inspired materials bio-inspired structure N.PAG N.PAG 3 11/17/20 20201113 NES 201113 The term biology-inspired engineering refers to the fact that biology has been an important inspiration for developments in all aspects of engineering, for example the design of robots. This special issue reports the results and reviews of biology-inspired engineering and engineering-inspired biology research. The results suggest that Lilibot can be considered as a friendly and generic quadrupedal platform for biology-inspired engineering and engineering-inspired biology studies. Biology-inspired engineering, engineering-inspired biology, bio-inspired computation, bio-inspired sensors, bio-inspired materials, bio-inspired structure. [Extracted from the article]

: Copyright of Frontiers in Neurorobotics is the property of Frontiers Media S.A. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

المؤلفون: Braun, Jan-Matthias, Wörgötter, Florentin, Manoonpong, Poramate

المصدر: Frontiers in Neurorobotics; 7/25/2018, pN.PAG-N.PAG, 17p

مصطلحات موضوعية: BIOLOGICAL neural networks, GAIT in humans, ORTHOPEDIC apparatus

مستخلص: Orthoses for the lower limbs support patients to perform movements that they could not perform on their own. In traditional devices, generic gait models for a limited set of supported movements restrict the patients mobility and device acceptance. To overcome such limitations, we propose a modular neural control approach with user feedback for personalizable Knee-Ankle-Foot-Orthoses (KAFO). The modular controller consists of two main neural components: neural orthosis control for gait phase tracking and neural internal models for gait prediction and selection. A user interface providing online feedback allows the user to shape the control output that adjusts the knee damping parameter of a KAFO. The accuracy and robustness of the control approach were investigated in different conditions including walking on flat ground and descending stairs as well as stair climbing. We show that the controller accurately tracks and predicts the user's movements and generates corresponding gaits. Furthermore, based on the modular control architecture, the controller can be extended to support various distinguishable gaits depending on differences in sensory feedback. [ABSTRACT FROM AUTHOR]

: Copyright of Frontiers in Neurorobotics is the property of Frontiers Media S.A. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)