The estimation of the joint angles of upper limb during walking using fuzzy logic system and relation maps

Skoda, David; Kutílek, Patrik; Socha, Vladimír; Schlenker, Jakub; Štefek, Alexandr; Kalina, Jan

doi:10.1109/sami.2015.7061888

Cited by 4 publications

(2 citation statements)

References 31 publications

(27 reference statements)

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“…These controllers are employed especially for assistive exoskeletons. [48][49][50] Similarly, there are also used methods based on neural networks. Neural networks are learned based on the previous state (measured by MoCap systems or assistive joints) and after learning about the neural networks, expected states are inferred.…”

Section: Operator-exoskeleton Interactionmentioning

confidence: 99%

Empowering lower limbs exoskeletons: state-of-the-art

et al. 2018

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SUMMARYGiven the advanced breakthroughs in the field of supportive robotic technologies, interest in the integration of the human body and a robot into a single system has rapidly increased. The aim of this work is to provide an overview of empowering lower limbs exoskeletons. Along with lower exoskeleton limbs, their unique design concepts, operator–exoskeleton interactions and control strategies are described. Although many problems have been solved in recent development, many challenges remain. Especially in the context of infantry soldiers, fire fighters and rescuers, the challenges of empowering exoskeletons are discussed, and improvements are outlined and described. This study is not only a summary of the current state, but also points to weaknesses of empowering lower limbs exoskeletons and outlines possible improvements.

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Section: Operator-exoskeleton Interactionmentioning

confidence: 99%

Empowering lower limbs exoskeletons: state-of-the-art

et al. 2018

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“…The development and simulation of fuzzy logic based learning mechanisms related to robotic rehabilitation is well-documented, utilizing various devices to emulate human motor learning [2], [9], [10], [11], [12], [13], and [14]. The relationships between movements of upper extremities identifying joint angles using a fuzzy logic system have been reported [15]; these authors analysed a range of joint angles and rhythmical movement variables to design a fuzzy expert system.…”

Section: Background and Related Workmentioning

confidence: 99%

An adaptive self-organizing fuzzy logic controller in a serious game for motor impairment rehabilitation

Esfahlani¹,

Cirstea²,

Sanaei³

et al. 2017

2017 IEEE 26th International Symposium on Industrial Electronics (ISIE)

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Rehabiliation robotics combined with video game technology provides a means of assisting in the rehabilitation of patients with neuromuscular disorders by performing various facilitation movements. The current work presents ReHabGame, a serious game using a fusion of implemented technologies that can be easily used by patients and therapists to assess and enhance sensorimotor performance and also increase the activities in the daily lives of patients. The game allows a player to control avatar movements through a Kinect Xbox, Myo armband and rudder foot pedal, and involves a series of reach-grasp-collect tasks whose difficulty levels are learnt by a fuzzy interface. The orientation, angular velocity, head and spine tilts and other data generated by the player are monitored and saved, whilst the task completion is calculated by solving an inverse kinematics algorithm which orientates the upper limb joints of the avatar. The different values in upper body quantities of movement provide fuzzy input from which crisp output is determined and used to generate an appropriate subsequent rehabilitation game level. The system can thus provide personalised, autonomously-learnt rehabilitation programmes for patients with neuromuscular disorders with superior predictions to guide the development of improved clinical protocols compared to traditional theraputic activities.

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