Autonomic Computing in a Biomimetic Algorithm for Robots Dedicated to Rehabilitation of Ankle

Autonomic Computing in a Biomimetic Algorithm for Robots Dedicated to Rehabilitation of Ankle

Euzébio D. de Souza (Federal University of Minas Gerais, Belo Horizonte, Brazil) and Eduardo José Lima II (Federal University of Minas Gerais, Belo Horizonte, Brazil)
Copyright: © 2017 |Pages: 13
DOI: 10.4018/IJGHPC.2017010105
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Abstract

Human mobility is the key element of everyday life, its reduction or loss deeply affects daily activities. In assisted rehabilitation, robotic devices have focuses on the biomechanics of motor control. However, biomechanics does not study the neurological and physiological processes related to normal gait. Biomimetics combined with biomechanics, can generate a more efficient stimulation of the motor cortex and the locomotor system. The highest efficiency obtained through torque generation models, based on the physiological response of muscles and bones to reaction forces, together with control techniques based on autonomic computation. An autonomic control algorithm has a self-adjusting behaviour, ensuring patient safety and robot operation without the continuous monitoring of the physiotherapist. Thus, this work will identify the elements that characterize the physiological stimuli related to normal human gait, focusing on the ankle joint, aiming the development of biomimetic algorithms for robots for rehabilitation of the lower limbs.
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Biomimetics Applied To Kinematic Model For Lower Limbs

The biomimetic point of view is important to understand the physical and physiological phenomena involved, aiming to create an effective physiological response in rehabilitation. Understand aspects of the movement of the joints and reaction forces, your behavior over bone tissue, are points needed to develop a robot dedicated to rehabilitation (Bai, 2015). In this analysis, the starting point is to ensure the re-production of the ankle joint moves. Therefore, the robot must provide with only one degree of freedom, allowing the reproduction of flexion plantar and dorsiflexion (Ahmad, 2013) as shown in Figure 1.

Figure 1.

Ankle joint movements

The angles shown in Figure 1 related to the maximum displacement of the ankle joint. Dorsiflexion is the movement, which gives the gear cadence while plantar flexion is responsible for generating impulse at the beginning of travel. This way the definition of an efficient and accurate kinematic model from the computational point of view becomes important (Schmidt, 2004), this being shown by the Equation 1.

(1)

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