Posts Tagged Multimodal Interface

[ARTICLE] Multimodal robotic system for upper-limb rehabilitation in physical environment – Full Text HTML

Abstract

This article researches the feasibility of use of a multimodal robotic system for upper-limb neurorehabilitation therapies in physical environments, interacting with real objects. This system consists of an end-effector upper-limb rehabilitation robot, a hand exoskeleton, a gaze tracking system, an object tracking system, and electromyographic measuring units. For this purpose, the system architecture is stated, explaining the detailed functions of each subsystem as well as the interaction among them. Finally, an experimental scenario is designed to test the system with healthy subjects in order to check whether the system is suitable for future experiments with patients.

Introduction

The use of robotic systems in neurorehabilitation therapies may be justified because of its potential impact on better treatment and motor learning.1 For this reason, in the recent years, a wide variety of robotic devices for upper-limb neurorehabilitation have been developed by research groups around the world.211

In conjunction with these robotic devices, a wide range of robot-oriented rehabilitation interfaces and environments have been stated. Many of the current devices use virtual reality systems to set up the rehabilitation context;1217 and just few examples use physical environments.18,19 It should be pointed out that all these examples, except Badesa et al.’s14 work, use robotic exoskeletons.

Virtual reality systems are specially suitable for early stages of the disease,20 due to the flexibility that it offers when designing tasks and feedback stimuli, and the safety that it provides due to the absence of interaction with physical objects that can lead to injuries. However, in order to obtain a realistic interaction, it is necessary to use haptic devices,2124 which result in expensive and complex systems. In contrast, physical environments may suppose a good and inexpensive alternative to perform more complex, and functional, rehabilitation tasks in later stages of the disease, when patients have recovered some motor control of their upper limb.

The objective of this article is to check whether an end-effector rehabilitation robot25can be used to develop a fully functional multimodal rehabilitation system in physical environments. In contrast to Frisoli et al.’s19 work, the use of an end-effector robot instead of an exoskeleton is expected to result in a considerable reduction in the setup time as well as in an increase in user’s comfort. Additionally, the brain–computer interface (BCI) is replaced by electromyography, which does not require previous training, reducing user’s mental fatigue26 and saving additional time.

In this regard, the experimentation will focus on testing whether the mechanical system can be controlled with precision and safety enough to interact with some objects and perform a simple occupational therapy activity successfully, so that further researches in this path can be done.

Multimodal architecture

The starting point is an already designed upper-limb neurorehabilitation robot, which was conceived to deliver therapies in virtual reality environments, during the early stages after stroke.

In order to achieve the stated objectives, a multimodal architecture has been stated so that users can use a combination of their residual capabilities to perform the task. Among the possible remaining skills that patients may keep, eye movement and electromyographic (EMG) signals have been chosen for these tests.

Specifically, the designed system is composed of the following:

  • An object tracking system, which gives the position of the object that will be handled.

  • A gaze tracking device that will determine which object the patient is looking at.

  • EMG measuring units used as a trigger of several actions.

  • An end-effector rehabilitation robot that will assist the patient to perform reaching movements.

  • A hand exoskeleton for grasping the objects.

  • A computer that implements the high-level control (HLC) system, which will process and coordinate the signals of each device and will determine the control actions.

Communication and relationship between each element are stated in Figure 1.

Figure 1.

Figure 1. System architecture and communications between components.

Continue —> Multimodal robotic system for upper-limb rehabilitation in physical environment

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[ARTICLE] Multimodal robotic system for upper-limb rehabilitation in physical environment – Full Text HTML

Abstract

This article researches the feasibility of use of a multimodal robotic system for upper-limb neurorehabilitation therapies in physical environments, interacting with real objects. This system consists of an end-effector upper-limb rehabilitation robot, a hand exoskeleton, a gaze tracking system, an object tracking system, and electromyographic measuring units. For this purpose, the system architecture is stated, explaining the detailed functions of each subsystem as well as the interaction among them. Finally, an experimental scenario is designed to test the system with healthy subjects in order to check whether the system is suitable for future experiments with patients.

Introduction

The use of robotic systems in neurorehabilitation therapies may be justified because of its potential impact on better treatment and motor learning.1 For this reason, in the recent years, a wide variety of robotic devices for upper-limb neurorehabilitation have been developed by research groups around the world.211

In conjunction with these robotic devices, a wide range of robot-oriented rehabilitation interfaces and environments have been stated. Many of the current devices use virtual reality systems to set up the rehabilitation context;1217 and just few examples use physical environments.18,19 It should be pointed out that all these examples, except Badesa et al.’s14 work, use robotic exoskeletons.

Virtual reality systems are specially suitable for early stages of the disease,20 due to the flexibility that it offers when designing tasks and feedback stimuli, and the safety that it provides due to the absence of interaction with physical objects that can lead to injuries. However, in order to obtain a realistic interaction, it is necessary to use haptic devices,2124 which result in expensive and complex systems. In contrast, physical environments may suppose a good and inexpensive alternative to perform more complex, and functional, rehabilitation tasks in later stages of the disease, when patients have recovered some motor control of their upper limb.

The objective of this article is to check whether an end-effector rehabilitation robot25can be used to develop a fully functional multimodal rehabilitation system in physical environments. In contrast to Frisoli et al.’s19 work, the use of an end-effector robot instead of an exoskeleton is expected to result in a considerable reduction in the setup time as well as in an increase in user’s comfort. Additionally, the brain–computer interface (BCI) is replaced by electromyography, which does not require previous training, reducing user’s mental fatigue26 and saving additional time.

In this regard, the experimentation will focus on testing whether the mechanical system can be controlled with precision and safety enough to interact with some objects and perform a simple occupational therapy activity successfully, so that further researches in this path can be done.

 

Continue —> Multimodal robotic system for upper-limb rehabilitation in physical environment

 

Figure 1.

Figure 1. System architecture and communications between components.

 

Figure 2.

Figure 2. Difference between hand position and end-effector position with respect to the reference frame of the end-effector.

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[BOOK CHAPTER] Interactive Motor Learning with the Autonomous Training Assistant: A Case Study – Springer

 

Interactive Motor Learning with the Autonomous Training Assistant: A Case Study – Springer.

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