In classical man-machine interfaces applied to rehabilitation, the primary goal is to control the (bio)mechanical interaction between the human and the machine or environment. However, integrating the human into the loop can be considered not only from a biomechanical view but also with regard to psychophysiological aspects. Biomechanical integration involves ensuring that the system to be used is ergonomically acceptable and “user cooperative.” Psychophysiological integration involves recording and controlling the patient’s physiological reactions so that the patient receives appropriate stimuli and is challenged in a moderate but engaging way without causing undue stress or harm. In this chapter, we present examples of biomechanical and psychophysiological integration of patients that have been verified with the gait robot Lokomat.
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- Detailed record: https://infoscience.epfl.ch/record/175828?ln=en
This paper presents the concept and initial results of a novel approach for robot assisted sensorimotor training in stroke rehabilitation. It is based on a brain-body-robot interface (B 2RI), combining both neural and physiological recordings, that detects the intention to perform a motor task. By directly including the injured brain into the therapy, we ultimately aim at providing a new method for severely impaired patients to engage in active movement therapy. In the present study, seven healthy subjects performed an isometric finger pinching task while functional near-infrared spectroscopy (fNIRS) signals from motor cortical areas and biosignals were recorded simultaneously. Results showed an insignificant increase in the blood pressure during the preparation period prior to motor execution. During the execution period, significant changes in oxy-and deoxyhemoglobin were found in the primary motor cortex, accompanied by an increase in blood pressure, respiration rate and galvanic skin response (GSR). Cortical measurements of premotor areas and heart rate revealed significant changes at the subject level with large inter-subject variability. The results presented here will serve as priors for the design of further studies to test the efficacy of the concept with stroke patients, and the found effects will provide a basis for the development of a classifier for a future B 2RI. © 2011 IEEE.
In general, concurrent augmented feedback has been shown to effectively enhance learning in complex motor tasks. However, to optimize technical systems that are intended to reinforce motor learning, a systematic evaluation of different augmented feedback designs is required. Until now, mainly visual augmented feedback has been applied to enhance learning of complex motor tasks. Since most complex motor tasks are mastered in response to information visually perceived, providing augmented concurrent feedback in a visual manner may overload the capacities of visual perception and cognitive processing. Thus, the aim of this work was to evaluate the practicability of auditory feedback designs supporting a three-dimensional rowing-type movement in comparison with visual feedback designs. We term a feedback design practical if the provided information can easily be perceived and interpreted, and immediately be used to support the movement. In a first experiment, it became evident that participants could interpret three-dimensional auditory feedback designs based on stereo balance, pitch, timbre, and/or volume. Eleven of 12 participants were able to follow the different target movements using auditory feedback designs as accurately as with a very abstract visual feedback design. Visual designs based on superposition of actual and target oar orientation led to the most accurate performance. Considering the first experimental results, the feedback designs were further developed and again evaluated. It became evident that a permanent visual display of the target trajectories could further enhance movement accuracy. Moreover, results indicated that the practicability of the auditory designs depends on the polarity of the mapping functions. In general, both visual and auditory concurrent feedback designs were practical to immediately support multidimensional movement. In a next step, the effectiveness to enhance motor learning will be systematically evaluated.
Les animaux ont-ils une conscience ? Les machines peuvent-elles se montrer intelligentes ? Chaque nouvelle découverte des biologistes, chaque progrès technologique nous invite à reconsidérer le propre de l’homme. Ce livre, fruit de la collaboration entre Georges Chapouthier, biologiste et philosophe de la biologie, et Frédéric Kaplan, ingénieur spécialiste de l’intelligence artificielle et des interfaces homme-machine, fait le point sur les multiples manières dont les animaux et les machines peuvent être comparés aux êtres humains. Après un panorama synthétique des capacités des animaux et des machines à apprendre, développer une conscience, ressentir douleur ou émotion, construire une culture ou une morale, les auteurs détaillent ce qui nous lie à nos alter-egos biologiques ou artificiels : attachement, sexualité, droit, hybridation. Au-delà, ils explorent des traits qui semblent spécifiquement humains – l’imaginaire, l’âme ou le sens du temps – mais pour combien de temps encore… Une exploration stimulante au coeur des mystères de la nature humaine, qui propose une redéfinition de l’homme dans son rapport à l’animal et à la machine.
- Detailed record: https://infoscience.epfl.ch/record/175830?ln=en
- Detailed record: https://infoscience.epfl.ch/record/175829?ln=en
- Detailed record: https://infoscience.epfl.ch/record/175827?ln=en
This paper presents the actuation system of the robotic leg ScarlETH. It was developed specifically for a quadrupedal robot and is designed to achieve fast position control as well as accurate joint torque control. It introduces strong passive dynamics to create an efficient running behavior. High spring compliance with low damping in combination with a cascaded, motor velocity based, control structure was successfully tested in simulation and experiments. Final tests with the entire leg demonstrate that the system can perform a hopping motion providing only positive actuator power.
Rehabilitation robots allow for a longer and more intensive locomotor training than that achieved by conventional therapies. Robot-assisted treadmill training also offers the ability to provide objective feedback within one training session and to monitor functional improvements over time. This article provides an overview of the technical approach for one of these systems known as “Lokomat” including new features such as hip ab/adduction actuation, cooperative control strategies, assessment tools, and augmented feedback. These special technical functions may be capable of further enhancing training quality, training intensity, and patient participation.