A comparative analysis of three non-invasive human-machine interfaces for the disabled
Ravindra V, Castellini C (2014)
Publication Type: Journal article
Publication year: 2014
Journal
Book Volume: 8
Article Number: e00024
Journal Issue: JAN
Abstract
In the framework of rehabilitation robotics, a major role is played by the human-machine interface (HMI) used to gather the patient's intent from biological signals, and convert them into control signals for the robotic artifact. Surprisingly, decades of research have not yet declared what the optimal HMI is in this context; in particular, the traditional approach based upon surface electromyography (sEMG) still yields unreliable results due to the inherent variability of the signal. To overcome this problem, the scientific community has recently been advocating the discovery, analysis, and usageofnovel HMIsto supersede oraugment sEMG; a comparative analysis of such HMIs is therefore a very desirable investigation. In this paper,we compare three such HMIs employedinthe detection of finger forces, namely sEMG, ultrasound imaging, and pressure sensing.The comparison is performed along four main lines: the accuracy in the prediction, the stability over time, the wearability, and the cost. A psychophysical experiment involving ten intact subjects engaged in a simple fingerflexion task was set up. Our results show that, at least in this experiment, pressure sensing and sEMG yield comparably good prediction accuracies as opposed to ultrasound imaging; and that pressure sensing enjoys a much better stability than sEMG. Given that pressure sensors are as wearable as sEMG electrodes but way cheaper, we claim that this HMI could represent a valid alternative/augmentation to sEMG to control a multi-fingered hand prosthesis.
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Germany (DE)How to cite
APA:
Ravindra, V., & Castellini, C. (2014). A comparative analysis of three non-invasive human-machine interfaces for the disabled. Frontiers in Neurorobotics, 8(JAN). https://dx.doi.org/10.3389/fnbot.2014.00024
MLA:
Ravindra, Vikram, and Claudio Castellini. "A comparative analysis of three non-invasive human-machine interfaces for the disabled." Frontiers in Neurorobotics 8.JAN (2014).
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