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Comparative performance analysis of M-IMU/EMG and voice user interfaces for assistive robots | IEEE Conference Publication | IEEE Xplore

Comparative performance analysis of M-IMU/EMG and voice user interfaces for assistive robots

Publisher: IEEE

Abstract:

People with a high level of disability experience great difficulties to perform activities of daily living and resort to their residual motor functions in order to operat...View more

Abstract:

People with a high level of disability experience great difficulties to perform activities of daily living and resort to their residual motor functions in order to operate assistive devices. The commercially available interfaces used to control assistive manipulators are typically based on joysticks and can be used only by subjects with upper-limb residual mobilities. Many other solutions can be found in the literature, based on the use of multiple sensory systems for detecting the human motion intention and state. Some of them require a high cognitive workload for the user. Some others are more intuitive and easy to use but have not been widely investigated in terms of usability and user acceptance. The objective of this work is to propose an intuitive and robust user interface for assistive robots, not obtrusive for the user and easily adaptable for subjects with different levels of disability. The proposed user interface is based on the combination of M-IMU and EMG for the continuous control of an arm-hand robotic system by means of M-IMUs. The system has been experimentally validated and compared to a standard voice interface. Sixteen healthy subjects volunteered to participate in the study: 8 subjects used the combined M-IMU/EMG robot control, and 8 subjects used the voice control. The arm-hand robotic system made of the KUKA LWR 4+ and the IH2 Azzurra hand was controlled to accomplish the daily living task of drinking. Performance indices and evaluation scales were adopted to assess performance of the two interfaces.
Date of Conference: 17-20 July 2017
Date Added to IEEE Xplore: 14 August 2017
ISBN Information:
Electronic ISSN: 1945-7901
PubMed ID: 28813952
Publisher: IEEE
Conference Location: London, UK

References

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