Evidence map›Paper›PMID 36369025›Full record

ArticleJournal of neuroengineering and rehabilitation2022

Neuro-cognitive assessment of intentional control methods for a soft elbow exosuit using error-related potentials.

Nicholas Tacca, John Nassour, Stefan K Ehrlich, Nicolas Berberich, Gordon Cheng

Abstract read
In one paragraph

Article in Journal of neuroengineering and rehabilitation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Nicholas Tacca *Institute for Cognitive Systems, Technical University of Munich, Munich, Germany.
John Nassour *Institute for Cognitive Systems, Technical University of Munich, Munich, Germany. nassour@tum.de.
Stefan K EhrlichInstitute for Cognitive Systems, Technical University of Munich, Munich, Germany.
Nicolas BerberichInstitute for Cognitive Systems, Technical University of Munich, Munich, Germany.
Gordon ChengInstitute for Cognitive Systems, Technical University of Munich, Munich, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Soft exosuits offer promise to support users in everyday workload tasks by providing assistance. However, acceptance of such systems remains low due to the difficulty of control compared with rigid mechatronic systems. Recently, there has been progress in developing control schemes for soft exosuits that move in line with user intentions. While initial results have demonstrated sufficient device performance, the assessment of user experience via the cognitive response has yet to be evaluated. To address this, we propose a soft pneumatic elbow exosuit designed based on our previous work to provide assistance in line with user expectations utilizing two existing state-of-the-art control methods consisting of a gravity compensation and myoprocessor based on muscle activation. A user experience study was conducted to assess whether the device moves naturally with user expectations and the potential for device acceptance by determining when the exosuit violated user expectations through the neuro-cognitive and motor response. Brain activity from electroencephalography (EEG) data revealed that subjects elicited error-related potentials (ErrPs) in response to unexpected exosuit actions, which were decodable across both control schemes with an average accuracy of 76.63 ± 1.73% across subjects. Additionally, unexpected exosuit actions were further decoded via the motor response from electromyography (EMG) and kinematic data with a grand average accuracy of 68.73 ± 6.83% and 77.52 ± 3.79% respectively. This work demonstrates the validation of existing state-of-the-art control schemes for soft wearable exosuits through the proposed soft pneumatic elbow exosuit. We demonstrate the feasibility of assessing device performance with respect to the cognitive response through decoding when the device violates user expectations in order to help understand and promote device acceptance.

Indexed as

Exoskeleton DeviceRoboticsBiomechanical PhenomenaCognitionElbowHumansEEGEMGExosuitHuman–machine interfaceSoft robotics

Identifiers

PMID36369025
PMCPMC9652996

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.