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Neuro-cognitive assessment of intentional control methods for a soft elbow exosuit using error-related potentials.
Tacca, Nicholas; Nassour, John; Ehrlich, Stefan K; Berberich, Nicolas; Cheng, Gordon.
Afiliação
  • Tacca N; Institute for Cognitive Systems, Technical University of Munich, Munich, Germany.
  • Nassour J; Institute for Cognitive Systems, Technical University of Munich, Munich, Germany. nassour@tum.de.
  • Ehrlich SK; Institute for Cognitive Systems, Technical University of Munich, Munich, Germany.
  • Berberich N; Institute for Cognitive Systems, Technical University of Munich, Munich, Germany.
  • Cheng G; Institute for Cognitive Systems, Technical University of Munich, Munich, Germany.
J Neuroeng Rehabil ; 19(1): 124, 2022 11 11.
Article em En | MEDLINE | ID: mdl-36369025
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.
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Texto completo: 1 Temas: ECOS / Aspectos_gerais Bases de dados: MEDLINE Assunto principal: Robótica / Exoesqueleto Energizado Limite: Humans Idioma: En Revista: J Neuroeng Rehabil Assunto da revista: ENGENHARIA BIOMEDICA / NEUROLOGIA / REABILITACAO Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Alemanha

Texto completo: 1 Temas: ECOS / Aspectos_gerais Bases de dados: MEDLINE Assunto principal: Robótica / Exoesqueleto Energizado Limite: Humans Idioma: En Revista: J Neuroeng Rehabil Assunto da revista: ENGENHARIA BIOMEDICA / NEUROLOGIA / REABILITACAO Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Alemanha