Multi-Exoskeleton Performance Evaluation: Integrated Muscle Energy Indices to Determine the Quality and Quantity of Assistance
The assessment of realistic work tasks is a critical aspect of introducing exoskeletons to work environments. However, as the experimental task’s complexity increases, the analysis of muscle activity becomes increasingly challenging. Thus, it is essential to use metrics that adequately represent the...
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MDPI AG
2024-12-01
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| Series: | Bioengineering |
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| Online Access: | https://www.mdpi.com/2306-5354/11/12/1231 |
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| author | Vasco Fanti Sergio Leggieri Tommaso Poliero Matteo Sposito Darwin G. Caldwell Christian Di Natali |
| author_facet | Vasco Fanti Sergio Leggieri Tommaso Poliero Matteo Sposito Darwin G. Caldwell Christian Di Natali |
| author_sort | Vasco Fanti |
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| description | The assessment of realistic work tasks is a critical aspect of introducing exoskeletons to work environments. However, as the experimental task’s complexity increases, the analysis of muscle activity becomes increasingly challenging. Thus, it is essential to use metrics that adequately represent the physical human–exoskeleton interaction (pHEI). Muscle activity analysis is usually reduced to a comparison of point values (average or maximum muscle contraction), neglecting the signals’ trend. Metrics based on single values, however, lack information about the dynamism of the task and its duration. Their meaning can be uncertain, especially when analyzing complex movements or temporally extended activities, and it is reduced to an overall assessment of the interaction on the whole task. This work proposes a method based on integrated EMGs (iEMGs) to evaluate the pHEI by considering task dynamism, temporal duration, and the neural energy associated with muscle activity. The resulting signal highlights the task phases in which the exoskeleton reduces or increases the effort required to accomplish the task, allowing the calculation of specific indices that quantify the energy exchange in terms of assistance (AII), resistance (RII), and overall interaction (OII). The method provides an analysis tool that enables developers and controller designers to receive insights into the exoskeleton performances and the quality of the user-robot interaction. The application of this method is provided for passive and two active back support exoskeletons: the Laevo, XoTrunk, and StreamEXO. |
| format | Article |
| id | doaj-art-e31cb567f6664e1fba30242d50b235b0 |
| institution | Kabale University |
| issn | 2306-5354 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
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| series | Bioengineering |
| spelling | doaj-art-e31cb567f6664e1fba30242d50b235b02024-12-27T14:11:33ZengMDPI AGBioengineering2306-53542024-12-011112123110.3390/bioengineering11121231Multi-Exoskeleton Performance Evaluation: Integrated Muscle Energy Indices to Determine the Quality and Quantity of AssistanceVasco Fanti0Sergio Leggieri1Tommaso Poliero2Matteo Sposito3Darwin G. Caldwell4Christian Di Natali5Department of Advanced Robotics (ADVR), Istituto Italiano di Tecnologia (IIT), 16163 Genova, ItalyDepartment of Advanced Robotics (ADVR), Istituto Italiano di Tecnologia (IIT), 16163 Genova, ItalyDepartment of Advanced Robotics (ADVR), Istituto Italiano di Tecnologia (IIT), 16163 Genova, ItalyDepartment of Advanced Robotics (ADVR), Istituto Italiano di Tecnologia (IIT), 16163 Genova, ItalyDepartment of Advanced Robotics (ADVR), Istituto Italiano di Tecnologia (IIT), 16163 Genova, ItalyDepartment of Advanced Robotics (ADVR), Istituto Italiano di Tecnologia (IIT), 16163 Genova, ItalyThe assessment of realistic work tasks is a critical aspect of introducing exoskeletons to work environments. However, as the experimental task’s complexity increases, the analysis of muscle activity becomes increasingly challenging. Thus, it is essential to use metrics that adequately represent the physical human–exoskeleton interaction (pHEI). Muscle activity analysis is usually reduced to a comparison of point values (average or maximum muscle contraction), neglecting the signals’ trend. Metrics based on single values, however, lack information about the dynamism of the task and its duration. Their meaning can be uncertain, especially when analyzing complex movements or temporally extended activities, and it is reduced to an overall assessment of the interaction on the whole task. This work proposes a method based on integrated EMGs (iEMGs) to evaluate the pHEI by considering task dynamism, temporal duration, and the neural energy associated with muscle activity. The resulting signal highlights the task phases in which the exoskeleton reduces or increases the effort required to accomplish the task, allowing the calculation of specific indices that quantify the energy exchange in terms of assistance (AII), resistance (RII), and overall interaction (OII). The method provides an analysis tool that enables developers and controller designers to receive insights into the exoskeleton performances and the quality of the user-robot interaction. The application of this method is provided for passive and two active back support exoskeletons: the Laevo, XoTrunk, and StreamEXO.https://www.mdpi.com/2306-5354/11/12/1231integrated EMGmuscular analysisoccupational exoskeletonsperformance evaluationphysical human–robot interaction |
| spellingShingle | Vasco Fanti Sergio Leggieri Tommaso Poliero Matteo Sposito Darwin G. Caldwell Christian Di Natali Multi-Exoskeleton Performance Evaluation: Integrated Muscle Energy Indices to Determine the Quality and Quantity of Assistance Bioengineering integrated EMG muscular analysis occupational exoskeletons performance evaluation physical human–robot interaction |
| title | Multi-Exoskeleton Performance Evaluation: Integrated Muscle Energy Indices to Determine the Quality and Quantity of Assistance |
| title_full | Multi-Exoskeleton Performance Evaluation: Integrated Muscle Energy Indices to Determine the Quality and Quantity of Assistance |
| title_fullStr | Multi-Exoskeleton Performance Evaluation: Integrated Muscle Energy Indices to Determine the Quality and Quantity of Assistance |
| title_full_unstemmed | Multi-Exoskeleton Performance Evaluation: Integrated Muscle Energy Indices to Determine the Quality and Quantity of Assistance |
| title_short | Multi-Exoskeleton Performance Evaluation: Integrated Muscle Energy Indices to Determine the Quality and Quantity of Assistance |
| title_sort | multi exoskeleton performance evaluation integrated muscle energy indices to determine the quality and quantity of assistance |
| topic | integrated EMG muscular analysis occupational exoskeletons performance evaluation physical human–robot interaction |
| url | https://www.mdpi.com/2306-5354/11/12/1231 |
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