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Silva L, Dias M, Folgado D, Nunes M, Namburi P, Anthony B, Carvalho D, Carvalho M, Edelman E, Gamboa H. Respiratory Inductance Plethysmography to Assess Fatigability during Repetitive Work. Sensors (Basel) 2022; 22:s22114247. [PMID: 35684868 PMCID: PMC9185634 DOI: 10.3390/s22114247] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/01/2022] [Revised: 05/27/2022] [Accepted: 05/30/2022] [Indexed: 11/16/2022]
Abstract
Cumulative fatigue during repetitive work is associated with occupational risk and productivity reduction. Usually, subjective measures or muscle activity are used for a cumulative evaluation; however, Industry 4.0 wearables allow overcoming the challenges observed in those methods. Thus, the aim of this study is to analyze alterations in respiratory inductance plethysmography (RIP) to measure the asynchrony between thorax and abdomen walls during repetitive work and its relationship with local fatigue. A total of 22 healthy participants (age: 27.0 ± 8.3 yrs; height: 1.72 ± 0.09 m; mass: 63.4 ± 12.9 kg) were recruited to perform a task that includes grabbing, moving, and placing a box in an upper and lower shelf. This task was repeated for 10 min in three trials with a fatigue protocol between them. Significant main effects were found from Baseline trial to the Fatigue trials (p < 0.001) for both RIP correlation and phase synchrony. Similar results were found for the activation amplitude of agonist muscle (p < 0.001), and to the muscle acting mainly as a joint stabilizer (p < 0.001). The latter showed a significant effect in predicting both RIP correlation and phase synchronization. Both RIP correlation and phase synchronization can be used for an overall fatigue assessment during repetitive work.
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Affiliation(s)
- Luís Silva
- Laboratório de Instrumentação, Engenharia Biomédica e Física da Radiação (LIBPhys-UNL), Departamento de Física, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, 2829-516 Caparica, Portugal; (M.D.); (D.F.); (H.G.)
- Correspondence:
| | - Mariana Dias
- Laboratório de Instrumentação, Engenharia Biomédica e Física da Radiação (LIBPhys-UNL), Departamento de Física, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, 2829-516 Caparica, Portugal; (M.D.); (D.F.); (H.G.)
| | - Duarte Folgado
- Laboratório de Instrumentação, Engenharia Biomédica e Física da Radiação (LIBPhys-UNL), Departamento de Física, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, 2829-516 Caparica, Portugal; (M.D.); (D.F.); (H.G.)
- Associação Fraunhofer Portugal Research, Rua Alfredo Allen 455/461, 4200-135 Porto, Portugal;
| | - Maria Nunes
- Associação Fraunhofer Portugal Research, Rua Alfredo Allen 455/461, 4200-135 Porto, Portugal;
| | - Praneeth Namburi
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; (P.N.); (B.A.); (E.E.)
- MIT.nano Immersion Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Brian Anthony
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; (P.N.); (B.A.); (E.E.)
- Device Realization Laboratory, Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Diogo Carvalho
- Faculty of Medicine, Rīga Stradiņš University, 16 Dzirciema iela, LV-1007 Rīga, Latvia;
| | - Miguel Carvalho
- Campus de Azurém, Minho University, 4800-058 Guimarães, Portugal;
| | - Elazer Edelman
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; (P.N.); (B.A.); (E.E.)
- Brigham and Women’s Hospital, Cardiovascular Division, 75 Francis Street, Boston, MA 02115, USA
| | - Hugo Gamboa
- Laboratório de Instrumentação, Engenharia Biomédica e Física da Radiação (LIBPhys-UNL), Departamento de Física, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, 2829-516 Caparica, Portugal; (M.D.); (D.F.); (H.G.)
- Associação Fraunhofer Portugal Research, Rua Alfredo Allen 455/461, 4200-135 Porto, Portugal;
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Ávila-Gutiérrez MJ, Aguayo-González F, Lama-Ruiz JR. Framework for the Development of Affective and Smart Manufacturing Systems Using Sensorised Surrogate Models. Sensors (Basel) 2021; 21:2274. [PMID: 33805015 DOI: 10.3390/s21072274] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 03/19/2021] [Accepted: 03/21/2021] [Indexed: 01/18/2023]
Abstract
Human Factor strategy and management have been affected by the incorporation of Key Enabling Technologies (KETs) of industry 4.0, whereby operator 4.0 has been configured to address the wide variety of cooperative activities and to support skills that operate in VUCA (volatile, uncertain, complex, and ambiguous) environments under the interaction with ubiquitous interfaces on real and virtual hybrid environments of cyber-physical systems. Current human Competences-Capacities that are supported by the technological enablers could result in a radically disempowered human factor. This means that in the processes of optimization and improvement of manufacturing systems from industry 4.0 to industry 5.0, it would be necessary to establish strategies for the empowerment of the human factor, which constitute symbiotic and co-evolutionary socio-technical systems through talent, sustainability, and innovation. This paper establishes a new framework for the design and development of occupational environments 5.0 for the inclusion of singularized operators 4.0, such as individuals with special capacities and talents. A case study for workers and their inclusion in employment is proposed. This model integrates intelligent and inclusive digital solutions in the current workspaces of organizations under digital transformation.
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