Publication
Auxiliary tool for hand rehabilitation through multicore optical fiber Bragg grating sensors
| Summary: | This work aimed to develop a fibre optic sensor capable of monitoring the joint movements of the fingers of the hand. This was achieved using multicore optical fibres (MCFs) with fibre Bragg gratings (FBGs) multiplexed along the length of the fibre and in the wavelength. Through the measurement of their spectral wavelength shift, it was possible to reconstruct the directional curvature in multiple points along the length of the MCF. The sensor was characterised in two configurations: using only the MCF and using the MCF encapsulated in a capillary tube. Various materials were tested for the tube, and it was concluded that the most suitable was the nitinol tube due to its superelastic properties, which allow the fibre to return to its original shape after deformation. The sensitivity curves obtained by the radial core-FBGs for different angular positions of the MCF revealed satisfactory results and were similar between each other, demonstrating good performance for the characterisation of the sensor. After obtaining the maximum sensitivities for each FBG inscribed in each MCF core, it was possible to reconstruct the curvature vector at a specific MCF length. Tests of the sensor's performance were carried out using the data obtained for calibrating the sensor, showing that it was capable of reconstructing both the amplitude and direction of the curvature vector with average errors of 5% and 1%, respectively. To validate the robustness of the method, random curvatures and orientations were tested for the four quadrants, obtaining errors lower than those mentioned above. In a second phase of the work, the sensor was used to reconstruct the twodimensional shape of the MCF. It was observed that the reconstructed shape was close to the predicted one, despite localised errors. These were attributed to the distance between the FBGs (≈ 2.5 cm) and the model used for reconstruction which uses the spatial position of the prior FBG to estimate the spatial position of the next, leading consequently to the propagation of errors. In addition, the reconstruction method assumes that the MCF maintains its angular alignment along the MCF length. However, since the MCF length was ≈ 70 cm, small twists can appear along its length, contributing to additional errors. In the final phase of this thesis, the sensor's performance was evaluated in the index finger, using three scenarios: using a 3D printed finger, through a robotic hand, and in the finger of a healthy individual. In each case, the amplitude of the curvature vector was reconstructed and later compared with the predicted one, showing better performance for smoother curvatures. The average errors obtained were in the order of 6% in the case of the tests carried out on the 3D printed finger and 4% in the case of both the healthy individual and the robotic hand. These results showed promising results regarding the use of this technology for the monitoring of the degrees of motor function disability of the hand in rehabilitation contexts, guaranteeing a powerful tool for the occupational therapist. |
|---|---|
| Main Authors: | Marinho, Maria Eduarda Teixeira |
| Subject: | Rehabilitation Hand Fiber bragg grating Optical fiber sensor Multicore optical fiber Curvature |
| Year: | 2025 |
| Country: | Portugal |
| Document type: | master thesis |
| Access type: | embargoed access |
| Associated institution: | Universidade de Aveiro |
| Language: | English |
| Origin: | RIA - Repositório Institucional da Universidade de Aveiro |
| _version_ | 1877769479652376576 |
|---|---|
| author | Marinho, Maria Eduarda Teixeira |
| author_facet | Marinho, Maria Eduarda Teixeira |
| author_role | author |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Marinho, Maria Eduarda Teixeira\"}] |
| datacite.creators.creator.creatorName.fl_str_mv | Marinho, Maria Eduarda Teixeira |
| datacite.date.Accepted.fl_str_mv | 2025-07-17T00:00:00Z |
| datacite.date.available.fl_str_mv | 2027-07-17T00:00:00Z |
| datacite.date.embargoed.fl_str_mv | 2027-07-17T00:00:00Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_f1cf |
| datacite.subjects.subject.fl_str_mv | Rehabilitation Hand Fiber bragg grating Optical fiber sensor Multicore optical fiber Curvature |
| datacite.titles.title.fl_str_mv | Auxiliary tool for hand rehabilitation through multicore optical fiber Bragg grating sensors |
| dc.creator.none.fl_str_mv | Marinho, Maria Eduarda Teixeira |
| dc.date.Accepted.fl_str_mv | 2025-07-17T00:00:00Z |
| dc.date.available.fl_str_mv | 2027-07-17T00:00:00Z |
| dc.date.embargoed.fl_str_mv | 2027-07-17T00:00:00Z |
| dc.description.none.fl_str_mv | Este trabalho teve o intuito de desenvolver um sensor de fibra ótica capaz de monitorizar os movimentos articulares dos dedos da mão. Para isso foram usadas fibras óticas de múltiplos núcleos (MCF) com redes de Bragg (FBG) multiplexados ao longo do comprimento da fibra e no comprimento de onda. Através da monitorização do seu desvio espectral foi possível reconstruir a curvatura direcional em múltiplos pontos ao longo do comprimento da MCF. A caracterização do sensor foi realizada em duas configurações: recorrendo somente à MCF e, encapsulando esta num tubo capilar. Diversos materiais foram testados para este último, tendo-se concluído que o mais adequado era o tubo de nitinol, devido às suas propriedades super elásticas, que permitem o retorno da fibra à sua forma original após a deformação. As curvas de sensibilidade obtidas pelas FBGs dos núcleos radiais para diferentes posições angulares da MCF apresentaram resultados satisfatórios e semelhantes entre si, demonstrando uma boa performance do sensor e do método de caracterização. Após a obtenção das sensibilidades máximas de cada FBG inscrita em cada núcleo da MCF, foi possível reconstruir o vetor de curvatura numa dada posição da MCF. Foram realizados testes da performance do sensor recorrendo aos dados obtidos para calibração do sensor, mostrando que este era capaz de reconstruir tanto a amplitude como a direção do vetor de curvatura, com erros médios de ≈ 5% e ≈ 1%, respetivamente. Para validar a robustez do método, foram testadas curvaturas e orientações aleatórias para os quatro quadrantes, obtendo-se erros inferiores aos mencionados anteriormente. Numa segunda fase do trabalho, o sensor foi utilizado para reconstruir a forma bidimensional da MCF. Observou-se que esta se aproximou da prevista, apesar de erros localizados, que foram atribuídos à distância entre FBGs (≈ 2,5 cm) e ao modelo utilizado para a reconstrução que pressupõem o uso da posição espacial da FBG antecedente para calcular a posição da FBG seguinte, levando inerentemente a uma propagação de erros. Adicionalmente, o método de reconstrução assume que a MCF se mantém sobre o mesmo alinhamento angular durante os ensaios. Contudo, como esta tinha ≈ 70 cm, existe possibilidade da existência de pequenas torções ao longo do seu comprimento, contribuindo também com erros adicionais. Na fase final desta tese, o desempenho do sensor foi avaliado no dedo indicador da mão. Usando três cenários: num dedo impresso em 3D; usando o dedo de uma mão robótica; e no dedo de um indivíduo saudável. Em cada caso, a amplitude do vetor de curvatura reconstruida foi comparada com a prevista, tendo-se verificado melhor desempenho para curvaturas mais suaves. Os erros médios obtidos foram na ordem dos 6% no caso dos testes realizados no dedo impresso e 4% tanto no caso do individuo saudável como na mão robótica. Estes resultados mostram-se bastante promissores para utilização futura da monitorização dos graus de incapacidade motora da mão em contextos de reabilitação garantindo uma ferramenta poderosa para o terapeuta ocupacional. |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10773/45503 |
| dc.language.none.fl_str_mv | eng |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_f1cf |
| dc.subject.none.fl_str_mv | Rehabilitation Hand Fiber bragg grating Optical fiber sensor Multicore optical fiber Curvature |
| dc.title.fl_str_mv | Auxiliary tool for hand rehabilitation through multicore optical fiber Bragg grating sensors |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_bdcc |
| description | This work aimed to develop a fibre optic sensor capable of monitoring the joint movements of the fingers of the hand. This was achieved using multicore optical fibres (MCFs) with fibre Bragg gratings (FBGs) multiplexed along the length of the fibre and in the wavelength. Through the measurement of their spectral wavelength shift, it was possible to reconstruct the directional curvature in multiple points along the length of the MCF. The sensor was characterised in two configurations: using only the MCF and using the MCF encapsulated in a capillary tube. Various materials were tested for the tube, and it was concluded that the most suitable was the nitinol tube due to its superelastic properties, which allow the fibre to return to its original shape after deformation. The sensitivity curves obtained by the radial core-FBGs for different angular positions of the MCF revealed satisfactory results and were similar between each other, demonstrating good performance for the characterisation of the sensor. After obtaining the maximum sensitivities for each FBG inscribed in each MCF core, it was possible to reconstruct the curvature vector at a specific MCF length. Tests of the sensor's performance were carried out using the data obtained for calibrating the sensor, showing that it was capable of reconstructing both the amplitude and direction of the curvature vector with average errors of 5% and 1%, respectively. To validate the robustness of the method, random curvatures and orientations were tested for the four quadrants, obtaining errors lower than those mentioned above. In a second phase of the work, the sensor was used to reconstruct the twodimensional shape of the MCF. It was observed that the reconstructed shape was close to the predicted one, despite localised errors. These were attributed to the distance between the FBGs (≈ 2.5 cm) and the model used for reconstruction which uses the spatial position of the prior FBG to estimate the spatial position of the next, leading consequently to the propagation of errors. In addition, the reconstruction method assumes that the MCF maintains its angular alignment along the MCF length. However, since the MCF length was ≈ 70 cm, small twists can appear along its length, contributing to additional errors. In the final phase of this thesis, the sensor's performance was evaluated in the index finger, using three scenarios: using a 3D printed finger, through a robotic hand, and in the finger of a healthy individual. In each case, the amplitude of the curvature vector was reconstructed and later compared with the predicted one, showing better performance for smoother curvatures. The average errors obtained were in the order of 6% in the case of the tests carried out on the 3D printed finger and 4% in the case of both the healthy individual and the robotic hand. These results showed promising results regarding the use of this technology for the monitoring of the degrees of motor function disability of the hand in rehabilitation contexts, guaranteeing a powerful tool for the occupational therapist. |
| dirty | 0 |
| eu_rights_str_mv | embargoedAccess |
| format | masterThesis |
| id | ria_5bcc713b62fda793cd155730a16002fc |
| identifier.url.fl_str_mv | http://hdl.handle.net/10773/45503 |
| inst_facet_str | urn:organizationAcronym:ua{{{_:::_}}}Universidade de Aveiro |
| instacron_str | ua |
| institution | Universidade de Aveiro |
| instname_str | Universidade de Aveiro |
| language | eng |
| network_acronym_str | ria |
| network_name_str | RIA - Repositório Institucional da Universidade de Aveiro |
| oai_identifier_str | oai:ria.ua.pt:10773/45503 |
| organization_str_mv | urn:organizationAcronym:ua |
| person_str_mv | Marinho, Maria Eduarda Teixeira |
| publishDate | 2025 |
| repo_facet_str | urn:repositoryAcronym:ria{{{_:::_}}}RIA - Repositório Institucional da Universidade de Aveiro |
| reponame_str | RIA - Repositório Institucional da Universidade de Aveiro |
| repository_id_str | urn:repositoryAcronym:ria |
| service_str_mv | urn:repositoryAcronym:ria |
| spelling | pt_PTThis work aimed to develop a fibre optic sensor capable of monitoring the joint movements of the fingers of the hand. This was achieved using multicore optical fibres (MCFs) with fibre Bragg gratings (FBGs) multiplexed along the length of the fibre and in the wavelength. Through the measurement of their spectral wavelength shift, it was possible to reconstruct the directional curvature in multiple points along the length of the MCF. The sensor was characterised in two configurations: using only the MCF and using the MCF encapsulated in a capillary tube. Various materials were tested for the tube, and it was concluded that the most suitable was the nitinol tube due to its superelastic properties, which allow the fibre to return to its original shape after deformation. The sensitivity curves obtained by the radial core-FBGs for different angular positions of the MCF revealed satisfactory results and were similar between each other, demonstrating good performance for the characterisation of the sensor. After obtaining the maximum sensitivities for each FBG inscribed in each MCF core, it was possible to reconstruct the curvature vector at a specific MCF length. Tests of the sensor's performance were carried out using the data obtained for calibrating the sensor, showing that it was capable of reconstructing both the amplitude and direction of the curvature vector with average errors of 5% and 1%, respectively. To validate the robustness of the method, random curvatures and orientations were tested for the four quadrants, obtaining errors lower than those mentioned above. In a second phase of the work, the sensor was used to reconstruct the twodimensional shape of the MCF. It was observed that the reconstructed shape was close to the predicted one, despite localised errors. These were attributed to the distance between the FBGs (≈ 2.5 cm) and the model used for reconstruction which uses the spatial position of the prior FBG to estimate the spatial position of the next, leading consequently to the propagation of errors. In addition, the reconstruction method assumes that the MCF maintains its angular alignment along the MCF length. However, since the MCF length was ≈ 70 cm, small twists can appear along its length, contributing to additional errors. In the final phase of this thesis, the sensor's performance was evaluated in the index finger, using three scenarios: using a 3D printed finger, through a robotic hand, and in the finger of a healthy individual. In each case, the amplitude of the curvature vector was reconstructed and later compared with the predicted one, showing better performance for smoother curvatures. The average errors obtained were in the order of 6% in the case of the tests carried out on the 3D printed finger and 4% in the case of both the healthy individual and the robotic hand. These results showed promising results regarding the use of this technology for the monitoring of the degrees of motor function disability of the hand in rehabilitation contexts, guaranteeing a powerful tool for the occupational therapist.pt_PTEste trabalho teve o intuito de desenvolver um sensor de fibra ótica capaz de monitorizar os movimentos articulares dos dedos da mão. Para isso foram usadas fibras óticas de múltiplos núcleos (MCF) com redes de Bragg (FBG) multiplexados ao longo do comprimento da fibra e no comprimento de onda. Através da monitorização do seu desvio espectral foi possível reconstruir a curvatura direcional em múltiplos pontos ao longo do comprimento da MCF. A caracterização do sensor foi realizada em duas configurações: recorrendo somente à MCF e, encapsulando esta num tubo capilar. Diversos materiais foram testados para este último, tendo-se concluído que o mais adequado era o tubo de nitinol, devido às suas propriedades super elásticas, que permitem o retorno da fibra à sua forma original após a deformação. As curvas de sensibilidade obtidas pelas FBGs dos núcleos radiais para diferentes posições angulares da MCF apresentaram resultados satisfatórios e semelhantes entre si, demonstrando uma boa performance do sensor e do método de caracterização. Após a obtenção das sensibilidades máximas de cada FBG inscrita em cada núcleo da MCF, foi possível reconstruir o vetor de curvatura numa dada posição da MCF. Foram realizados testes da performance do sensor recorrendo aos dados obtidos para calibração do sensor, mostrando que este era capaz de reconstruir tanto a amplitude como a direção do vetor de curvatura, com erros médios de ≈ 5% e ≈ 1%, respetivamente. Para validar a robustez do método, foram testadas curvaturas e orientações aleatórias para os quatro quadrantes, obtendo-se erros inferiores aos mencionados anteriormente. Numa segunda fase do trabalho, o sensor foi utilizado para reconstruir a forma bidimensional da MCF. Observou-se que esta se aproximou da prevista, apesar de erros localizados, que foram atribuídos à distância entre FBGs (≈ 2,5 cm) e ao modelo utilizado para a reconstrução que pressupõem o uso da posição espacial da FBG antecedente para calcular a posição da FBG seguinte, levando inerentemente a uma propagação de erros. Adicionalmente, o método de reconstrução assume que a MCF se mantém sobre o mesmo alinhamento angular durante os ensaios. Contudo, como esta tinha ≈ 70 cm, existe possibilidade da existência de pequenas torções ao longo do seu comprimento, contribuindo também com erros adicionais. Na fase final desta tese, o desempenho do sensor foi avaliado no dedo indicador da mão. Usando três cenários: num dedo impresso em 3D; usando o dedo de uma mão robótica; e no dedo de um indivíduo saudável. Em cada caso, a amplitude do vetor de curvatura reconstruida foi comparada com a prevista, tendo-se verificado melhor desempenho para curvaturas mais suaves. Os erros médios obtidos foram na ordem dos 6% no caso dos testes realizados no dedo impresso e 4% tanto no caso do individuo saudável como na mão robótica. Estes resultados mostram-se bastante promissores para utilização futura da monitorização dos graus de incapacidade motora da mão em contextos de reabilitação garantindo uma ferramenta poderosa para o terapeuta ocupacional.application/pdfengpt_PTAuxiliary tool for hand rehabilitation through multicore optical fiber Bragg grating sensorsMarinho, Maria Eduarda TeixeiraHandlehttp://hdl.handle.net/10773/455032027-07-17T00:00:00Z2025-07-17T00:00:00Z2025-07-17http://purl.org/coar/access_right/c_f1cfembargoed accesspt_PTRehabilitationpt_PTHandpt_PTFiber bragg gratingpt_PTOptical fiber sensorpt_PTMulticore optical fiberpt_PTCurvature2928332 byteshttp://purl.org/coar/access_right/c_f1cfapplication/pdffulltexthttps://ria.ua.pt/bitstream/10773/45503/1/Documento_Maria_Marinho.pdfother research producthttp://purl.org/coar/resource_type/c_bdccmaster thesis |
| spellingShingle | Auxiliary tool for hand rehabilitation through multicore optical fiber Bragg grating sensors Marinho, Maria Eduarda Teixeira Rehabilitation Hand Fiber bragg grating Optical fiber sensor Multicore optical fiber Curvature |
| status | SINGLETON |
| subject.fl_str_mv | Rehabilitation Hand Fiber bragg grating Optical fiber sensor Multicore optical fiber Curvature |
| title | Auxiliary tool for hand rehabilitation through multicore optical fiber Bragg grating sensors |
| title_full | Auxiliary tool for hand rehabilitation through multicore optical fiber Bragg grating sensors |
| title_fullStr | Auxiliary tool for hand rehabilitation through multicore optical fiber Bragg grating sensors |
| title_full_unstemmed | Auxiliary tool for hand rehabilitation through multicore optical fiber Bragg grating sensors |
| title_short | Auxiliary tool for hand rehabilitation through multicore optical fiber Bragg grating sensors |
| title_sort | Auxiliary tool for hand rehabilitation through multicore optical fiber Bragg grating sensors |
| topic | Rehabilitation Hand Fiber bragg grating Optical fiber sensor Multicore optical fiber Curvature |
| topic_facet | Rehabilitation Hand Fiber bragg grating Optical fiber sensor Multicore optical fiber Curvature |
| url | http://hdl.handle.net/10773/45503 |
| visible | 1 |
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