A Soft and Smart Telehealth System Hand Rehabilitation Device for Grasping Force Assessment of Post Stroke Patients
| Main Author: | |
|---|---|
| Publication Date: | 2023 |
| Format: | Master thesis |
| Language: | eng |
| Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
| Download full: | http://hdl.handle.net/10362/160937 |
Summary: | The assessment of post-stroke patient rehabilitation currently lacks a comprehensive ap- proach, often relying on subjective evaluations without a universally accepted quantitative method. In this study, a sensorised device was developed to contribute to bridging this gap. This device interfaces with a platform enabling therapists to visually analyse real-time data and facilitates data retrieval for in-depth analysis. This research involved the creation and characterisation of several pneumatic sensors using Finite Element Anaysis (FEA) and mechanical testing. After meticulous shape selection, multiple sensors were calibrated and integrated into a cylindrical object. Com- munication was established through two multiplexers and an Arduino Nano, resulting in a compact and portable object. This system was then connected to a laptop via USB, utilising a LabVIEW program as the user interface. This program enabled the concurrent measurement of individual finger forces during grasping movements for both hands. Real-time data visualization and subsequent data retrieval were also supported. The system adeptly addresses the identified limitations, emerging as a cost-effective, precise, and adaptable tool. Subsequent improvements are expected to fine-tune its precision, durability, and relevance within stroke rehabilitation scenarios. In this regard, the innovative tool, which is the primary contribution of this study, holds the potential to substantially elevate rehabilitation strategies and play a pivotal role in augmenting the recovery process. The research work described in this dissertation was carried out in accordance with the norms established in the ethics code of Universidade Nova de Lisboa. The work described and the material presented in this dissertation, with the exceptions clearly indicated, constitute original work carried out by the author. |
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A Soft and Smart Telehealth System Hand Rehabilitation Device for Grasping Force Assessment of Post Stroke PatientsStrokeHand rehabilitationSensorised objectsGrasping forceFlexible sensorsHand AnatomyDomínio/Área Científica::Engenharia e Tecnologia::Outras Engenharias e TecnologiasThe assessment of post-stroke patient rehabilitation currently lacks a comprehensive ap- proach, often relying on subjective evaluations without a universally accepted quantitative method. In this study, a sensorised device was developed to contribute to bridging this gap. This device interfaces with a platform enabling therapists to visually analyse real-time data and facilitates data retrieval for in-depth analysis. This research involved the creation and characterisation of several pneumatic sensors using Finite Element Anaysis (FEA) and mechanical testing. After meticulous shape selection, multiple sensors were calibrated and integrated into a cylindrical object. Com- munication was established through two multiplexers and an Arduino Nano, resulting in a compact and portable object. This system was then connected to a laptop via USB, utilising a LabVIEW program as the user interface. This program enabled the concurrent measurement of individual finger forces during grasping movements for both hands. Real-time data visualization and subsequent data retrieval were also supported. The system adeptly addresses the identified limitations, emerging as a cost-effective, precise, and adaptable tool. Subsequent improvements are expected to fine-tune its precision, durability, and relevance within stroke rehabilitation scenarios. In this regard, the innovative tool, which is the primary contribution of this study, holds the potential to substantially elevate rehabilitation strategies and play a pivotal role in augmenting the recovery process. The research work described in this dissertation was carried out in accordance with the norms established in the ethics code of Universidade Nova de Lisboa. The work described and the material presented in this dissertation, with the exceptions clearly indicated, constitute original work carried out by the author.A avaliação da reabilitação de pacientes após Acidente Vascular Cerebral carece atualmente de uma abordagem abrangente, muitas vezes dependendo de avaliações subjetivas sem um método quantitativo universalmente aceite. Neste estudo, um dispositivo sensorizado foi desenvolvido para ajudar a colmatar esta lacuna. Este dispositivo interage com uma plataforma que permite aos terapeutas analisar visualmente dados em tempo real e facilita a recuperação de dados para análise detalhada. Este projeto envolveu a criação e caracterização de vários sensores pneumáticos uti- lizando o método de Análise de Elementos Finitos bem como testes mecânicos. Após uma seleção meticulosa de formas, vários sensores foram calibrados e integrados num objeto cilíndrico. A comunicação foi estabelecida através de dois multiplexadores e um Arduino Nano, resultando num objeto compacto e portátil. Este sistema foi então ligado a um computador portátil via USB, utilizando um programa LabVIEW como interface com o utilizador. Este programa permitiu a medição simultânea das forças individuais dos dedos durante os movimentos de preensão palmar de ambas as mãos. A visualização de dados em tempo real e a subsequente recuperação de dados também foram suportadas. O sistema aborda de forma hábil as limitações identificadas, emergindo como uma ferramenta eficaz, precisa e adaptável em termos de custos. Melhorias subsequentes têm como objetivo afinar a sua precisão, durabilidade e relevância em cenários de reabilitação. Neste sentido, esta ferramenta inovadora, que é o principal contributo deste estudo, tem o potencial de elevar substancialmente as estratégias de reabilitação correntes e desempenhar um papel fundamental no melhoramento do processo de recuperação. O trabalho de investigação descrito nesta dissertação foi realizado de acordo com as normas estabelecidas no código de ética da Universidade Nova de Lisboa. O trabalho descrito e o material apresentado nesta dissertação, com as exceções claramente indicadas, constituem trabalho original realizado pela autora.Alici, GurselPereira, CarlaRUNMartinho, Mafalda Miranda Salreu2023-12-06T12:24:34Z2023-112023-11-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/160937enginfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-22T18:16:28Zoai:run.unl.pt:10362/160937Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:46:59.421768Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
| dc.title.none.fl_str_mv |
A Soft and Smart Telehealth System Hand Rehabilitation Device for Grasping Force Assessment of Post Stroke Patients |
| title |
A Soft and Smart Telehealth System Hand Rehabilitation Device for Grasping Force Assessment of Post Stroke Patients |
| spellingShingle |
A Soft and Smart Telehealth System Hand Rehabilitation Device for Grasping Force Assessment of Post Stroke Patients Martinho, Mafalda Miranda Salreu Stroke Hand rehabilitation Sensorised objects Grasping force Flexible sensors Hand Anatomy Domínio/Área Científica::Engenharia e Tecnologia::Outras Engenharias e Tecnologias |
| title_short |
A Soft and Smart Telehealth System Hand Rehabilitation Device for Grasping Force Assessment of Post Stroke Patients |
| title_full |
A Soft and Smart Telehealth System Hand Rehabilitation Device for Grasping Force Assessment of Post Stroke Patients |
| title_fullStr |
A Soft and Smart Telehealth System Hand Rehabilitation Device for Grasping Force Assessment of Post Stroke Patients |
| title_full_unstemmed |
A Soft and Smart Telehealth System Hand Rehabilitation Device for Grasping Force Assessment of Post Stroke Patients |
| title_sort |
A Soft and Smart Telehealth System Hand Rehabilitation Device for Grasping Force Assessment of Post Stroke Patients |
| author |
Martinho, Mafalda Miranda Salreu |
| author_facet |
Martinho, Mafalda Miranda Salreu |
| author_role |
author |
| dc.contributor.none.fl_str_mv |
Alici, Gursel Pereira, Carla RUN |
| dc.contributor.author.fl_str_mv |
Martinho, Mafalda Miranda Salreu |
| dc.subject.por.fl_str_mv |
Stroke Hand rehabilitation Sensorised objects Grasping force Flexible sensors Hand Anatomy Domínio/Área Científica::Engenharia e Tecnologia::Outras Engenharias e Tecnologias |
| topic |
Stroke Hand rehabilitation Sensorised objects Grasping force Flexible sensors Hand Anatomy Domínio/Área Científica::Engenharia e Tecnologia::Outras Engenharias e Tecnologias |
| description |
The assessment of post-stroke patient rehabilitation currently lacks a comprehensive ap- proach, often relying on subjective evaluations without a universally accepted quantitative method. In this study, a sensorised device was developed to contribute to bridging this gap. This device interfaces with a platform enabling therapists to visually analyse real-time data and facilitates data retrieval for in-depth analysis. This research involved the creation and characterisation of several pneumatic sensors using Finite Element Anaysis (FEA) and mechanical testing. After meticulous shape selection, multiple sensors were calibrated and integrated into a cylindrical object. Com- munication was established through two multiplexers and an Arduino Nano, resulting in a compact and portable object. This system was then connected to a laptop via USB, utilising a LabVIEW program as the user interface. This program enabled the concurrent measurement of individual finger forces during grasping movements for both hands. Real-time data visualization and subsequent data retrieval were also supported. The system adeptly addresses the identified limitations, emerging as a cost-effective, precise, and adaptable tool. Subsequent improvements are expected to fine-tune its precision, durability, and relevance within stroke rehabilitation scenarios. In this regard, the innovative tool, which is the primary contribution of this study, holds the potential to substantially elevate rehabilitation strategies and play a pivotal role in augmenting the recovery process. The research work described in this dissertation was carried out in accordance with the norms established in the ethics code of Universidade Nova de Lisboa. The work described and the material presented in this dissertation, with the exceptions clearly indicated, constitute original work carried out by the author. |
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2023 |
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2023-12-06T12:24:34Z 2023-11 2023-11-01T00:00:00Z |
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