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AAL-IoT: Ambient Assisted Living using non-intrusive smart sensing and IoT for gait rehabilitation

Authors: Santos, Joel Vieira;

AAL-IoT: Ambient Assisted Living using non-intrusive smart sensing and IoT for gait rehabilitation

Abstract

A monitorização de saúde de pacientes em hospitais, lares, clínicas de fisioterapia ou outros centros clínicos, é uma tarefa importante e recorrente. Além disso, estas instituições requerem um sistema estruturado e organizado, com acesso ao historial médico de todos os utilizadores. O desenvolvimento de um sistema com a capacidade de medir a características de saúde físicas dos utilizadores pode ser também aplicado à área de fisioterapia. Neste contexto, o trabalho de investigação de mestrado apresenta uma solução de um sistema não-intrusivo caracterizado por sensores inteligentes, como parte de um ecossistema de IoT, que visa resolver todas as questões enunciadas. O sistema IoT utiliza uma carpete inteligente, SensFloor, para medir vários indicadores físicos, como a posição dos utilizadores e as características da marcha considerando jogos sérios que foram implementadas para aumentar a motivação de utilizadores nos planos de reabilitação de marcha. Os dados produzidos pelo sistema são armazenados em tempo-real numa base de dados em nuvem, pelo que tanto os fisioterapeutas como os pacientes têm acesso a estes dados. Além disso, a apresentação de resultados é realizada utilizando gráficos que são produzidos tempo-real, permitindo análises adicionais acerca da marcha dos utilizadores – Considerando a informação obtida os fisioterapeutas podem tomar medidas para melhorar o plano de treino com exercícios mais personalizados.

Health monitoring of users in medical centers, nursing homes, physiotherapy clinics or other healthcare centers, is an important and recurring task. In addition, these facilities require a structured, organized system with access to all users’ medical history. The design of a system that can measure individuals’ physiological health characteristics (PHC) may also be applied to physical rehabilitation. In this context, this Master’s research work presents a solution of a non-intrusive system characterized by smart sensing as part of an IoT ecosystem, that aims to solve all the issues stated. The IoT system uses a smart carpet, SensFloor, to measure several physical indicators, such as users’ position and gait characteristics, considering serious games that were implemented to increase the motivation of users in gait rehabilitation plans. The produced data by the system is stored in a real-time cloud database, thus physical therapists and patients are able to access it. Also, the presentation of results is achieved using several dashboards that are produced in real-time, to provide further analysis on users’ gait and PHCs – Considering the obtained information, physiotherapists may take measures to improve the training plan with personalized exercises.

Country
Portugal
Keywords

Internet of things, Serious games, Monitoring, Monitorização, AAL, Análise de dados -- Data analysis, Smart carpet, Marcha, mHealth, Carpete inteligente, Jogos sérios, eHealth, Gait, Domínio/Área Científica::Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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