Development and initial validation of the Seated Posture Scale

Barks, Lelia; Luther, Stephen L.; Brown, Lisa M.; Schulz, Brian W.; Bowen, Mary Elizabeth; Powell‐Cope, Gail

doi:10.1682/jrrd.2014.04.0100

Cited by 9 publications

(2 citation statements)

References 16 publications

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“…At present, given the difficulty of continuous monitoring by health specialists, postural monitoring and diagnosis is carried out by means of specific questionnaires [8]. However, these questionnaires are composed of a certain subjective character, and they are not suitable to monitor posture on a continuous basis.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Sitting Posture Classifier for Wheelchair Users

Vermander

Mancisidor

Cabanes

et al. 2023

IEEE Trans. Neural Syst. Rehabil. Eng.

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In recent years, there has been growing interest in postural monitoring while seated, thus preventing the appearance of ulcers and musculoskeletal problems in the long term. To date, postural control has been carried out by means of subjective questionnaires that do not provide continuous and quantitative information. For this reason, it is necessary to carry out a monitoring that allows to determine not only the postural status of wheelchair users, but also to infer the evolution or anomalies associated with a specific disease. Therefore, this paper proposes an intelligent classifier based on a multilayer neural network for the classification of sitting postures of wheelchair users. The posture database was generated based on data collected by a novel monitoring device composed of force resistive sensors. A training and hyperparameter selection methodology has been used based on the idea of using a stratified K-Fold in weight groups strategy. This allows the neural network to acquire a greater capacity for generalization, thus allowing, unlike other proposed models, to achieve higher success rates not only in familiar subjects but also in subjects with physical complexions outside the standard. In this way, the system can be used to support wheelchair users and healthcare professionals, helping them to automatically monitor their posture, regardless physical complexions.

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Section: Introductionmentioning

confidence: 99%

Intelligent Sitting Posture Classifier for Wheelchair Users

Vermander

Mancisidor

Cabanes

et al. 2023

IEEE Trans. Neural Syst. Rehabil. Eng.

View full text Add to dashboard Cite

show abstract

“…Isso foi comprovado com o relato dos usuários de CR entrevistados que demonstraram forte desejo de alterações em seus equipamentos, e corroborou com estudos de Ossada et al, 2014 e Caro et al, 2014, sobre a insatisfação dos usuários que receberam CR e SAP concedidos pelo SUS e a falta de especialistas para prescrições adequadas. Um tema que tem sido discutido e preconizado em diversos países é avaliação para prescrição das CR e SAP ser baseada em três princípios da Classificação International de Funcionalidade -CIF (WHO, 2001), porque ajudam a avaliar e caracterizar de maneira mais integrada a condição da pessoa com deficiência, combinando a limitação funcional com outros fatores: (1) Estruturas e funções do corpo (2) Atividades e participações do usuário 3Meio ambiente e tecnologias atuais (ARLEDGE et al, 2011). No Brasil, a legislação vigente categoriza a deficiência ainda segundo critérios biológicos, como por exemplo: deficiência física, visual, auditiva, mental e múltipla.…”

Section: Resultados Finais -úLtima Versão Do App Easyseatingunclassified