Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/83195
Título: | Gait monitoring system for patients with Parkinson’s disease |
Autor(es): | Gonçalves, Helena Raquel Gouveia Silva Rodrigues, Ana Margarida Fernandes Marques Santos, Cristina |
Palavras-chave: | Wearable sensors Adaptive computational method Real-time application Gait monitoring system Parkinson’s disease |
Data: | 2021 |
Editora: | Elsevier 1 |
Revista: | Expert Systems with Applications |
Citação: | Helena R. Gonçalves, Ana Rodrigues, Cristina P. Santos, Gait monitoring system for patients with Parkinson’s disease, Expert Systems with Applications, Volume 185, 2021, 115653, ISSN 0957-4174, https://doi.org/10.1016/j.eswa.2021.115653. |
Resumo(s): | Background: Wearable monitoring devices based on inertial sensors have the potential to be used as a quantitative method in clinical practice for continuous assessment of gait disabilities in Parkinson’s disease (PD). Methods: This manuscript introduces a new gait monitoring system adapted to patients with PD, based on a wearable monitoring device. To eliminate inter- and intra-subject variability, the computational method was based on heuristic rules with adaptive thresholds and ranges and a motion compensation strategy. The experimental trials involved repeated measurements of walking trials from two cross-sectional studies: the first study was performed in order to validate the effectiveness of the system against a robust 3D motion analysis with 10 healthy subjects; and the second-one aimed to validate our approach against a well-studied wearable IMU-based system on a hospital environment with 20 patients with PD. Results: The proposed system proved to be efficient (Experiment I: sensitivity = 95,09% and accuracy = 93,64%; Experiment II: sensitivity = 99,53% and accuracy = 97,42%), time-effective (Experiment I: earlies = 13,71 ms and delays = 12,91 ms; Experiment II: earlies = 12,94 ms and delays = 12,71 ms), user and user-motion adaptable and a low computational-load strategy for real-time gait events detection. Further, it was measured the percentage of absolute error classified with a good acceptability (Experiment I: 3,02 ≤ ε%≤12,94; Experiment II: 2,81 ≤ ε%≤13,45). Lastly, regarding the measured gait parameters, it was observed a reflection of the typical levels of motor impairment for the different disease stages. Conclusion: The achieved outcomes enabled to verify that the proposed system can be suitable for gait analysis in the assistance and rehabilitation fields. |
Tipo: | Artigo |
URI: | https://hdl.handle.net/1822/83195 |
DOI: | 10.1016/j.eswa.2021.115653 |
ISSN: | 0957-4174 |
Versão da editora: | https://doi.org/10.1016/j.eswa.2021.115653 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: | CMEMS - Artigos em revistas internacionais/Papers in international journals |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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1-s2.0-S0957417421010447-main.pdf | 9,7 MB | Adobe PDF | Ver/Abrir |