Feasibility of a Mobile-Based System for Unsupervised Monitoring in Parkinson’s Disease
Mobile health (mHealth) has emerged as a potential solution to providing valuable ecological information about the severity and burden of Parkinson’s disease (PD) symptoms in real-life conditions. <b>Objective</b>: The objective of our study was to explore the feasibility and usability o...
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| Language: | English |
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MDPI AG
2021-07-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/21/15/4972 |
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| author | Raquel Bouça-Machado Filipa Pona-Ferreira Mariana Leitão Ana Clemente Diogo Vila-Viçosa Linda Azevedo Kauppila Rui M. Costa Ricardo Matias Joaquim J. Ferreira |
| author_facet | Raquel Bouça-Machado Filipa Pona-Ferreira Mariana Leitão Ana Clemente Diogo Vila-Viçosa Linda Azevedo Kauppila Rui M. Costa Ricardo Matias Joaquim J. Ferreira |
| author_sort | Raquel Bouça-Machado |
| collection | DOAJ |
| description | Mobile health (mHealth) has emerged as a potential solution to providing valuable ecological information about the severity and burden of Parkinson’s disease (PD) symptoms in real-life conditions. <b>Objective</b>: The objective of our study was to explore the feasibility and usability of an mHealth system for continuous and objective real-life measures of patients’ health and functional mobility, in unsupervised settings. <b>Methods</b>: Patients with a clinical diagnosis of PD, who were able to walk unassisted, and had an Android smartphone were included. Patients were asked to answer a daily survey, to perform three weekly active tests, and to perform a monthly in-person clinical assessment. Feasibility and usability were explored as primary and secondary outcomes. An exploratory analysis was performed to investigate the correlation between data from the mKinetikos app and clinical assessments. <b>Results</b>: Seventeen participants (85%) completed the study. Sixteen participants (94.1%) showed a medium-to-high level of compliance with the mKinetikos system. A 6-point drop in the total score of the Post-Study System Usability Questionnaire was observed. <b>Conclusions</b>: Our results support the feasibility of the mKinetikos system for continuous and objective real-life measures of a patient’s health and functional mobility. The observed correlations of mKinetikos metrics with clinical data seem to suggest that this mHealth solution is a promising tool to support clinical decisions. |
| first_indexed | 2024-03-10T09:08:56Z |
| format | Article |
| id | doaj.art-33b4ef1cc4a643f8b12500378c757210 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T09:08:56Z |
| publishDate | 2021-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-33b4ef1cc4a643f8b12500378c7572102023-11-22T06:08:31ZengMDPI AGSensors1424-82202021-07-012115497210.3390/s21154972Feasibility of a Mobile-Based System for Unsupervised Monitoring in Parkinson’s DiseaseRaquel Bouça-Machado0Filipa Pona-Ferreira1Mariana Leitão2Ana Clemente3Diogo Vila-Viçosa4Linda Azevedo Kauppila5Rui M. Costa6Ricardo Matias7Joaquim J. Ferreira8Instituto de Medicina Molecular, 1649-028 Lisbon, PortugalCNS—Campus Neurológico, 2560-280 Torres Vedras, PortugalCNS—Campus Neurológico, 2560-280 Torres Vedras, PortugalKinetikos, 3030-199 Coimbra, PortugalKinetikos, 3030-199 Coimbra, PortugalCNS—Campus Neurológico, 2560-280 Torres Vedras, PortugalChampalimaud Research, Champalimaud Centre for the Unknown, 1400 Lisbon, PortugalChampalimaud Research, Champalimaud Centre for the Unknown, 1400 Lisbon, PortugalInstituto de Medicina Molecular, 1649-028 Lisbon, PortugalMobile health (mHealth) has emerged as a potential solution to providing valuable ecological information about the severity and burden of Parkinson’s disease (PD) symptoms in real-life conditions. <b>Objective</b>: The objective of our study was to explore the feasibility and usability of an mHealth system for continuous and objective real-life measures of patients’ health and functional mobility, in unsupervised settings. <b>Methods</b>: Patients with a clinical diagnosis of PD, who were able to walk unassisted, and had an Android smartphone were included. Patients were asked to answer a daily survey, to perform three weekly active tests, and to perform a monthly in-person clinical assessment. Feasibility and usability were explored as primary and secondary outcomes. An exploratory analysis was performed to investigate the correlation between data from the mKinetikos app and clinical assessments. <b>Results</b>: Seventeen participants (85%) completed the study. Sixteen participants (94.1%) showed a medium-to-high level of compliance with the mKinetikos system. A 6-point drop in the total score of the Post-Study System Usability Questionnaire was observed. <b>Conclusions</b>: Our results support the feasibility of the mKinetikos system for continuous and objective real-life measures of a patient’s health and functional mobility. The observed correlations of mKinetikos metrics with clinical data seem to suggest that this mHealth solution is a promising tool to support clinical decisions.https://www.mdpi.com/1424-8220/21/15/4972Parkinson’s diseasedigital healthremote monitoringsensorswearable technology |
| spellingShingle | Raquel Bouça-Machado Filipa Pona-Ferreira Mariana Leitão Ana Clemente Diogo Vila-Viçosa Linda Azevedo Kauppila Rui M. Costa Ricardo Matias Joaquim J. Ferreira Feasibility of a Mobile-Based System for Unsupervised Monitoring in Parkinson’s Disease Sensors Parkinson’s disease digital health remote monitoring sensors wearable technology |
| title | Feasibility of a Mobile-Based System for Unsupervised Monitoring in Parkinson’s Disease |
| title_full | Feasibility of a Mobile-Based System for Unsupervised Monitoring in Parkinson’s Disease |
| title_fullStr | Feasibility of a Mobile-Based System for Unsupervised Monitoring in Parkinson’s Disease |
| title_full_unstemmed | Feasibility of a Mobile-Based System for Unsupervised Monitoring in Parkinson’s Disease |
| title_short | Feasibility of a Mobile-Based System for Unsupervised Monitoring in Parkinson’s Disease |
| title_sort | feasibility of a mobile based system for unsupervised monitoring in parkinson s disease |
| topic | Parkinson’s disease digital health remote monitoring sensors wearable technology |
| url | https://www.mdpi.com/1424-8220/21/15/4972 |
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