Smartphone Applications in the Management of Parkinson's Disease in a Family Setting: An Opinion Article

Zhang, Ting; Dong, Li; Hua, Jing; Gao, Song

doi:10.3389/fneur.2021.668953

Cited by 4 publications

(3 citation statements)

References 52 publications

(53 reference statements)

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“…Although some studies have been performed in the real world (ie, daily living, outside clinical or laboratory settings),17 18 a more granular picture is required. Digital health technology (DHT) presents the tools to explore this, by allowing for the continuous assessment of medication adherence and mobility (digital mobility outcomes, DMOs) in the real world 5 19–22. A variety of DMOs can be used to assess mobility; and of primary interest is walking speed 23.…”

Section: Introductionmentioning

confidence: 99%

Translating digital healthcare to enhance clinical management: a protocol for an observational study using a digital health technology system to monitor medication adherence and its effect on mobility in people with Parkinson’s

Packer,

Debelle,

Bailey

et al. 2023

BMJ Open

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IntroductionIn people with Parkinson’s (PwP) impaired mobility is associated with an increased falls risk. To improve mobility, dopaminergic medication is typically prescribed, but complex medication regimens result in suboptimal adherence. Exploring medication adherence and its impact on mobility in PwP will provide essential insights to optimise medication regimens and improve mobility. However, this is typically assessed in controlled environments, during one-off clinical assessments. Digital health technology (DHT) presents a means to overcome this, by continuously and remotely monitoring mobility and medication adherence. This study aims to use a novel DHT system (DHTS) (comprising of a smartphone, smartwatch and inertial measurement unit (IMU)) to assess self-reported medication adherence, and its impact on digital mobility outcomes (DMOs) in PwP.Methods and analysisThis single-centre, UK-based study, will recruit 55 participants with Parkinson’s. Participants will complete a range of clinical, and physical assessments. Participants will interact with a DHTS over 7 days, to assess self-reported medication adherence, and monitor mobility and contextual factors in the real world. Participants will complete a motor complications diary (ON-OFF-Dyskinesia) throughout the monitoring period and, at the end, a questionnaire and series of open-text questions to evaluate DHTS usability. Feasibility of the DHTS and the motor complications diary will be assessed. Validated algorithms will quantify DMOs from IMU walking activity. Time series modelling and deep learning techniques will model and predict DMO response to medication and effects of contextual factors. This study will provide essential insights into medication adherence and its effect on real-world mobility in PwP, providing insights to optimise medication regimens.Ethics and disseminationEthical approval was granted by London—142 Westminster Research Ethics Committee (REC: 21/PR/0469), protocol V.2.4. Results will be published in peer-reviewed journals. All participants will provide written, informed consent.Trial registration numberISRCTN13156149.

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Section: Introductionmentioning

confidence: 99%

Translating digital healthcare to enhance clinical management: a protocol for an observational study using a digital health technology system to monitor medication adherence and its effect on mobility in people with Parkinson’s

Packer,

Debelle,

Bailey

et al. 2023

BMJ Open

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“…The remote monitoring of PD symptoms has become increasingly common because it can allow patients to self-manage their condition at home [24][25][26]. Digital technologies allow for the at-home monitoring of patients through smart devices, sensors, and other tools.…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence Applications for Assessment, Monitoring, and Management of Parkinson Disease Symptoms: Protocol for a Systematic Review

Bounsall¹,

Milne‐Ives²,

Hall³

et al. 2023

JMIR Res Protoc

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Background Parkinson disease (PD) is the second most prevalent neurodegenerative disease, with around 10 million people with PD worldwide. Current assessments of PD symptoms are conducted by questionnaires and clinician assessments and have many limitations, including unreliable reporting of symptoms, little autonomy for patients over their disease management, and standard clinical review intervals regardless of disease status or clinical need. To address these limitations, digital technologies including wearable sensors, smartphone apps, and artificial intelligence (AI) methods have been implemented for this population. Many reviews have explored the use of AI in the diagnosis of PD and management of specific symptoms; however, there is limited research on the application of AI to the monitoring and management of the range of PD symptoms. A comprehensive review of the application of AI methods is necessary to address the gap of high-quality reviews and highlight the developments of the use of AI within PD care. Objective The purpose of this protocol is to guide a systematic review to identify and summarize the current applications of AI applied to the assessment, monitoring, and management of PD symptoms. Methods This review protocol was structured using the PRISMA-P (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols) and the Population, Intervention, Comparator, Outcome, and Study (PICOS) frameworks. The following 5 databases will be systematically searched: PubMed, IEEE Xplore, Institute for Scientific Information’s Web of Science, Scopus, and the Cochrane Library. Title and abstract screening, full-text review, and data extraction will be conducted by 2 independent reviewers. Data will be extracted into a predetermined form, and any disagreements in screening or extraction will be discussed. Risk of bias will be assessed using the Cochrane Collaboration Risk of Bias 2 tool for randomized trials and the Mixed Methods Appraisal Tool for nonrandomized trials. Results As of April 2023, this systematic review has not yet been started. It is expected to begin in May 2023, with the aim to complete by September 2023. Conclusions The systematic review subsequently conducted as a product of this protocol will provide an overview of the AI methods being used for the assessment, monitoring, and management of PD symptoms. This will identify areas for further research in which AI methods can be applied to the assessment or management of PD symptoms and could support the future implementation of AI-based tools for the effective management of PD. International Registered Report Identifier (IRRID) PRR1-10.2196/46581

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“…At present, China's population is aging, and the incidence of chronic diseases is increasing year by year. Society and the government are facing major public health challenges ( 4 , 5 ). The government issued policies aimed at improving citizens' health and effectively controlling the development of chronic diseases.…”

Section: Introductionmentioning

confidence: 99%

The implementation of “integration of sports and medicine” in China: Its limitation and recommendations for model improvement

Zhang

Ning

Liu³

et al. 2022

Front. Public Health

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The “integration of sports and medicine” (ISM) under the “Healthy China 2030” strategy can alleviate the contradiction between residents' health needs and medical supply. Under the “Healthy China 2030” strategy, the government-initiated calls and measures for the integration of sports and medical institutions based on the actual region conditions. This article outlines the “Sports-Medical Integration” program implemented in the coastal cities of China's southeast, Suzhou and Shanghai. We described the specific implementation modes and related deficiencies of the ISM, taking Suzhou and Shanghai as examples. Through three policy recommendations, we put forward the idea of promoting the development of a new model of ISM in China.

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Smartphone Applications in the Management of Parkinson's Disease in a Family Setting: An Opinion Article

Cited by 4 publications

References 52 publications

Translating digital healthcare to enhance clinical management: a protocol for an observational study using a digital health technology system to monitor medication adherence and its effect on mobility in people with Parkinson’s

Translating digital healthcare to enhance clinical management: a protocol for an observational study using a digital health technology system to monitor medication adherence and its effect on mobility in people with Parkinson’s

Artificial Intelligence Applications for Assessment, Monitoring, and Management of Parkinson Disease Symptoms: Protocol for a Systematic Review

The implementation of “integration of sports and medicine” in China: Its limitation and recommendations for model improvement

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