Literature DB >> 32937225

Digital phenotyping in Parkinson's disease: Empowering neurologists for measurement-based care.

Roongroj Bhidayasiri1, Zoltan Mari2.   

Abstract

There remains a significant mismatch between the complexity and variability of symptoms and disabilities in Parkinson's disease (PD), and the capabilities of existing validated assessment tools to objectively measure and monitor them. However, with the advances of circuit and sensor technologies, it is now possible to apply the concept of digital phenotyping to PD, providing a moment-by-moment quantification of individual patient phenotypes using personal digital devices, such as smartphones. Such technology holds considerable potential if a patient-centered multidisciplinary team is able to select digital outcomes that are not only clinically relevant, but also provide measurement-based care results that support individual patient clinical decision making. However, it is likely to be a long road, requiring large collaborative efforts to undertake a number of essential steps before full integration and synchronization of these outcomes into patient management platforms that can deliver individualized data to patients, caregivers, and treating neurologists. In the meantime, both neurologists and patients can empower themselves with digital technologies, working as a team to define the ways that new technologies can be most powerfully employed in PD management. Once digital phenotyping becomes feasible and widely adopted in PD communities, it is likely to expand our understanding of individual PD patients' lives and priorities, leading to targeted treatments and better outcomes for PD patients and their families.
Copyright © 2020 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Accelerometer; Digital footprint; Digital phenotyping; Digital technology; Parkinson's disease; Smartphone

Year:  2020        PMID: 32937225     DOI: 10.1016/j.parkreldis.2020.08.038

Source DB:  PubMed          Journal:  Parkinsonism Relat Disord        ISSN: 1353-8020            Impact factor:   4.891


  3 in total

1.  Will Artificial Intelligence Outperform the Clinical Neurologist in the Near Future? Yes.

Authors:  Roongroj Bhidayasiri
Journal:  Mov Disord Clin Pract       Date:  2021-04-12

Review 2.  The Disease Modification Conundrum in Parkinson's Disease: Failures and Hopes.

Authors:  Zoltan Mari; Tiago A Mestre
Journal:  Front Aging Neurosci       Date:  2022-02-28       Impact factor: 5.750

3.  Toward Improved Treatment and Empowerment of Individuals With Parkinson Disease: Design and Evaluation of an Internet of Things System.

Authors:  Liran Karni; Ilir Jusufi; Dag Nyholm; Gunnar Oskar Klein; Mevludin Memedi
Journal:  JMIR Form Res       Date:  2022-06-09
  3 in total

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