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Mov Disord. 2016 Sep;31(9):1272-82. doi: 10.1002/mds.26642. Epub 2016 Apr 29.

Technology in Parkinson's disease: Challenges and opportunities.

Author information

1
James J. and Joan A. Gardner Family Center for Parkinson's disease and Movement Disorders, University of Cincinnati, Cincinnati, Ohio, USA. alberto.espay@uc.edu.
2
Department of Physical Medicine and Rehabilitation, Harvard Medical School, Boston, Massachusetts, USA.
3
Department of Neurosciences, University of California San Diego, La Jolla, CA, USA.
4
Department of Neurodegeneration, Hertie Institute for Clinical Brain Research (HIH), University of Tuebingen, Tübingen, Germany.
5
DZNE, German Center for Neurodegenerative Diseases, Tübingen, Germany.
6
Davis Phinney Foundation for Parkinson's, Boulder, Colorado, USA.
7
Department of Molecular Neurology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany.
8
Digital Sports Group, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany.
9
Department of Neuroscience "Rita Levi Montalcini", Città della salute e della scienza di Torino, Torino, Italy.
10
Department of Neurology, Oregon Health & Science University, Portland VA Medical System, Portland, Oregon.
11
APDM, Inc., Portland, Oregon, USA.
12
Morton and Gloria Movement Disorders Clinic and the Edmond J. Safra Program in Parkinson's Disease, Toronto Western Hospital, Toronto, Canada.
13
George-Huntington-Institute, Muenster, Germany.
14
Department of Radiology, University of Muenster, Muenster, Germany.
15
Department of Neurodegenerative Diseases and Hertie-Institute for Clinical Brain Research, University of Tuebingen, Tuebingen, Germany.
16
Great Lakes NeuroTechnologies, Cleveland, Ohio, USA.
17
Neuromotor Rehabilitation Research Group, Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium.
18
Global Kinetics Corporation & Florey Institute for Neuroscience and Mental Health, University of Melbourne, Parkville, Victoria, Australia.
19
Department of Mathematics, Aston University, Birmingham, UK.
20
Media Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
21
Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA.
22
Department of Neurology, University of Rochester Medical Center, Rochester, New York, USA.
23
Michael J Fox Foundation for Parkinson's Research, New York City, New York, USA.
24
Department of Neurology, National Institute of Clinical Neurosciences, Budapest, Hungary.
25
Center of Interdisciplinary Research Egas Moniz (CiiEM), Instituto Superior de Ciências da Saúde Egas Moniz, Monte de Caparica, Portugal.
26
Apptomics LLC, Wellesley, Massachusetts, USA.
27
Medtronic Neuromodulation, Minneapolis, Minnesota, USA.
28
Sackler School of Medicine, Tel Aviv University and Center for the Study of Movement, Cognition, and Mobility, Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
29
Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Department of Neurology, Nijmegen, the Netherlands.
30
Massachusetts General Hospital, Boston, Massachusetts, USA.

Abstract

The miniaturization, sophistication, proliferation, and accessibility of technologies are enabling the capture of more and previously inaccessible phenomena in Parkinson's disease (PD). However, more information has not translated into a greater understanding of disease complexity to satisfy diagnostic and therapeutic needs. Challenges include noncompatible technology platforms, the need for wide-scale and long-term deployment of sensor technology (among vulnerable elderly patients in particular), and the gap between the "big data" acquired with sensitive measurement technologies and their limited clinical application. Major opportunities could be realized if new technologies are developed as part of open-source and/or open-hardware platforms that enable multichannel data capture sensitive to the broad range of motor and nonmotor problems that characterize PD and are adaptable into self-adjusting, individualized treatment delivery systems. The International Parkinson and Movement Disorders Society Task Force on Technology is entrusted to convene engineers, clinicians, researchers, and patients to promote the development of integrated measurement and closed-loop therapeutic systems with high patient adherence that also serve to (1) encourage the adoption of clinico-pathophysiologic phenotyping and early detection of critical disease milestones, (2) enhance the tailoring of symptomatic therapy, (3) improve subgroup targeting of patients for future testing of disease-modifying treatments, and (4) identify objective biomarkers to improve the longitudinal tracking of impairments in clinical care and research. This article summarizes the work carried out by the task force toward identifying challenges and opportunities in the development of technologies with potential for improving the clinical management and the quality of life of individuals with PD.

KEYWORDS:

Parkinson's disease; digital biomarkers; digital health; eHealth; precision medicine; remote monitoring; technology; wearable technology

PMID:
27125836
PMCID:
PMC5014594
DOI:
10.1002/mds.26642
[Indexed for MEDLINE]
Free PMC Article

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