Developing a Tool for Remote Digital Assessment of Parkinson's Disease
Panagiotis Kassavetis,Panagiotis Kassavetis,Tabish A. Saifee,George Roussos,L Drougkas,Maja Kojovic,John C. Rothwell,Mark J. Edwards,Kailash P. Bhatia +8 more
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TLDR
The first report on the development and testing of stand‐alone software for mobile devices that could be used to assess both tremor and bradykinesia of PD patients is provided.Abstract:
BACKGROUND: The natural fluctuation of motor symptoms of Parkinson's disease (PD) makes judgement of any change challenging and the use of clinical scales such as the International Parkinson and Movement Disorder Society (MDS)-UPDRS imperative. Recently developed commodity mobile communication devices, such as smartphones, could possibly be used to assess motor symptoms in PD patients in a convenient way with low cost. We provide the first report on the development and testing of stand-alone software for mobile devices that could be used to assess both tremor and bradykinesia of PD patients.
METHODS: We assessed motor symptoms with a custom-made smartphone application in 14 patients and compared the results with their MDS-UPDRS scores.
RESULTS: We found significant correlation between five subscores of MDS-UPDRS (rest tremor, postural tremor, pronation-supination, leg agility, and finger tapping) and eight parameters of the data collected with the smartphone.
CONCLUSIONS: These results provide evidence as a proof of principle that smartphones could be a useful tool to objectively assess motor symptoms in PD in clinical and experimental settings.read more
Citations
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Evaluation of smartphone-based testing to generate exploratory outcome measures in a phase 1 Parkinson's disease clinical trial.
Florian Lipsmeier,Kirsten I. Taylor,Timothy Kilchenmann,Detlef Wolf,Alf Scotland,Jens Schjodt-Eriksen,Wei-Yi Cheng,Ignacio Fernandez‐Garcia,Juliane Siebourg-Polster,Liping Jin,Jay Soto,Lynne Verselis,Frank G. Boess,Martin Koller,Michael Grundman,Andreas U. Monsch,Ronald B. Postuma,Anirvan Ghosh,Thomas Kremer,Christian Czech,Christian Gossens,Michael Lindemann +21 more
TL;DR: This research presents a new domain of digital biomarkers, where smartphone sensors promise to fundamentally change biomedical research and treatment monitoring in neurological diseases such as PD, creating a new Domain of Digital biomarkers.
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A review of physiological and behavioral monitoring with digital sensors for neuropsychiatric illnesses
TL;DR: Recent studies utilizing context-aware and physiologically relevant digital sensors in consumer technology in the context of neuropsychiatric illnesses including stress and depression, bipolar disorder, schizophrenia, post traumatic stress disorder, Alzheimer's disease, and Parkinson's disease are reviewed.
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Big data in Parkinson's disease: using smartphones to remotely detect longitudinal disease phenotypes.
TL;DR: This study tries to tackle some of the major challenges associated with self-assessed severity labels by designing and validating features extracted from big datasets in PD, which could help identify digital biomarkers capable of providing measures of disease severity outside of a clinical environment.
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Technologies Assessing Limb Bradykinesia in Parkinson’s Disease
TL;DR: This review provides an up-to-date repository and synthesis of the current literature regarding technology used for assessing limb bradykinesia in PD and discusses the current trends with regards to technology.
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Intelligent cyber-physical system for an efficient detection of Parkinson disease using fog computing
Malathi Devarajan,Logesh Ravi +1 more
TL;DR: An intelligent system for detecting Parkinson’s disease to provide proper medication by analysing voice samples using Fog computing as a midway layer between end devices and the cloud server is proposed.
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Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS): scale presentation and clinimetric testing results.
Christopher G. Goetz,Barbara C. Tilley,Stephanie R. Shaftman,Glenn T. Stebbins,Stanley Fahn,Pablo Martinez-Martin,Werner Poewe,Cristina Sampaio,Matthew B. Stern,Richard Dodel,Bruno Dubois,Robert G. Holloway,Joseph Jankovic,Jaime Kulisevsky,Anthony E. Lang,Andrew J. Lees,Sue Leurgans,Peter A. LeWitt,David L. Nyenhuis,C. Warren Olanow,Olivier Rascol,Anette Schrag,Jeanne A. Teresi,Jacobus J. van Hilten,Nancy R. LaPelle,Pinky Agarwal,Saima Athar,Yvette Bordelan,Helen Bronte-Stewart,Richard Camicioli,Kelvin L. Chou,Wendy Cole,Arif Dalvi,Holly Delgado,Alan Diamond,Jeremy P.R. Dick,John E. Duda,Rodger J. Elble,Carol Evans,V. G. H. Evidente,Hubert H. Fernandez,Susan H. Fox,Joseph H. Friedman,Robin D. Fross,David A. Gallagher,Deborah A. Hall,Neal Hermanowicz,Vanessa K. Hinson,Stacy Horn,Howard I. Hurtig,Un Jung Kang,Galit Kleiner-Fisman,Olga Klepitskaya,Katie Kompoliti,Eugene C. Lai,Maureen L. Leehey,Iracema Leroi,Kelly E. Lyons,Terry McClain,Steven W. Metzer,Janis M. Miyasaki,John C. Morgan,Martha Nance,Joanne Nemeth,Rajesh Pahwa,Sotirios A. Parashos,Jay S. Schneider,Kapil D. Sethi,Lisa M. Shulman,Andrew Siderowf,Monty Silverdale,Tanya Simuni,Mark Stacy,Robert Malcolm Stewart,Kelly L. Sullivan,David M. Swope,Pettaruse M. Wadia,Richard Walker,Ruth H. Walker,William J. Weiner,Jill Wiener,Jayne R. Wilkinson,Joanna M. Wojcieszek,Summer C. Wolfrath,Frederick Wooten,Allen Wu,Theresa A. Zesiewicz,Richard M. Zweig +87 more
TL;DR: The combined clinimetric results of this study support the validity of the MDS‐UPDRS for rating PD.
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What features improve the accuracy of clinical diagnosis in Parkinson's disease A clinicopathologic study
TL;DR: Assessment of clinical features of 100 patients diagnosed prospectively by a group of consultant neurologists as having idiopathic Parkinson's disease suggests that studies based on consultant diagnosis of PD, using standard diagnostic criteria, will include cases other than PD, thus distorting results from clinical trials and epidemiologic studies.
Proceedings ArticleDOI
Implementation of an iPhone for characterizing Parkinson's disease tremor through a wireless accelerometer application
TL;DR: The initial testing and evaluation of the iPhone wireless accelerometer application for quantifying Parkinson's disease tremor successfully demonstrates the capacity to acquire tremor characteristics in an effectively autonomous environment, while potentially alleviating strain on limited and highly specialized medical resources.
Journal ArticleDOI
Epidemiology, diagnosis and differential diagnosis in Parkinson's disease tremor
TL;DR: The epidemiology of tremor in Parkinson's disease is not well examined, and patients with a predominant tremor phenotype may have a more favourable prognosis in terms of mortality and the development of motor and non-motor complications.
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