MDS Abstracts

Abstracts from the International Congress of Parkinson’s and Movement Disorders.

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  • MDS Virtual Congress 2021

    Sleep assessment with Fitbit4 in Parkinson’s disease

    S. Diaconu, L. Ungureanu, R. Rancz, B. Ciopleiaș, L. Irincu, I. Ivan, C. Falup-Pecurariu (Brasov, Romania)

    Objective: The aim of this study is to evaluate the sleep characteristics in PD patients using Fitbit4, as a wearable objective measure of sleep for…
  • MDS Virtual Congress 2021

    PKG for the management of advance Parkinson’s Disease

    S. Duja (Dudley, United Kingdom)

    Objective: Is PKG an effective way of monitoring advanced PD patients? Is it cost effective? Can PKG be used to review and manage patients virtually? Can PKG…
  • MDS Virtual Congress 2021

    FOG-IT – Towards Personalized Freezing of Gait detection using Artificial Intelligence

    B. Filtjens, N. Ghosh, P. Slaets, B. Vanrumste, A. Nieuwboer, P. Ginis (Leuven, Belgium)

    Objective: Validate a novel software platform to measure freezing of gait using a modular build-up from 1) basic algorithm, to 2) integration of wearable sensor…
  • MDS Virtual Congress 2021

    Is there a place for virtual support groups for Parkinson’s disease in Africa? Lessons from the Covid-19 pandemic

    N. Fothergill-Misbah, J. Price, O. Thomas, J. Okeno, R. Walker, L. Ebenezer (Newcastle Upon Tyne, United Kingdom)

    Objective: Using a case study from Kenya to understand the potential role of virtual support groups for Parkinson’s disease (PD) in Africa. Background: The Covid-19…
  • MDS Virtual Congress 2021

    Co-designing a meaningful, humane and personalized eHealth platform (eCARE-PD) for people living with Parkinson’s Disease

    S. Grosjean, JL. Ciocca, E. Poitras, A. Gauthier-Beaupré, D. Côté, D. Grimes, T. Mestre (Ottawa, Canada)

    Objective: To design a personalized eHealth platform to support self-care and promote integrated care for people living with Parkinson's Disease (PwP). Background: There is evidence…
  • MDS Virtual Congress 2021

    Metadata standards to support deployment of Digital Health Technologies in Clinical Trials in Parkinson’s Disease (PD)

    D. Hill, D. Stephenson, J. Brayanov, K. Claes, R. Badawy, S. Sardar, K. Fisher, S. Lee, A. Bannon, V. Terebaite, R. Bhatnagar (St Pierre Dechartreuse, France)

    Objective: A metadata framework for Digital Health Technologies (DHT) to support enhanced regulatory maturity, and to facilitate standardization and harmonization of data collection Background: DHTs…
  • MDS Virtual Congress 2021

    Adding environmental context to passive wearable sensor data

    D. Hill, T. Tran, T. Le, N. Defranoux, A. Devaux, A. Castillejo, V. Janousek (Grenoble, France)

    Objective: To reduce variability in home based wearable sensor measures by automatically adding environmental context using wireless beacons. Background: Wearable sensors can provide continuous quantification…
  • MDS Virtual Congress 2021

    A Machine Learning Approach to VTA Prediction in DBS

    B. Hoenes, G. Steinke (Valencia, USA)

    Objective: This study aims to evaluate a novel, machine learning approach to volume of activation (VTA) prediction for real-time use in the clinical setting and…
  • MDS Virtual Congress 2021

    Validity of quantitative parameters for analyzing gait motion in PD patients after STN-DBS

    J. Ide, K. Goto, T. Sugi (Fukuoka, Japan)

    Objective: The validity of parameters for quantitative assessment of gait movement characteristics specific to Parkinson's disease (PD) patients was tested with data from STN-DBS On/Off.…
  • MDS Virtual Congress 2021

    Technology-based adaptation of a natural history study of Parkinson disease during the COVID-19 pandemic

    S. Jensen-Roberts, E. Waddell, T. Myers, M. Pawlik, J. Soto, A. Sarkar, M. Coffey, E. Stevenson, R. Wilson, E. Dorsey, K. Lizarraga, C. Tarolli, R. Schneider, J. Adams (Rochester, USA)

    Objective: To describe the transition of a novel study in Parkinson disease (PD) evaluating four technologies—the mPower 2.0 smartphone application, MC10 wearable BioStamp nPoint® sensors,…
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