MDS Abstracts

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

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  • 2018 International Congress

    Comparison of quantitative analysis of finger and forearm movements between early stage Parkinson’s disease and scans without evidence of dopaminergic deficit (SWEDD)

    D.Y. Kwon, M.H. Park, J.W. Kim (Ansan-city, Republic of Korea)

    Objective: The aim of this study was to compare detailed presentations of hand movement by using an angular measurement system with gyrosensors in PD, SWEDDs…
  • 2018 International Congress

    Facial Movement Analysis in Parkinson’s disease: A decade of advances

    W. Rattanachaisit, R. Bhidayasiri (Bangkok, Thailand)

    Objective: To review advances in the analysis of the characteristics and pathophysiology of facial movement abnormalities in PD. Background: Hypomimia, a reduction or absence of…
  • 2018 International Congress

    Feasibility of a multi-sensor data fusion method for assessment of Parkinson’s disease motor symptoms

    M. Memedi, S. Aghanavesi, D. Nyholm, F. Bergquist, M. Senek (Örebro, Sweden)

    Objective: To assess the feasibility of measuring Parkinson’s disease (PD) motor symptoms with a multi-sensor data fusion method. More specifically, the aim is to assess…
  • 2018 International Congress

    Assessment of Motor Symptoms in Parkinson’s disease using Flexible Wearable Sensors and Deep Neural Networks: A CIS-PD substudy

    L. Lonini, A. Dai, C. Poon, N. Shawen, L. Shimanovich, T. Simuni, D. Daeschler, J. Rogers, A. Jayaraman (Chicago, IL, USA)

    Objective: To develop an algorithm to characterize in-office motor symptoms of Parkinson’s disease (PD) using multiple wireless sensors, and to compare symptom recognition in activities…
  • 2018 International Congress

    An automated algorithm for detection and quantification of tremor from pen-on-paper Archimedes spirals

    R. Rajan, A. R, A. Pandit, V. Venugopalan, D. Vibha, S. Krishnan, A. Srivastava, K. Prasad, A. Kishore (New Delhi, India)

    Objective: 1) To compare variables derived from pen-on-paper spirals using an automated algorithm with clinical rating scales for tremor. 2) To analyse the diagnostic utility…
  • 2018 International Congress

    Developing a Self-Administered Instrumented Motor Exam for Home-based Parkinson’s Disease Assessment Using Wearable Sensors

    S. Patel, C. Demanuele, B. Ho, P. Wacnik, H. Zhang, T. Kangarloo, V. Ramos, S. Amato, D. Volfson, P. Bergethon, M. Erb (Cambridge, MA, USA)

    Objective: To develop a self-administered instrumented motor exam enabling remote measurement of Parkinson’s Disease (PD) signs. Background: Current methods for PD assessment in clinical trials…
  • 2018 International Congress

    Improving clinical data collection at patients’ home in Parkinson’s disease: The Sleep Fit app

    A. Mascheroni, C. Ferlito, S. Hackethal, S. Caverzasio, E-K. Choe, Y. Luo, F. Faraci, A. Kaelin-Lang, A. Puiatti, P-L. Ratti, M. Marazza (Manno, Switzerland)

    Objective: We introduce Sleep Fit, the first tablet application to collect subjective and objective clinical data especially designed for patients with Parkinson’s Disease (PD). Background:…
  • 2018 International Congress

    Tracking RBD and PD progression with longitudinal structural brain connectomes

    J. Suescun, O. Peña Nogales, T. Ellmore, R. de Luis-Garcia, M. Schiess, L. Giancardo (Houston, TX, USA)

    Objective: To compare longitudinal structural connectomes derived from whole brain dMRI and PD clinical rating scales as a disease progression biomarker, on three cohorts: de-novo…
  • 2018 International Congress

    Safety and efficacy of high definition tDCS for proprioception and balance in Parkinson’s disease: A pilot randomised trial

    H. Teasdale, E. Preston, A. Flood, G. Waddington (Canberra, Australia)

    Objective: To determine: 1. Is HD-tDCS safe and well-tolerated in PD? 2. Does combined HD-tDCS and physical exercise improve proprioception and balance in PD? Background:…
  • 2018 International Congress

    Objective monitoring of drug response in early PD patients using remote, at-home typing data through machine learning analysis

    M. Matarazzo, T. Arroyo-Gallego, P. Montero Escribano, V. Puertas-Martín, I. Butterworth, C. S. Mendoza, MJ. Ledesma-Carbayo, MJ. Catalán, JA. Molina-Arjona, F. Bermejo-Pareja, JC. Martínez Castrillo, L. López-Manzanares, A. Alonso-Cánovas, J. Herreros-Rodríguez, I. Obeso, P. Martínez Martín, JC. Martínez-Ávila, A. Gómez de-la-Cámara, M. Gray, JA. Obeso, L. Giancardo, Á. Sánchez-Ferro (Vancouver, BC, Canada)

    Objective: We designed an algorithm to detect response to medication in an early PD population using at-home, unsupervised, unobtrusive typing data. Background: Advances in technology…
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