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A Long-Term, Real-Life Parkinson Monitoring Database Combining Unscripted Objective and Subjective Recordings

Author

Listed:
  • Jeroen G. V. Habets

    (Department of Neurosurgery, School for Mental Health and Neurosciences, Faculty of Health, Medicine and Life Sciences, Maastricht University, 6229 ER Maastricht, The Netherlands)

  • Margot Heijmans

    (Department of Neurosurgery, School for Mental Health and Neurosciences, Faculty of Health, Medicine and Life Sciences, Maastricht University, 6229 ER Maastricht, The Netherlands)

  • Albert F. G. Leentjens

    (Department of Psychiatry and Neuropsychology, School for Mental Health and Neurosciences, Faculty of Health, Medicine and Life Sciences, 6229 ER Maastricht, The Netherlands)

  • Claudia J. P. Simons

    (Department of Psychiatry and Neuropsychology, School for Mental Health and Neurosciences, Faculty of Health, Medicine and Life Sciences, 6229 ER Maastricht, The Netherlands
    GGzE (Mental Healthcare Eindhoven), 5626 ND Eindhoven, The Netherlands)

  • Yasin Temel

    (Department of Neurosurgery, School for Mental Health and Neurosciences, Faculty of Health, Medicine and Life Sciences, Maastricht University, 6229 ER Maastricht, The Netherlands)

  • Mark L. Kuijf

    (Department of Neurology, School for Mental Health and Neurosciences, Faculty of Health, Medicine and Life Sciences, Maastricht University, 6229 ER Maastricht, The Netherlands)

  • Pieter L. Kubben

    (Department of Neurosurgery, School for Mental Health and Neurosciences, Faculty of Health, Medicine and Life Sciences, Maastricht University, 6229 ER Maastricht, The Netherlands)

  • Christian Herff

    (Department of Neurosurgery, School for Mental Health and Neurosciences, Faculty of Health, Medicine and Life Sciences, Maastricht University, 6229 ER Maastricht, The Netherlands)

Abstract

Accurate real-life monitoring of motor and non-motor symptoms is a challenge in Parkinson’s disease (PD). The unobtrusive capturing of symptoms and their naturalistic fluctuations within or between days can improve evaluation and titration of therapy. First-generation commercial PD motion sensors are promising to augment clinical decision-making in general neurological consultation, but concerns remain regarding their short-term validity, and long-term real-life usability. In addition, tools monitoring real-life subjective experiences of motor and non-motor symptoms are lacking. The dataset presented in this paper constitutes a combination of objective kinematic data and subjective experiential data, recorded parallel to each other in a naturalistic, long-term real-life setting. The objective data consists of accelerometer and gyroscope data, and the subjective data consists of data from ecological momentary assessments. Twenty PD patients were monitored without daily life restrictions for fourteen consecutive days. The two types of data can be used to address hypotheses on naturalistic motor and/or non-motor symptomatology in PD.

Suggested Citation

  • Jeroen G. V. Habets & Margot Heijmans & Albert F. G. Leentjens & Claudia J. P. Simons & Yasin Temel & Mark L. Kuijf & Pieter L. Kubben & Christian Herff, 2021. "A Long-Term, Real-Life Parkinson Monitoring Database Combining Unscripted Objective and Subjective Recordings," Data, MDPI, vol. 6(2), pages 1-12, February.
    • Handle: RePEc:gam:jdataj:v:6:y:2021:i:2:p:22-:d:504391
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