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

Jeroen G. V. Habets, Margot Heijmans, Albert F. G. Leentjens, Claudia J. P. Simons, Yasin Temel, Mark L. Kuijf, Pieter L. Kubben and Christian Herff
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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
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

Data, 2021, vol. 6, issue 2, 1-12

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.

Keywords: Parkinson’s disease; real-life; unscripted; naturalistic monitoring; wearable sensors; motor diaries; ecological momentary assessments; experience sampling method (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2021
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