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

J.G.V. Habets*, M. Heijmans, A.F.G. Leentjens, C.J.P. Simons, Y. Temel, M.L. Kuijf, P.L. Kubben, C. Herff

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


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.
Original languageEnglish
Article number22
Number of pages12
Issue number2
Publication statusPublished - 1 Feb 2021


  • Parkinson's disease
  • ecological momentary assessments
  • experience sampling method
  • motor diaries
  • naturalistic monitoring
  • parkinson's disease
  • real-life
  • unscripted
  • wearable sensors


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