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@ARTICLE{vanderLinden:1018539,
      author       = {van der Linden, Christina and Berger, Thea and Brandt,
                      Gregor A. and Strelow, Joshua N. and Jergas, Hannah and
                      Baldermann, Juan Carlos and Visser-Vandewalle, Veerle and
                      Fink, Gereon Rudolf and Barbe, Michael T. and
                      Petry-Schmelzer, Jan Niklas and Dembek, Till A.},
      title        = {{A}ccelerometric {C}lassification of {R}esting and
                      {P}ostural {T}remor {A}mplitude},
      journal      = {Sensors},
      volume       = {23},
      number       = {20},
      issn         = {1424-8220},
      address      = {Basel},
      publisher    = {MDPI},
      reportid     = {FZJ-2023-04867},
      pages        = {8621 -},
      year         = {2023},
      abstract     = {Clinical rating scales for tremors have significant
                      limitations due to low resolution, high rater dependency,
                      and lack of applicability in outpatient settings. Reliable,
                      quantitative approaches for assessing tremor severity are
                      warranted, especially evaluating treatment effects, e.g., of
                      deep brain stimulation (DBS). We aimed to investigate how
                      different accelerometry metrics can objectively classify
                      tremor amplitude of Essential Tremor (ET) and tremor in
                      Parkinson's Disease (PD). We assessed 860 resting and
                      postural tremor trials in 16 patients with ET and 25
                      patients with PD under different DBS settings. Clinical
                      ratings were compared to different metrics, based on either
                      spectral components in the tremorband or pure acceleration,
                      derived from simultaneous triaxial accelerometry captured at
                      the index finger and wrist. Nonlinear regression was applied
                      to a training dataset to determine the relationship between
                      accelerometry and clinical ratings, which was then evaluated
                      in a holdout dataset. All of the investigated accelerometry
                      metrics could predict clinical tremor ratings with a high
                      concordance $(>70\%)$ and substantial interrater reliability
                      (Cohen's weighted Kappa > 0.7) in out-of-sample data.
                      Finger-worn accelerometry performed slightly better than
                      wrist-worn accelerometry. We conclude that triaxial
                      accelerometry reliably quantifies resting and postural
                      tremor amplitude in ET and PD patients. A full release of
                      our dataset and software allows for implementation,
                      development, training, and validation of novel
                      methods.Keywords: Parkinson’s Disease; accelerometry;
                      essential tremor; tremor; wearables.},
      cin          = {INM-3},
      ddc          = {620},
      cid          = {I:(DE-Juel1)INM-3-20090406},
      pnm          = {5251 - Multilevel Brain Organization and Variability
                      (POF4-525) / DFG project 502436811 - Prospektive Evaluation
                      der Bestimmung des effektivsten Kontaktes mittels
                      individueller Traktographie zur Kontrolle des Tremors bei
                      Patienten mit Tiefer Hirnstimulation (TremTract Studie)
                      (502436811)},
      pid          = {G:(DE-HGF)POF4-5251 / G:(GEPRIS)502436811},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {37896714},
      UT           = {WOS:001099382400001},
      doi          = {10.3390/s23208621},
      url          = {https://juser.fz-juelich.de/record/1018539},
}