Development of a Tremor Detection Algorithm for use in an Academic Movement Disorders Center

Abstract: Tremor, defined as an "involuntary, rhythmic, oscillatory movement of a body part," is a key feature of many neurological conditions, but is still clinically assessed by visual observation. Methodologies for objectively quantifying tremor are promising but remain non-standardized across centers. Our center performs full-body behavioral testing with 3D motion capture for clinical and research purposes for patients with Parkinson's disease, essential tremor, and other conditions. The objective of this study was to assess the ability of several candidate processing pipelines to identify the presence or absence of tremor in kinematic data from movement disorders patients compared to expert ratings from movement disorders specialists. We curated a database of 2,272 separate kinematic data recordings from our center, each of which was contemporaneously annotated as tremor present or absent by a clinical provider. We compared the ability of six separate processing pipelines to recreate clinician ratings based on F1 score, in addition to accuracy, precision, and recall. We found generally comparable performance across algorithms. The average F1 score was 0.84 0.02 (Mean ISD; range 0.81 - 0.87), with all F1 confidence intervals overlapping. The highest performing algorithm (cross-validated F1 = 0.87) was a hybrid that used engineered features adapted from an algorithm in longstanding clinical use with a modern Support Vector Machine classifier. Taken together, our results suggest the potential to update legacy clinical decision support systems to incorporate modern machine learning classifiers in order to create better performing tools. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study was funded by philanthropic funds to author SAF ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of Emory University under IRB protocol 00002688 approved June 2, 2021. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors