title: A Validation Study of a Smartphone-Based Finger Tapping Application for Quantitative Assessment of Bradykinesia in Parkinson's Disease.
abstract: BACKGROUND
  Most studies of smartphone-based assessments of motor symptoms in Parkinson's disease (PD) focused on gait, tremor or speech. Studies evaluating bradykinesia using wearable sensors are limited by a small cohort size and study design. We developed an application named smartphone tapper (SmT) to determine its applicability for clinical purposes and compared SmT parameters to current standard methods in a larger cohort.
  
  
  METHODS
  A total of 57 PD patients and 87 controls examined with motor UPDRS underwent timed tapping tests (TT) using SmT and mechanical tappers (MeT) according to CAPSIT-PD. Subjects were asked to alternately tap each side of two rectangles with an index finger at maximum speed for ten seconds. Kinematic measurements were compared between the two groups.
  
  
  RESULTS
  The mean number of correct tapping (MCoT), mean total distance of finger movement (T-Dist), mean inter-tap distance, and mean inter-tap dwelling time (IT-DwT) were significantly different between PD patients and controls. MCoT, as assessed using SmT, significantly correlated with motor UPDRS scores, bradykinesia subscores and MCoT using MeT. Multivariate analysis using the SmT parameters, such as T-Dist or IT-DwT, as predictive variables and age and gender as covariates demonstrated that PD patients were discriminated from controls. ROC curve analysis of a regression model demonstrated that the AUC for T-Dist was 0.92 (95% CI 0.88-0.96).
  
  
  CONCLUSIONS
  Our results suggest that a smartphone tapping application is comparable to conventional methods for the assessment of motor dysfunction in PD and may be useful in clinical practice.
authors.affiliation: Department of Neurology, Hallym University Sacred Heart hospital, Hallym University College of Medicine, Hallym University, Anyang, Korea.
authors.forename: Chae Young
authors.initials: CY
authors.lastname: Lee
authors.affiliation: Department of Electronic Engineering, Hallym University, Chuncheon, Korea.
authors.forename: Seong Jun
authors.initials: SJ
authors.lastname: Kang
authors.affiliation: Hallym Institute of Translational Genomics & Bioinformatics, Hallym University Medical Center, Anyang, Korea.
authors.forename: Sang-Kyoon
authors.initials: SK
authors.lastname: Hong
authors.affiliation: Department of Neurology, Hallym University Sacred Heart hospital, Hallym University College of Medicine, Hallym University, Anyang, Korea.
authors.forename: Hyeo-Il
authors.initials: HI
authors.lastname: Ma
authors.affiliation: Department of Electronic Engineering, Hallym University, Chuncheon, Korea.
authors.forename: Unjoo
authors.initials: U
authors.lastname: Lee
authors.affiliation: Department of Neurology, Hallym University Sacred Heart hospital, Hallym University College of Medicine, Hallym University, Anyang, Korea.|Hallym Institute of Translational Genomics & Bioinformatics, Hallym University Medical Center, Anyang, Korea.|ILSONG Institute of Life Science, Hallym University, Anyang, Korea.
authors.forename: Yun Joong
authors.identifier: http://orcid.org/0000-0002-2956-1552
authors.initials: YJ
authors.lastname: Kim
mesh_terms: D000368:Aged; D016022:Case-Control Studies; D005260:Female; D005385:Fingers / Q000503:physiopathology*; D006801:Humans; D018476:Hypokinesia / Q000175:diagnosis* / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D010300:Parkinson Disease / Q000503:physiopathology*; D000068997:Smartphone