title: Robotic measurement of arm movements after stroke establishes biomarkers of motor recovery.
abstract: OBJECTIVE
  Because robotic devices record the kinematics and kinetics of human movements with high resolution, we hypothesized that robotic measures collected longitudinally in patients after stroke would bear a significant relationship to standard clinical outcome measures and, therefore, might provide superior biomarkers.
  
  
  METHODS
  In patients with moderate-to-severe acute ischemic stroke, we used clinical scales and robotic devices to measure arm movement 7, 14, 21, 30, and 90 days after the event at 2 clinical sites. The robots are interactive devices that measure speed, position, and force so that calculated kinematic and kinetic parameters could be compared with clinical assessments.
  
  
  RESULTS
  Among 208 patients, robotic measures predicted well the clinical measures (cross-validated R(2) of modified Rankin scale=0.60; National Institutes of Health Stroke Scale=0.63; Fugl-Meyer=0.73; Motor Power=0.75). When suitably scaled and combined by an artificial neural network, the robotic measures demonstrated greater sensitivity in measuring the recovery of patients from day 7 to day 90 (increased standardized effect=1.47).
  
  
  CONCLUSIONS
  These results demonstrate that robotic measures of motor performance will more than adequately capture outcome, and the altered effect size will reduce the required sample size. Reducing sample size will likely improve study efficiency.
authors: From the Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge (H.I.K., L.D.); Janssen Research & Development, Titusville, NJ (M.K., A.D.B.); Covance, Princeton, NJ (D.K.A., E.Y.); Biogen-Idec, Experimental Medicine, Cambridge, MA (J.C.C.); GSL Statistical Consulting, Ardmore, PA (G.S.L.); BVBA Bioconstat, Gent, Oostakker, Belgium (G.B.); The Burke Medical Research Institute, White Plains, NY (A.R.); Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom (K.M.A., K.H., K.R.L.); Department of Neurology, University of Duisburg-Essen, Essen, Germany (K.H.); and The Feinstein Institute for Medical Research, Manhasset, NY (B.T.V.).
authors: Hermano I
authors: HI
authors: Krebs
authors: Michael
authors: M
authors: Krams
authors: Dimitris K
authors: DK
authors: Agrafiotis
authors: Allitia
authors: A
authors: DiBernardo
authors: Juan C
authors: JC
authors: Chavez
authors: Gary S
authors: GS
authors: Littman
authors: Eric
authors: E
authors: Yang
authors: Geert
authors: G
authors: Byttebier
authors: Laura
authors: L
authors: Dipietro
authors: Avrielle
authors: A
authors: Rykman
authors: Kate
authors: K
authors: McArthur
authors: Karim
authors: K
authors: Hajjar
authors: Kennedy R
authors: KR
authors: Lees
authors: Bruce T
authors: BT
authors: Volpe
mesh_terms: D000368:Aged; D001132:Arm / Q000502:physiology*; D015415:Biomarkers; D001696:Biomechanical Phenomena; D003627:Data Interpretation, Statistical; D023381:Endpoint Determination; D005006:Ethnicity; D005260:Female; D007839:Functional Laterality / Q000502:physiology; D006801:Humans; D008297:Male; D008953:Models, Anatomic; D009068:Movement / Q000502:physiology*; D017711:Nonlinear Dynamics; D011237:Predictive Value of Tests; D020127:Recovery of Function; D015203:Reproducibility of Results; D012371:Robotics; D020521:Stroke / Q000503:physiopathology*; D000071939:Stroke Rehabilitation
chemical_list: D015415:Biomarkers
keywords: biomarkers; motor skills; robotics; sensory motor performance; stroke