title: Predicting task performance from upper extremity impairment measures after cervical spinal cord injury.
abstract: BACKGROUND
  Automated sensor-based assessments of upper extremity (UE) function after cervical spinal cord injury (SCI) could provide more detailed tracking of individual recovery profiles than is possible with existing assessments, and optimize the delivery and assessment of new interventions. The design of reliable automated assessments requires identifying the key variables that need to be measured to meaningfully quantify UE function. An unanswered question is to what extent measures of sensorimotor impairment can quantitatively predict performance on functional tasks.
  
  
  OBJECTIVE
  The objective was to define the predictive value of impairment measures for concurrent functional task performance in traumatic cervical SCI, as measured by the Graded Redefined Assessment of Strength, Sensibility and Prehension (GRASSP).
  
  
  METHODS
  Retrospective analysis.
  
  
  METHODS
  A data set of 138 GRASSP assessments was analyzed. The Strength and Sensation modules were used as measures of impairment, whereas the concurrent Prehension Performance module was used as the surrogate measure of function. Classifiers were trained to predict the scores on each of the six individual tasks in the Prehension Performance module. The six scores were added to obtain a total score.
  
  
  RESULTS
  The Spearman's ρ between predicted and actual total Prehension Performance scores was 0.84. Predictions using both the Strength and Sensation scores were not found to be superior to predictions using the Strength scores alone.
  
  
  CONCLUSIONS
  Measures of UE motor impairment are highly predictive of functional task performance after cervical SCI. Automated sensor-based assessments of UE motor function after SCI can rely on measuring only impairment and estimating functional performance accordingly.
authors.affiliation: Toronto Rehabilitation Institute-University Health Network, Toronto, Ontario, Canada.|Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada.|Rehabilitation Sciences Institute, University of Toronto, Toronto, Ontario, Canada.
authors.forename: J
authors.initials: J
authors.lastname: Zariffa
authors.affiliation: Spinal Cord Injury Center, Balgrist University Hospital, Zurich, Switzerland.
authors.forename: A
authors.initials: A
authors.lastname: Curt
authors.affiliation: Toronto Rehabilitation Institute-University Health Network, Toronto, Ontario, Canada.|Rehabilitation Sciences Institute, University of Toronto, Toronto, Ontario, Canada.|Department of Physical Therapy, University of Toronto, Toronto, Ontario, Canada.
authors.forename: M C
authors.initials: MC
authors.lastname: Verrier
authors.affiliation: Krembil Neuroscience Centre-University Health Network, Toronto, Ontario, Canada.|Department of Surgery, University of Toronto, Ontario, Canada.
authors.forename: M G
authors.initials: MG
authors.lastname: Fehlings
authors.affiliation: Department of Physical Therapy, University of Toronto, Toronto, Ontario, Canada.|Krembil Neuroscience Centre-University Health Network, Toronto, Ontario, Canada.
authors.forename: S
authors.initials: S
authors.lastname: Kalsi-Ryan
mesh_terms: D061725:Accelerometry / Q000295:instrumentation / Q000379:methods*; D066193:Cervical Cord / Q000293:injuries* / Q000503:physiopathology; D003430:Cross-Sectional Studies; D004185:Disability Evaluation; D006801:Humans; D008137:Longitudinal Studies; D000069550:Machine Learning; D009043:Motor Activity / Q000502:physiology*; D011379:Prognosis; D020127:Recovery of Function / Q000502:physiology; D012189:Retrospective Studies; D013119:Spinal Cord Injuries / Q000175:diagnosis* / Q000503:physiopathology*; D034941:Upper Extremity / Q000503:physiopathology*