title: Discriminating between maximal and feigned isokinetic knee musculature performance using waveform similarity measures.
abstract: BACKGROUND
  Muscle strength test outcomes may aid in determination of impairment or disability rating following injury. In such settings, verification of participant effort during testing is imperative. This investigation explored the utilization of within-set moment waveform similarity measures, namely cross correlation and percent root mean square difference scores, to develop decision rules for discriminating between maximal and feigned efforts during isokinetic testing of the knee joint musculature.
  
  
  METHODS
  A mixed-gender sample of 46 participants performed non-reciprocal sets of maximal or feigned knee extension and flexion concentric and eccentric efforts at testing velocities of 30°s(-1) and 120°s(-1). Logistic regression and Monte Carlo simulations were used to derive decision rules for differentiating between the two effort types.
  
  
  RESULTS
  Employing cutoff scores corresponding to 100% specificity; sensitivities of the knee extensor's velocity-specific decision rules were 92.4% and 84.8%, respectively. The velocity-specific knee flexor's test sensitivities were 56.5% and 46.7%.
  
  
  CONCLUSIONS
  Utilizing the proposed decision rules, substantiating maximal effort performance of the knee extensors may be possible using this specific testing protocol. However, the proposed methods are limited in their ability to verify performance of maximal knee flexor efforts.
authors.affiliation: School of Kinesiology and Health Studies, Queen's University, Kingston, Ontario, Canada. sivanalm@hotmail.com
authors.forename: Sivan
authors.initials: S
authors.lastname: Almosnino
authors.forename: Joan M
authors.initials: JM
authors.lastname: Stevenson
authors.forename: Andrew G
authors.initials: AG
authors.lastname: Day
authors.forename: Davide D
authors.initials: DD
authors.lastname: Bardana
authors.forename: Elena D
authors.initials: ED
authors.lastname: Diaconescu
authors.forename: Zeevi
authors.initials: Z
authors.lastname: Dvir
mesh_terms: D000328:Adult; D000465:Algorithms; D005260:Female; D006801:Humans; D007719:Knee Joint / Q000502:physiology*; D008297:Male; D009119:Muscle Contraction / Q000502:physiology*; D053580:Muscle Strength / Q000502:physiology*; D053581:Muscle Strength Dynamometer; D018482:Muscle, Skeletal / Q000502:physiology*; D010363:Pattern Recognition, Automated / Q000379:methods; D010807:Physical Endurance / Q000502:physiology*; D005082:Physical Exertion / Q000502:physiology*; D011597:Psychomotor Performance / Q000502:physiology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity