title: Assessing Arthroscopic Skills Using Wireless Elbow-Worn Motion Sensors.
abstract: BACKGROUND
  Assessment of surgical skill is a critical component of surgical training. Approaches to assessment remain predominantly subjective, although more objective measures such as Global Rating Scales are in use. This study aimed to validate the use of elbow-worn, wireless, miniaturized motion sensors to assess the technical skill of trainees performing arthroscopic procedures in a simulated environment.
  
  
  METHODS
  Thirty participants were divided into three groups on the basis of their surgical experience: novices (n = 15), intermediates (n = 10), and experts (n = 5). All participants performed three standardized tasks on an arthroscopic virtual reality simulator while wearing wireless wrist and elbow motion sensors. Video output was recorded and a validated Global Rating Scale was used to assess performance; dexterity metrics were recorded from the simulator. Finally, live motion data were recorded via Bluetooth from the wireless wrist and elbow motion sensors and custom algorithms produced an arthroscopic performance score.
  
  
  RESULTS
  Construct validity was demonstrated for all tasks, with Global Rating Scale scores and virtual reality output metrics showing significant differences between novices, intermediates, and experts (p < 0.001). The correlation of the virtual reality path length to the number of hand movements calculated from the wireless sensors was very high (p < 0.001). A comparison of the arthroscopic performance score levels with virtual reality output metrics also showed highly significant differences (p < 0.01). Comparisons of the arthroscopic performance score levels with the Global Rating Scale scores showed strong and highly significant correlations (p < 0.001) for both sensor locations, but those of the elbow-worn sensors were stronger and more significant (p < 0.001) than those of the wrist-worn sensors.
  
  
  CONCLUSIONS
  A new wireless assessment of surgical performance system for objective assessment of surgical skills has proven valid for assessing arthroscopic skills. The elbow-worn sensors were shown to achieve an accurate assessment of surgical dexterity and performance.
  
  
  CONCLUSIONS
  The validation of an entirely objective assessment of arthroscopic skill with wireless elbow-worn motion sensors introduces, for the first time, a feasible assessment system for the live operating theater with the added potential to be applied to other surgical and interventional specialties.
authors.affiliation: McLaren Applied Technologies, McLaren Technology Centre, Chertsey Road, Woking, Surrey, GU21 4YH, United Kingdom.
authors.forename: Georgina S J
authors.initials: GS
authors.lastname: Kirby
authors.affiliation: Botnar Research Centre and NIHR Biomedical Research Unit, University of Oxford, Old Road, Headington, Oxford OX3 7LD, United Kingdom. E-mail address for J.L. Rees: jonathan.rees@ndorms.ox.ac.uk.
authors.forename: Paul
authors.initials: P
authors.lastname: Guyver
authors.affiliation: Botnar Research Centre and NIHR Biomedical Research Unit, University of Oxford, Old Road, Headington, Oxford OX3 7LD, United Kingdom. E-mail address for J.L. Rees: jonathan.rees@ndorms.ox.ac.uk.
authors.forename: Louise
authors.initials: L
authors.lastname: Strickland
authors.affiliation: Botnar Research Centre and NIHR Biomedical Research Unit, University of Oxford, Old Road, Headington, Oxford OX3 7LD, United Kingdom. E-mail address for J.L. Rees: jonathan.rees@ndorms.ox.ac.uk.
authors.forename: Abtin
authors.initials: A
authors.lastname: Alvand
authors.affiliation: The Hamlyn Centre, Imperial College London, Exhibition Road, SW7 2AZ London, United Kingdom.
authors.forename: Guang-Zhong
authors.initials: GZ
authors.lastname: Yang
authors.affiliation: McLaren Applied Technologies, McLaren Technology Centre, Chertsey Road, Woking, Surrey, GU21 4YH, United Kingdom.
authors.forename: Caroline
authors.initials: C
authors.lastname: Hargrove
authors.affiliation: The Hamlyn Centre, Imperial College London, Exhibition Road, SW7 2AZ London, United Kingdom.
authors.forename: Benny P L
authors.initials: BP
authors.lastname: Lo
authors.affiliation: Botnar Research Centre and NIHR Biomedical Research Unit, University of Oxford, Old Road, Headington, Oxford OX3 7LD, United Kingdom. E-mail address for J.L. Rees: jonathan.rees@ndorms.ox.ac.uk.
authors.forename: Jonathan L
authors.initials: JL
authors.lastname: Rees
mesh_terms: D001182:Arthroscopy / Q000193:education*; D002983:Clinical Competence; D004550:Elbow; D006801:Humans; D008953:Models, Anatomic; D011597:Psychomotor Performance / Q000502:physiology*; D058998:Remote Sensing Technology; D015203:Reproducibility of Results; D012785:Shoulder Joint / Q000601:surgery*; D014953:Wrist