A marker-less technique for measuring kinematics in the operating room.

Frasier LL1, Azari DP2, Ma Y1, Pavuluri Quamme SR1, Radwin RG3, Pugh CM1, Yen TY3, Chen CH4, Greenberg CC5.

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Abstract

BACKGROUND:

Often in simulated settings, quantitative analysis of technical skill relies largely on specially tagged instruments or tracers on surgeons' hands. We investigated a novel, marker-less technique for evaluating technical skill during open operations and for differentiating tasks and surgeon experience level.

METHODS:

We recorded the operative field via in-light camera for open operations. Sixteen cases yielded 138 video clips of suturing and tying tasks ≥5 seconds in duration. Video clips were categorized based on surgeon role (attending, resident) and task subtype (suturing tasks: body wall, bowel anastomosis, complex anastomosis; tying tasks: body wall, superficial tying, deep tying). We tracked a region of interest on the hand to generate kinematic data. Nested, multilevel modeling addressed the nonindependence of clips obtained from the same surgeon.

RESULTS:

Interaction effects for suturing tasks were seen between role and task categories for average speed (P = .04), standard deviation of speed (P = .05), and average acceleration (P = .03). There were significant differences across task categories for standard deviation of acceleration (P = .02). Significant differences for tying tasks across task categories were observed for maximum speed (P = .02); standard deviation of speed (P = .04); and average (P = .02), maximum (P < .01), and standard deviation (P = .03) of acceleration.

CONCLUSION:

We demonstrated the ability to detect kinematic differences in performance using marker-less tracking during open operative cases. Suturing task evaluation was most sensitive to differences in surgeon role and task category and may represent a scalable approach for providing quantitative feedback to surgeons about technical skill.