title: The accuracy of conventional 2D video for quantifying upper limb kinematics in repetitive motion occupational tasks.
abstract: Marker-less 2D video tracking was studied as a practical means to measure upper limb kinematics for ergonomics evaluations. Hand activity level (HAL) can be estimated from speed and duty cycle. Accuracy was measured using a cross-correlation template-matching algorithm for tracking a region of interest on the upper extremities. Ten participants performed a paced load transfer task while varying HAL (2, 4, and 5) and load (2.2 N, 8.9 N and 17.8 N). Speed and acceleration measured from 2D video were compared against ground truth measurements using 3D infrared motion capture. The median absolute difference between 2D video and 3D motion capture was 86.5 mm/s for speed, and 591 mm/s(2) for acceleration, and less than 93 mm/s for speed and 656 mm/s(2) for acceleration when camera pan and tilt were within ± 30 degrees. Single-camera 2D video had sufficient accuracy (< 100 mm/s) for evaluating HAL. Practitioner Summary: This study demonstrated that 2D video tracking had sufficient accuracy to measure HAL for ascertaining the American Conference of Government Industrial Hygienists Threshold Limit Value(®) for repetitive motion when the camera is located within ± 30 degrees off the plane of motion when compared against 3D motion capture for a simulated repetitive motion task.
authors.affiliation: a Department of Electrical and Computer Engineering , University of Wisconsin-Madison , Madison , WI 53706 , USA.
authors.forename: Chia-Hsiung
authors.initials: CH
authors.lastname: Chen
authors.affiliation: b Department of Industrial and Systems Engineering , University of Wisconsin-Madison , Madison , WI 53706 , USA.
authors.forename: David P
authors.initials: DP
authors.lastname: Azari
authors.affiliation: a Department of Electrical and Computer Engineering , University of Wisconsin-Madison , Madison , WI 53706 , USA.
authors.forename: Yu Hen
authors.initials: YH
authors.lastname: Hu
authors.affiliation: c Department of Biostatistics and Medical Informatics , University of Wisconsin-Madison , Madison , WI 53706 , USA.
authors.forename: Mary J
authors.initials: MJ
authors.lastname: Lindstrom
authors.affiliation: d Department of Mechanical Engineering , University of Wisconsin-Madison , Madison , WI 53706 , USA.
authors.forename: Darryl
authors.initials: D
authors.lastname: Thelen
authors.affiliation: b Department of Industrial and Systems Engineering , University of Wisconsin-Madison , Madison , WI 53706 , USA.
authors.forename: Thomas Y
authors.initials: TY
authors.lastname: Yen
authors.affiliation: b Department of Industrial and Systems Engineering , University of Wisconsin-Madison , Madison , WI 53706 , USA.
authors.forename: Robert G
authors.initials: RG
authors.lastname: Radwin
mesh_terms: D000054:Acceleration; D000293:Adolescent; D000328:Adult; D000465:Algorithms; D001696:Biomechanical Phenomena; D006804:Ergonomics; D005260:Female; D006801:Humans; D008297:Male; D009068:Movement; D009140:Musculoskeletal Diseases; D009784:Occupational Diseases; D016273:Occupational Exposure / Q000032:analysis*; D034941:Upper Extremity / Q000502:physiology*; D014741:Video Recording / Q000379:methods*; D055815:Young Adult
keywords: exposure assessment; hand activity level; marker-less video tracking; repetitive motion; work-related musculoskeletal disorders