separation and summation of emg recordings by task using video records n.
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  1. SEPARATION AND SUMMATION OF EMG RECORDINGS BY TASK USING VIDEO RECORDS York University, Toronto, Canada University of Waterloo, Waterloo, Canada Institute for Work and Health, Toronto Canada Anne Moore, Richard Wells, Dwayne Van Eerd, Stephen Krajcarski, Melanie Banina, Donald Cole, and Sheilah Hogg-Johnson

  2. Introduction • Exposure to musculoskeletal loading at work depends on many factors (Wells et al) • -tasks performed, workload • -workstation, equipment, technique • -task-time organization • Difficult to separate out the effects of each factor from overall level of musculoskeletal loading

  3. Introduction – cont’d • Combining EMG and task identification using video has shown promising results in industry(Formsan et al, 2002) • Can we differentiate between tasks in an office setting even when these tasks are done within an environment of other tasks that may or may not be done simultaneously?

  4. Methods • 33 Participants: • Newspaper advertising and finance employees • Clerical, administration, sales, customer accounts and call centre • 10 male/ 23 female

  5. Methods (cont’d) Electromyographic signals bilaterally from: • Extensor Carpi Ulnaris Brevis (ECRB) • Trapezius Recorded using portable EMG system (ME3000P8, Mega Electronics, Finland) Simultaneous video recording

  6. Protocol Participant reported to a private room for hook up, signal verification and calibration: • Maximal shoulder shrug with arms abducted against resistance • Wrist extension with maximal grasp Participant and researcher returned to participant’s usual workstation

  7. Protocol EMG and video recorded while participant performed usual job for 2 hours Subset repeated protocol on a 2nd day (n=20)

  8. Video Analysis • 30 minutes of Video chosen for analysis based on: • Included “mark” for time synchronization • Emphasis on seated work • On/off states of 7 tasks identified while viewing video and simultaneously recorded on computer (Observer Pro 4.0, Noldus Technology, Netherlands)

  9. Video Analysis (cont’d) • Seven states/activities identified:

  10. EMG Analysis • Custom software performed: • Link in time with video file • EMG calibration • Amplitude Probability Distribution Function (APDF) at 10th, 50th, and 90th level (Jonsson, 1982) • Gaps Analysis (Veiersted et al, 1990) • All analyses performed at: • Whole file level • General Task level (individual and concatonated) • Specific Group level (individual and concatonated)

  11. Task Identification and Concatonation Process

  12. Results

  13. Keyboarding – Static EMG

  14. Keyboarding - Gaptime * *

  15. Mousing – Static EMG

  16. Mousing – Peak EMG

  17. Phone – Static EMG

  18. Conclusions • Separating EMG by task in the workplace allows examination effects of specific tasks on musculoskeletal load in situ

  19. Conclusions - continued • Use of a mouse is a constrained task that has high static muscle activity and low peak muscle activity in mouse hand • The period of time while keyboarding was marked by significantly higher static loading in both the forearms and shoulders

  20. Acknowledgements • NIOSH/NIH R010H03708-02 • Center for VDT & Health Research • Toronto Star • Southern Ontario Newspaper Guild