Research on Devices for Handling Whole Slide Images on Pathology Workstations. An Ergonomic Outlook
Abstract
Background
Digital Pathology represents a technological innovation that introduces changes in the traditional tasks of pathologists. In this regard, an important issue that has not been enough emphasized is the image handling from an ergonomic point of view to avoid work-related musculoskeletal disorders (MSD). The aim of this study was to investigate a proper input device for digital pathology.
Material & Methods
Research was conducted in two phases: (1). A comparative study to find out an optimal external controller. Eight medical students analyzed 11 input devices: keyboard (Hewlett Packard, HP), conventional mouse (HP), vertical mouse (CLS), touchpad (Logitech), 3 trackballs (Logitech, Kensington Expert and Ulove), Rollermouse (Contour), Ergopointer (Märzhäuser Sensotech), gamepad (Logitech) and a touchless device (Leap Motion Controller), using them with the Image Viewer software (Ventana). The web-based Fitts´ law test (UC Berkeley) was used to objectify the accuracy of each used device, randomly. 12 items were included in the questionnaire: comfort, technical aspects (cursor movement and objective achievement), prospects, overall satisfaction, prior experience, and others. (2). Evaluation by two experienced pathologists of the best rated input device on the previous experiment and its comparison with a voice recognition system (Invox Medical Dictation, Vocali) using a headset microphone (Plantronics). Perceived workload was scored using the NASA Task Load Index on 28 whole slide images visualized on the Digital Image Hub (Leica) platform with a 4 MegaPixel display (Barco). Data were processed with SPSS 21.0.
Results
Correlation between technical aspects of the evaluated devices and accuracy (Fitts´ law test), and comfort with overall satisfaction, was demonstrated (p<0.05). Comparative analysis of the 11 input devices concluded that vertical mouse was the best rated input device. However, on the second phase of the study, we find a slightly higher perceived workload using this device than using the voice recognition system, which was the best controller in digital pathology from an ergonomic point of view in this study.
Conclusions
We describe a methodology that can study and compare input devices for future workstations in digital pathology. Pathologists should be involved in this process trying to find ergonomic devices that prevent MSD. Voice recognition can function as a good handsfree device for digital pathology and could be considered in physical disability situations. Further studies using electromyography, accelerometry and 3D reconstruction analysis could provide additional ergonomic information.
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Keywords
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