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1.
Rev Esp Patol ; 55(1): 19-25, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-34980436

RESUMO

INTRODUCTION: The high prevalence of musculoskeletal disorders in pathologists, together with the current trend towards the digitization of pathology, prompted us to study the different types of input devices employed during the revision of whole slide images, in order to investigate the pattern and extent of muscle activity involved in their use. MATERIAL AND METHODS: A comparative study was made of 10 input devices (conventional and vertical mouse, three trackballs, the Ergopointer™, the Rollermouse™, an optical pen mouse, a touchpad, and the Leap Motion™). Six medical students performed a standardized circuit using a Fitts' Law based tissue array, digitized. The electrical activity of seven upper limb muscles (adductor pollicis, extensor pollicis longus, extensor digitorum, flexor digitorum, middle deltoid, upper trapezius, and middle trapezius) was measured using surface electromyography. RESULTS: Statistically significant differences in the overall electrical activity among the different input devices, both absolute values in mV as well as normalized values to the upper limb at rest, were observed (p<0.001); the Rollermouse™ (0.1027mV; 139%), Logitech M570 trackball (0.1053mV; 145%), Ergopointer™ (0.1151mV; 167%), conventional mouse (0.1251mV; 191%), and vertical mouse (0.1312mV; 205%) required less activity, while the optical pen mouse (0.1717mV; 299%), Leap Motion™ (0.1803mV; 319%), Expert Mouse trackball (0.1845mV; 329%), EIGIIS trackball (0.2442mV; 468%) and the touchpad (0.2560mV; 496%) required greater muscle mobilization. CONCLUSION: We designed a system based on Fitts' Law to compare input devices in digital pathology. Variability between compared devices and muscle activity was found. Long-term use could result in different muscular fatigue patterns. Even though the selection of an input device is a matter of personal preference, its impact on ergonomics should be considered.


Assuntos
Ergonomia , Músculo Esquelético , Eletromiografia , Humanos , Músculo Esquelético/fisiologia
2.
Rev. esp. patol ; 55(1): 19-25, ene-mar 2022. ilus
Artigo em Inglês | IBECS | ID: ibc-206767

RESUMO

Introduction: The high prevalence of musculoskeletal disorders in pathologists, together with the current trend towards the digitization of pathology, prompted us to study the different types of input devices employed during the revision of whole slide images, in order to investigate the pattern and extent of muscle activity involved in their use. Material and methods: A comparative study was made of 10 input devices (conventional and vertical mouse, three trackballs, the Ergopointer™, the Rollermouse™, an optical pen mouse, a touchpad, and the Leap Motion™). Six medical students performed a standardized circuit using a Fitts’ Law based tissue array, digitized. The electrical activity of seven upper limb muscles (adductor pollicis, extensor pollicis longus, extensor digitorum, flexor digitorum, middle deltoid, upper trapezius, and middle trapezius) was measured using surface electromyography. Results: Statistically significant differences in the overall electrical activity among the different input devices, both absolute values in mV as well as normalized values to the upper limb at rest, were observed (p<0.001); the Rollermouse™ (0.1027mV; 139%), Logitech M570 trackball (0.1053mV; 145%), Ergopointer™ (0.1151mV; 167%), conventional mouse (0.1251mV; 191%), and vertical mouse (0.1312mV; 205%) required less activity, while the optical pen mouse (0.1717mV; 299%), Leap Motion™ (0.1803mV; 319%), Expert Mouse trackball (0.1845mV; 329%), EIGIIS trackball (0.2442mV; 468%) and the touchpad (0.2560mV; 496%) required greater muscle mobilization. Conclusion: We designed a system based on Fitts’ Law to compare input devices in digital pathology. Variability between compared devices and muscle activity was found. Long-term use could result in different muscular fatigue patterns. Even though the selection of an input device is a matter of personal preference, its impact on ergonomics should be considered.(AU)


Introducción y objetivos: La alta prevalencia de trastornos musculoesqueléticos entre patólogos y el cambio hacia la digitalización de la Anatomía Patológica, nos ha hecho plantear un estudio comparativo de dispositivos de entrada al manejar preparaciones histológicas digitalizadas, evaluando el patrón y la actividad muscular durante su uso. Material y métodos: se realizó una comparación entre 10 dispositivos: ratón convencional y vertical, 3 trackballs, Ergopointer™, Rollermouse™, lápiz óptico, touchpad, Leap Motion™. Seis estudiantes de medicina realizaron un circuito estandarizado empleando una matriz tisular digitalizada, basada en la ley de Fitts. Se registró con electromiografía superficial la actividad eléctrica de 7 músculos del brazo dominante (aductor y extensor largo del pulgar, extensor y flexor común de los dedos, deltoides medio, y trapecios superior y medio). Resultados: se encontraron diferencias estadísticamente significativas en la actividad muscular, absoluta y relativizada (respecto al reposo), entre los dispositivos (p<0,001); Rollermouse™ (0,1027mV;139%), trackball Logitech M570 (0,1053mV/145%), Ergopointer™ (0,1151mV/167%), ratón convencional (0,1251mV/191%) y ratón vertical (0,1312mV/205%) fueron los que demandaron menor actividad, mientras que el lápiz óptico (0,1717mV/299%), Leap Motion™ (0,1803mV/319%), trackball Expert Mouse (0,1845mV/329%), trackball EIGIIS (0,2442mV/468%) y touchpad (0,2560mV/496%) fueron los que mayor movilización muscular requirieron. Conclusiones: Hemos diseñado un sistema basado en la ley de Fitts para comparar dispositivos de entrada. Se encontró variabilidad entre los dispositivos comparados y la actividad muscular demandada, lo que podría traducirse en diferentes patrones de fatiga muscular a largo plazo. Aunque la elección de un dispositivo es una cuestión de preferencia personal, es importante analizar su impacto desde el punto de vista ergonómico.(AU)


Assuntos
Humanos , Ergonomia , Eletromiografia , Doenças Musculoesqueléticas , Tecnologia da Informação , Patologia
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