Biomedical subjects

Julie A Jacko

Publications and source records attributed to Julie A Jacko.

5 recordsLinked to original sources

PubMed2006

The impact of auditory and haptic feedback on computer task performance in patients with age-related macular degeneration and control subjects with no known ocular disease.

PURPOSE: To determine the impact of auditory and haptic (tactile) feedback on computer task performance of patients with age-related macular degeneration (AMD) compared to controls. METHODS: Thirty patients with AMD and 29 similarly aged controls with no known ocular disease completed timed computer icon "drag and drop" tasks under all four possible conditions of presence or absence of auditory and haptic feedback in a two-factor repeated measures design. Patient recruitment was stratified by best eye acuity: 20/20-20/50; 20/60-20/100; <20/100. Controls had best eye acuity>or=20/30. Task completion time was quantified using final target highlight time (FTHT) and total trial time, measured in milliseconds. RESULTS: Mean+/-standard deviation (SD) FTHT with neither feedback type in the three patient and control groups was, respectively: 1,110+/-356, 1,682+/-1,069, 1,763+/-831, 924+/-533. Auditory feedback improved performance [%FTHT decrease, p-value] in all groups, respectively: 18%, P=0.018; 38%, P=0.054; 57%, P=0.001; 19%, P=0.001. Haptic feedback improved performance in the worst acuity AMD group and controls: 46%, P=0.009; 17%, P=0.038. In the worst acuity AMD group, auditory and/or haptic feedback was associated with a 4-6 second mean (for each task) reduction in total trial time. CONCLUSION: Auditory and haptic feedback can substantially increase performance speed of computer "drag and drop" tasks for patients with AMD, particularly in those patients with the most compromised vision.

Aged↗

PubMed2005

A review and a framework of handheld computer adoption in healthcare.

Wide adoption of mobile computing technology can potentially improve information access, enhance workflow, and promote evidence-based practice to make informed and effective decisions at the point of care. Handheld computers or personal digital assistants (PDAs) offer portable and unobtrusive access to clinical data and relevant information at the point of care. This article reviews the literature on issues related to adoption of PDAs in health care and barriers to PDA adoption. Studies showed that PDAs were used widely in health care providers' practice, and the level of use is expected to rise rapidly. Most care providers found PDAs to be functional and useful in areas of documentation, medical reference, and access to patient data. Major barriers to adoption were identified as usability, security concerns, and lack of technical and organizational support. PDAs offer health care practitioners advantages to enhance their clinical practice. However, better designed PDA hardware and software applications, more institutional support, seamless integration of PDA technology with hospital information systems, and satisfactory security measures are necessary to increase acceptance and wide use of PDAs in healthcare.

Access to Information↗

PubMed2005

Software-based compensation of visual refractive errors of computer users.

For human beings, vision is one of the most important senses in interacting with the surrounding environment, as well as with any tools that require visual communication. As such, the ability to interact effectively with computers through typical graphic user interfaces (GUIs) is greatly affected by any refractive errors present in an individual's visual system. If the refractive errors can be mathematically modeled, a system for overcoming these aberrations can be devised which can increase the effective human-computer interaction for these individuals. Several methods, such as Adaptive Optics, have been proposed that attempt to solve this problem using electro-mechanical devices. These methods are costly and impractical, preventing most visually impaired individuals from benefiting from their use. In contrast, an image-processing method, based on deconvolution techniques, has recently been proposed for the pre-compensation of images to be displayed in a computer. This method is much more practical, being completely implemented in software, and has achieved encouraging results. Previous results have yielded an average 50% increase in visual efficiency in the compensation of a known artificial aberration introduced into the field of vision of experimental subjects. This paper describes the difficulties encountered with the present software-only compensation and proposes several methods for overcoming these obstacles. The difficulties, as well as the proposed solutions, are described theoretically and followed by examples using a lens system showing the improvement over previous methods.

Algorithms↗

PubMed2002

Impact of visual function on computer task accuracy and reaction time in a cohort of patients with age-related macular degeneration.

PURPOSE: To investigate the impact of visual function parameters on computer task performance in patients with age-related macular degeneration (AMD). DESIGN: Interventional case series. METHODS: Eighteen patients with visual impairment due to age-related macular degeneration underwent evaluation of visual acuity using the Early Treatment Diabetic Retinopathy Study protocol, contrast sensitivity using a Pelli-Robson chart, binocular simultaneous visual field using the Esterman program on an automated perimeter, and color vision using Farnsworth D-15. Each subject then completed 125 computer icon identification tasks. Relationships between computer task performance (accuracy and speed) and visual function parameters (visual acuity, contrast sensitivity, visual field, and color vision) were analyzed. RESULTS: Visual acuity and contrast sensitivity in the better eye, weighted average contrast sensitivity, and color vision defects are significantly associated with computer task accuracy. Visual acuity in the better eye, weighted average visual acuity, and color vision defects are significantly associated with performance speed. Visual function parameters and clinical features significantly associated with computer task accuracy in a multiple regression model include weighted average contrast sensitivity (P = 0.001), protan color vision defect (P = 0.002), cataract severity in the better-seeing eye (P = 0.036), and geographic atrophy outside the central macula (P = 0.046). Visual function parameters and clinical features significantly associated with computer task speed in a multiple regression model include color vision defects (deutan, P < 0.001; protan, P < 0.001) and gender (P = 0.05). CONCLUSIONS: Among this cohort of patients with AMD, visual acuity, contrast sensitivity, and color vision defects are significant predictors of computer task performance. Visual function parameters of the better eye played a more significant role than parameters of the worse eye, and contrast sensitivity is the most significant predictor of computer task accuracy.

Activities of Daily Living↗

PubMed2002

Impact of graphical user interface screen features on computer task accuracy and speed in a cohort of patients with age-related macular degeneration.

PURPOSE: To investigate the impact of graphical user interface screen features on computer task performance in patients with age-related macular degeneration (AMD). DESIGN: Interventional case series. METHODS: Eighteen patients with visual impairment due to AMD were recruited from the Bascom Palmer Eye Institute Low Vision Clinic. Each patient underwent evaluation of visual acuity using the Early Treatment Diabetic Retinopathy Study protocol, contrast sensitivity using a Pelli-Robson chart, binocular simultaneous visual field using the Esterman program on an automated perimeter, and color vision using Farnsworth D-15. Each subject then completed computer icon identification tasks while the following screen features of the graphical user interface were varied: size of icons displayed, icon set size (number of icons displayed), and background color. Each patient performed all 125 computer tasks with each of five icon sizes (9.2 mm, 14.6 mm, 23.2 mm, 36.8 mm, 58.3 mm), each of five icon set sizes (2, 3, 4, 5, 6), and each of five different background colors (black, white, red, green, blue) in a randomly ordered fashion. Relationships between computer task performance (accuracy and speed) and graphical user interface screen features were studied. RESULTS: Icon size and icon set size are significantly associated with computer task accuracy (P <.001), whereas background color is not a significant predictor of task accuracy (P =.63). The impact of icon size on accuracy is nonlinear, with the data indicating that no additional improvement in accuracy is associated with increasing the icon size beyond 23.2 mm. The impact of icon set size on accuracy is linear, with a smaller icon set size significantly associated with greater computer accuracy. A larger icon size is significantly associated with a shorter time to task completion (P =.001); this relationship is largely linearly related to icon size. There was no significant impact of background color (P =.11) or set size (P =.37) on time to task completion. CONCLUSIONS: Modifications of graphical user interface design may permit improved computer task performance among patients with visual impairment due to AMD.

Adult↗