User-centered virtual environment design for virtual rehabilitation

<p>Abstract</p> <p>Background</p> <p>As physical and cognitive rehabilitation protocols utilizing virtual environments transition from single applications to comprehensive rehabilitation programs there is a need for a new design cycle methodology. Current human-computer interaction designs focus on usability without benchmarking technology within a user-in-the-loop design cycle. The field of virtual rehabilitation is unique in that determining the efficacy of this genre of computer-aided therapies requires prior knowledge of technology issues that may confound patient outcome measures. Benchmarking the technology (e.g., displays or data gloves) using healthy controls may provide a means of characterizing the "normal" performance range of the virtual rehabilitation system. This standard not only allows therapists to select appropriate technology for use with their patient populations, it also allows them to account for technology limitations when assessing treatment efficacy.</p> <p>Methods</p> <p>An overview of the proposed user-centered design cycle is given. Comparisons of two optical see-through head-worn displays provide an example of benchmarking techniques. Benchmarks were obtained using a novel vision test capable of measuring a user's stereoacuity while wearing different types of head-worn displays. Results from healthy participants who performed both virtual and real-world versions of the stereoacuity test are discussed with respect to virtual rehabilitation design.</p> <p>Results</p> <p>The user-centered design cycle argues for benchmarking to precede virtual environment construction, especially for therapeutic applications. Results from real-world testing illustrate the general limitations in stereoacuity attained when viewing content using a head-worn display. Further, the stereoacuity vision benchmark test highlights differences in user performance when utilizing a similar style of head-worn display. These results support the need for including benchmarks as a means of better understanding user outcomes, especially for patient populations.</p> <p>Conclusions</p> <p>The stereoacuity testing confirms that without benchmarking in the design cycle poor user performance could be misconstrued as resulting from the participant's injury state. Thus, a user-centered design cycle that includes benchmarking for the different sensory modalities is recommended for accurate interpretation of the efficacy of the virtual environment based rehabilitation programs.</p

Indicators of "Healthy Aging" in older women (65-69 years of age). A data-mining approach based on prediction of long-term survival

<p>Abstract</p> <p>Background</p> <p>Prediction of long-term survival in healthy adults requires recognition of features that serve as early indicators of successful aging. The aims of this study were to identify predictors of long-term survival in older women and to develop a multivariable model based upon longitudinal data from the Study of Osteoporotic Fractures (SOF).</p> <p>Methods</p> <p>We considered only the youngest subjects (<it>n </it>= 4,097) enrolled in the SOF cohort (65 to 69 years of age) and excluded older SOF subjects more likely to exhibit a "frail" phenotype. A total of 377 phenotypic measures were screened to determine which were of most value for prediction of long-term (19-year) survival. Prognostic capacity of individual predictors, and combinations of predictors, was evaluated using a cross-validation criterion with prediction accuracy assessed according to time-specific AUC statistics.</p> <p>Results</p> <p>Visual contrast sensitivity score was among the top 5 individual predictors relative to all 377 variables evaluated (mean AUC = 0.570). A 13-variable model with strong predictive performance was generated using a forward search strategy (mean AUC = 0.673). Variables within this model included a measure of physical function, smoking and diabetes status, self-reported health, contrast sensitivity, and functional status indices reflecting cumulative number of daily living impairments (HR ≥ 0.879 or RH ≤ 1.131; P < 0.001). We evaluated this model and show that it predicts long-term survival among subjects assigned differing causes of death (e.g., cancer, cardiovascular disease; P < 0.01). For an average follow-up time of 20 years, output from the model was associated with multiple outcomes among survivors, such as tests of cognitive function, geriatric depression, number of daily living impairments and grip strength (P < 0.03).</p> <p>Conclusions</p> <p>The multivariate model we developed characterizes a "healthy aging" phenotype based upon an integration of measures that together reflect multiple dimensions of an aging adult (65-69 years of age). Age-sensitive components of this model may be of value as biomarkers in human studies that evaluate anti-aging interventions. Our methodology could be applied to data from other longitudinal cohorts to generalize these findings, identify additional predictors of long-term survival, and to further develop the "healthy aging" concept.</p

Size-Related Changes in Foot Impact Mechanics in Hoofed Mammals

Foot-ground impact is mechanically challenging for all animals, but how do large animals mitigate increased mass during foot impact? We hypothesized that impact force amplitude scales according to isometry in animals of increasing size through allometric scaling of related impact parameters. To test this, we measured limb kinetics and kinematics in 11 species of hoofed mammals ranging from 18–3157 kg body mass. We found impact force amplitude to be maintained proportional to size in hoofed mammals, but that other features of foot impact exhibit differential scaling patterns depending on the limb; forelimb parameters typically exhibit higher intercepts with lower scaling exponents than hind limb parameters. Our explorations of the size-related consequences of foot impact advance understanding of how body size influences limb morphology and function, foot design and locomotor behaviour