Starlab

About: Starlab is a based out in . It is known for research contribution in the topics: GNSS applications & Transcranial direct-current stimulation. The organization has 121 authors who have published 218 publications receiving 7214 citations.

Advanced Interaction in Context

Abstract: Mobile information appliances are increasingly used in numerous different situations and locations, setting new requirements to their interaction methods When the user's situation, place or activity changes, the functionality of the device should adapt to these changes In this work we propose a layered real-time architecture for this kind of context-aware adaptation based on redundant collections of low-level sensors Two kinds of sensors are distinguished: physical and logical sensors, which give cues from environment parameters and host information A prototype board that consists of eight sensors was built for experimentation The contexts are derived from cues using real-time recognition software, which was constructed after experiments with Kohonen's Self-Organizing Maps and its variants A personal digital assistant (PDA) and a mobile phone were used with the prototype to demonstrate situational awareness On the PDA font size and backlight were changed depending on the demonstrated contexts while in mobile phone the active user profile was changed The experiments have shown that it is feasible to recognize contexts using sensors and that context information can be used to create new interaction metaphors

An objective approach to dry eye disease severity.

Abstract: Purpose A prospective, multisite clinical study (10 sites in the European Union and the United States) evaluated the clinical utility of commonly used tests and tear osmolarity for assessing dry eye disease severity. Methods Three hundred fourteen consecutive subjects between the ages of 18 and 82 years were recruited from the general patient population, 299 of which qualified with complete datasets. Osmolarity testing, Schirmer test without anesthesia, tear film breakup time (TBUT), corneal staining, meibomian dysfunction assessment, and conjunctival staining were performed bilaterally. A symptom questionnaire, the Ocular Surface Disease Index (OSDI), was also administered to each patient. Distributions of clinical signs and symptoms against a continuous composite severity index were evaluated. Results Osmolarity was found to have the highest correlation coefficient to disease severity (r(2) = 0.55), followed by conjunctival staining (r(2) = 0.47), corneal staining (r(2) = 0.43), OSDI (r(2) = 0.41), meibomian score (r(2) = 0.37), TBUT (r(2) = 0.30), and Schirmer result (r(2) = 0.17). A comparison of standard threshold-based classification with the composite severity index revealed significant overlap between the disease severities of prospectively defined normal and dry eye groups. Fully 63% of the subjects were found to be poorly classified by combinations of clinical thresholds. Conclusions Tear film osmolarity was found to be the single best marker of disease severity across normal, mild/moderate, and severe categories. Other tests were found to be informative in the more severe forms of disease; thus, clinical judgment remains an important element in the clinical assessment of dry eye severity. The results also indicate that the initiation and progression of dry eye is multifactorial and supports the rationale for redefining severity on the basis of a continuum of clinical signs. (ClinicalTrials.gov number, NCT00848198.).