A vision-based human--computer interface is presented in the paper. The interface detects voluntary eye-blinks and interprets them as control commands. The employed image processing methods include Haar-like features for automatic face detection, and template matching based eye tracking and eye-blink detection. Interface performance was tested by 49 users (of which 12 were with physical disabilities). Test results indicate interface usefulness in offering an alternative mean of communication with computers. The users entered English and Polish text (with average time of less than 12s per character) and were able to browse the Internet. The interface is based on a notebook equipped with a typical web camera and requires no extra light sources. The interface application is available on-line as open-source software.

In recent years there has been an increased interest in human-computer interaction systems allowing for more natural communication with machines. Such systems are especially important for the elderly and disabled persons. The paper presents a vision-based system for detection of long voluntary eye blinks and interpretation of blink patterns for communication between man and machine. The blink-controlled applications developed for this system have been described, i.e. the spelling program and the eye-controlled Web browser.

The aim of this paper is to analyze the massive open online courses available on the platform “Coursera” from the perspective of their accessibility for users with disabilities. The analysis was carried out against the guidelines developed by the world wide web consortium in three ways: user testing, heuristic evaluation and automatic audit using selected online tools. Ten users, one of them being an accessibility expert, with different impairments were involved in the research procedure. Their task was to follow a course of their choice and to communicate their observations and comments on the courses with the use of a specially designed questionnaire. Despite the continuous development of Coursera platform, the introduction of new improvements and the implementation of an accessibility policy along with a subpage dedicated to this subject, the participants of the study still faced barriers to digital accessibility. Significant non-compliances with the aforementioned guidelines have been demonstrated through the analysis of the questionnaire results and through a simplified audit of the platform.

Heart rate variability (HRV) analysis can be a useful tool to detect underlying heart or even general health problems. Currently, such analysis is usually performed in controlled or semi-controlled conditions. Since many of the typical HRV measures are sensitive to data quality, manual artifact correction is common in literature, both as an exclusive method or in addition to various filters. With proliferation of Personal Monitoring Devices with continuous HRV analysis an opportunity opens for HRV analysis in a new setting. However, current artifact correction approaches have several limitations that hamper the analysis of real-life HRV data. To address this issue we propose an algorithm for automated artifact correction that has a minimal impact on HRV measures, but can handle more artifacts than existing solutions. We verify this algorithm based on two datasets. One collected during a recreational bicycle race and another one in a laboratory, both using a PMD in form of a GPS watch. Data include direct measurement of electrical myocardial signals using chest straps and direct measurements of power using a crank sensor (in case of race dataset), both paired with the watch. Early results suggest that the algorithm can correct more artifacts than existing solutions without a need for manual support or parameter tuning. At the same time, the error introduced to HRV measures for peak correction and shorter gaps is similar to the best existing solution (Kubios-inspired threshold-based cubic interpolation) and better than commonly used median filter. For longer gaps, cubic interpolation can in some cases result in lower error in HRV measures, but the shape of the curve it generates matches ground truth worse than our algorithm. It might suggest that further development of the proposed algorithm may also improve these results.