Towards automation of dynamic-gaze video analysis taking functional upper-limb tasks as a case study

Background and objective : Previous studies in motor control have yielded clear evidence that gaze behavior (where someone looks) quantifies the attention paid to perform actions. However, eliciting clinically meaningful results from the gaze data has been done manually, rendering it incredibly tedious, time-consuming, and highly subjective. This paper aims to study the feasibility of automating the coding process of the gaze data taking functional upper-limb tasks as a case study. Methods : This is achieved by developing a new algorithm capable of coding the collected gaze data through three main stages; data preparation, data processing, and output generation. The input data in the form of a crosshair and a gaze video are converted into a 25Hz frame rate sequence. Keyframes and non-key frames are then obtained and processed using a combination of image processing techniques and a fuzzy logic controller. In each trial, the location and duration of gaze fixation at the areas of interest (AOIs) are obtained. Once the gaze data is coded, it can be presented in different forms and formats, including the stacked color bar. Results : The obtained results showed that the developed coding algorithm highly agrees with the manual coding method but significantly faster and less prone to unsystematic errors. Statistical analysis showed that Cohen's Kappa ranges from 0.705 to 1.0. Moreover, based on the intra-class correlation coefficient (ICC), the agreement index between computerized and manual coding methods is found to be (i) 0.908 with 95% confidence intervals (0.867, 0.937) for the anatomical hand and (ii) 0.923 with 95% confidence intervals (0.888, 0.948) for the prosthetic hand. A Bland-Altman plot also showed that all data points are closely scattered around the mean. These findings confirm the validity and effectiveness of the developed coding algorithm. Conclusion : The developed algorithm demonstrated that it is feasible to automate the coding of the gaze data, reduce the coding time, and improve the coding process's reliability

Performance of Forest Bryophytes with Different Geographical Distributions Transplanted across a Topographically Heterogeneous Landscape

Most species distribution models assume a close link between climatic conditions and species distributions. Yet, we know little about the link between species’ geographical distributions and the sensitivity of performance to local environmental factors. We studied the performance of three bryophyte species transplanted at south- and north-facing slopes in a boreal forest landscape in Sweden. At the same sites, we measured both air and ground temperature. We hypothesized that the two southerly distributed species Eurhynchium angustirete and Herzogiella seligeri perform better on south-facing slopes and in warm conditions, and that the northerly distributed species Barbilophozia lycopodioides perform better on north-facing slopes and in relatively cool conditions. The northern, but not the two southern species, showed the predicted relationship with slope aspect. However, the performance of one of the two southern species was still enhanced by warm temperatures. An important reason for the inconsistent results can be that microclimatic gradients across landscapes are complex and influenced by many climate-forcing factors. Therefore, comparing only north- and south-facing slopes might not capture the complexity of microclimatic gradients. Population growth rates and potential distributions are the integrated results of all vital rates. Still, the study of selected vital rates constitutes an important first step to understand the relationship between population growth rates and geographical distributions and is essential to better predict how climate change influences species distributions.EkoKli