Recognition Tasks

Recognizing surgical tasks is a crucial step toward automatic surgical training in robotic surgery training. In this work, we proposed and developed a classification framework for surgical task recognition. This approach is based on using three components: Dynamic Time Warping (DTW), Procrustes analysis (PA), and Fuzzy k-nearest neighbor (FkNN). First, the DTW method processes multi-channel motion trajectories with different lengths by stretching and compressing both signals such that their lengths become identical. Second, Procrustes analysis is used as a distance measure between two sequences based on shape similarity transformations: rotations, reflection, scaling, and translation. Finally, a Fuzzy k-nearest neighbor algorithm is applied to distinguish between different tasks by assigning a fuzzy class membership based on their distances. We evaluated our framework on a real raw kinematic surgical robotic dataset. Then, we validated the proposed model using Leave One Supertrial Out (LOSO) and Leave One User Out (LOUO) cross-validation schemes. Our results show improvements in the classification of the three different Robot-assisted minimally invasive surgery (RMIS) tasks: suturing, needle-passing, and knot-tying.

Evaluación psicométrica del recuerdo y el reconocimiento de tareas para la medida de la memoria teatral de jóvenes espectadores
Avaluació psicomètrica del record i el reconeixement de tasques per a la mesura de la memòria teatral de joves espectadors

The purpose of this research is the construction and psychometric evaluation of seven categories of recall and recognition tasks for the measurement of young spectators' theatrical memory, based on the respective theatre codes of a specific performance for young audiences. The aim of those tasks is the evaluation of the young spectators' mnemonic recordings on a level of a) the actors' representation of the characters on stage (acting), b) the visual frame of the performance, c) the audio code, d) the lights, e) the dramatic text, f) the plot/action and g) the Shadow Theatre technique. The recall and recognition tasks were constructed according to the Classical Test Theory of Question Analysis on a sample of 5th Grade Primary School pupils, who had seen this specific performance addressed to young spectators and were evaluated with the Factor Analysis method. For the evaluation of the quality of the questions, we took into consideration the difficulty coefficient of each question, the discriminant coefficient and the evaluation of the correlation level

Images, audio, and videos have been used by researchers for a long time to develop several tasks regarding human facial recognition and emotion detection. Most of the available datasets usually focus on either static expression, a short video of changing emotion from neutral to peak emotion, or difference in sounds to detect the current emotion of a person. Moreover, the common datasets were collected and processed in the United States (US) or Europe, and only several datasets were originated from Asia. In this paper, we present our effort to create a unique dataset that can fill in the gap by currently available datasets. At the time of writing, our datasets contain 10 full HD (1920 × 1080) video clips with annotated JSON file, which is in total 100 minutes of duration and the total size of 13 GB. We believe this dataset will be useful as a training and benchmark data for a variety of research topics regarding human facial and emotion recognition.

Differences in pupil dilation are observed for studied compared to new items in recognition memory.
According to cognitive load theory, this effect reflects the greater cognitive demands of retrieving contextual
information from study phase. Pupil dilation can also occur when new items conceptually related to old ones
are erroneously recognized as old, but the aspects of similarity that modulate false memory and related pupil
responses remain unclear. We investigated this issue by manipulating the degree of featural similarity between
new (unstudied) and old (studied) concepts in an old/new recognition task. We found that new concepts with
high similarity were mistakenly identified as old and had greater pupil dilation than those with low similarity,
suggesting that pupil dilation reflects the strength of evidence on which recognition judgments are based and,
importantly, greater locus coeruleus and prefrontal activity determined by the higher degree of retrieval
monitoring involved in recognizing these items.