A new and general approach to signal denoising and eye movement classification based on segmented linear regression.

We introduce a conceptually novel method for eye-movement signal analysis. The method is general in that it does not place severe restrictions on sampling frequency, measurement noise or subject behavior. Event identification is based on segmentation that simultaneously denoises the signal and determines event boundaries. The full gaze position time-series is segmented into an approximately optimal piecewise linear function in O(n) time. Gaze feature parameters for classification into fixations, saccades, smooth pursuits and post-saccadic oscillations are derived from human labeling in a data-driven manner. The range of oculomotor events identified and the powerful denoising performance make the method useable for both low-noise controlled laboratory settings and high-noise complex field experiments. This is desirable for harmonizing the gaze behavior (in the wild) and oculomotor event identification (in the laboratory) approaches to eye movement behavior. Denoising and classification performance are assessed using multiple datasets. Full open source implementation is included.

SubsMatch 2.0: Scanpath comparison and classification based on subsequence frequencies.

Our eye movements are driven by a continuous trade-off between the need for detailed examination of objects of interest and the necessity to keep an overview of our surrounding. In consequence, behavioral patterns that are characteristic for our actions and their planning are typically manifested in the way we move our eyes to interact with our environment. Identifying such patterns from individual eye movement measurements is however highly challenging. In this work, we tackle the challenge of quantifying the influence of experimental factors on eye movement sequences. We introduce an algorithm for extracting sequence-sensitive features from eye movements and for the classification of eye movements based on the frequencies of small subsequences. Our approach is evaluated against the state-of-the art on a novel and a very rich collection of eye movements data derived from four experimental settings, from static viewing tasks to highly dynamic outdoor settings. Our results show that the proposed method is able to classify eye movement sequences over a variety of experimental designs. The choice of parameters is discussed in detail with special focus on highlighting different aspects of general scanpath shape. Algorithms and evaluation data are available at: http://www.ti.uni-tuebingen.de/scanpathcomparison.html .

The Craig Hospital Eye Evaluation Rating Scale (CHEERS).

BACKGROUND: Oculomotor deficits in smooth pursuit, saccades, vestibular-ocular reflex (VOR), vergence, and fixation are common problems seen after moderate to severe traumatic brain injury (TBI). No scale currently exists to rate all of these together. The Craig Hospital Eye Evaluation Rating Scale (CHEERS) was designed to systematically quantify frequency and severity of eye movement deficits in TBI. OBJECTIVE: To assess the intra- and interrater reliability of a new rating scale for detecting the presence and degree of 5 oculomotor abnormalities after TBI. DESIGN: A reliability study. SETTING: This was an institution-based study at Craig Rehabilitation Hospital. PARTICIPANTS: English-speaking patients between ages 18 and 65 years with a primary diagnosis of moderate to severe mechanical TBI and who were not blind in either eye were eligible. METHODS: Between October 2013 and March 2014, a total of 11 TBI patients and 9 non-TBI controls were enrolled in the study. The median age was 30 years (range, 18-74 years) for subjects and 52 years (range, 28-63 years) for controls. All patients were male, and 8 of 9 controls were female. Eye movements (fixation, smooth pursuit, saccade, convergence, and vestibular-ocular reflex) were recorded for each on digital video. They were rated on 2 separate occasions by each of the 2 raters. MAIN OUTCOME MEASUREMENTS: Inter- and intrarater reliability tests. RESULTS: Median elapsed time between the first and second ratings was 7 days (range, 5-44 days). Intrarater agreement was very strong (Spearman ρ ≥ 0.900) for pursuit, saccades, and VOR for both raters, and strong (Spearman ρ ≥ 0.710) for vergence and fixation. The interrater agreement for detecting presence of any oculomotor abnormality was substantial (unweighted κ = 0.63). The interrater concordance on the full range of scale scoring was strongest on the VOR test (weighted κ = 0.98), was substantial for vergence, pursuit, saccades, and total score (weighted κ > 0.60), and was moderate for fixation. For TBI patients, every eye movement rated was found to be more abnormal than compared to those in the controls. CONCLUSIONS: CHEERS is a reliable scale for assessing and quantifying oculomotor deficits commonly observed in moderate to severe TBI. Further studies to validate the scale's utility in outcome prediction, and its applicability to broader brain injury populations, are warranted. LEVEL OF EVIDENCE: IV.

Individual differences in the strength of taxonomic versus thematic relations.

Knowledge about word and object meanings can be organized taxonomically (fruits, mammals, etc.) on the basis of shared features or thematically (eating breakfast, taking a dog for a walk, etc.) on the basis of participation in events or scenarios. An eye-tracking study showed that both kinds of knowledge are activated during comprehension of a single spoken word, even when the listener is not required to perform any active task. The results further revealed that an individual's relative activation of taxonomic relations compared to thematic relations predicts that individual's tendency to favor taxonomic over thematic relations when asked to choose between them in a similarity judgment task. These results indicate that individuals differ in the relative strengths of their taxonomic and thematic semantic knowledge and suggest that meaning information is organized in 2 parallel, complementary semantic systems.