Search Results (6)

Copious evidence shows that impaired visual–motor integration (VMI) is intrinsically linked to the core deficits of autism spectrum disorder (ASD) and associated with an anomalous social capability. Therefore, an effective evaluation method of visual–motor behaviour can provide meaningful insight into the evaluation of VMI towards social capability. The current pilot study aims to explore the appropriate quantified metrics for evaluating VMI ability based on a hand-drawn imitation protocol. First, a simple and interesting hand-drawn protocol was designed, and six healthy participants were recruited to perform the task. Then, based on the collected hand–eye behaviour data, several metrics were applied to infer the participant’s social capability and VMI in engagement and visual–motor complexity based on hand–eye properties with Hausdorff distance and cross-recurrence quantification analysis (CRQA). Finally, those quantified metrics were verified through statistical significance. This study proposed a set of quantitative metrics to construct a comprehensive VMI evaluation, including outcome and progress measures. The results revealed the proposed method as a directly interpretable indicator providing a promising computational framework and biomarker for VMI evaluation, paving the way for its future use in ASD diagnosis and guiding intervention. Full article

In recent years, with the frequency of marine disasters, water quality has become an important environmental problem for researchers, and much effort has been put into the prediction of marine water quality. The temporal and spatial correlation of marine water quality parameters directly determines whether the marine time-series data prediction task can be completed efficiently. However, existing research has only focused on the correlation analysis of marine data in a certain area and has ignored the temporal and spatial characteristics of marine data in complex and changeable marine environments. Therefore, we constructed a spatio-temporal dynamic analysis model of marine water quality based on a cross-recurrence plot (CRP) and cross-recurrence quantitative analysis (CRQA). The time-series data of marine water quality were first mapped to high-dimensional space through phase space reconstruction, and then the dynamic relationship among various factors affecting water quality was visually displayed through CRP. Finally, their correlation was quantitatively explained by CRQA. The experimental results showed that our scheme demonstrated well the dynamic correlation of various factors affecting water quality in different locations, providing important data support for the spatio-temporal prediction of marine water quality. Full article

Background: Several algorithms have been proposed to quantify synchronization. However, little is known about their convergent and predictive validity. Methods: The sample included 30 persons who completed a manualized interview focusing on psychosomatic symptoms. The intensity of body motions was measured using motion-energy analysis. We computed several measures of movement synchrony based on the time series of the interviewer and participant: mutual information, windowed cross-recurrence analysis, cross-correlation, rMEA, SUSY, SUCO, WCLC–PP and WCLR–PP. Depressive symptoms were assessed with the Patient Health Questionnaire (PHQ9). Results: According to the explorative factor analyses, all the variants of cross-correlation and all the measures of SUSY, SUCO and rMEA–WCC led to similar synchrony measures and could be assigned to the same factor. All the mutual-information measures, rMEA–WCLC, WCLC–PP–F, WCLC–PP–R2, WCLR–PP–F, and WinCRQA–DET loaded on the second factor. Depressive symptoms correlated negatively with WCLC–PP–F and WCLR–PP–F and positively with rMEA–WCC, SUCO–ES–CO, and MI–Z. Conclusion: More standardization efforts are needed because different synchrony measures have little convergent validity, which can lead to contradictory conclusions concerning associations between depressive symptoms and movement synchrony using the same dataset. Full article

The objective of this study was to examine cardio hypothalamic-pituitary coupling and to better understand how the temporal relations between these systems are altered during rest and exercise conditions. An intensive within subjects study design was used. Seven adult males completed two visits, each consisting of either a 24 h period of complete rest or a 24 h period containing a high-intensity exercise bout. An intravenous catheter was used to collect serum samples every 10 min throughout the 24 h period (i.e., 145 samples/person/condition) to assess growth hormone (GH) dynamics throughout the 24 h period. Cardiac dynamics were also collected throughout the 24 h period and epoched into 3 min windows every 10 min, providing serial short-time measurements of heart rate variability (HRV) concurrent to the GH sampling. The standard deviation of the normal RR interval (SDNN), the root mean square of successive differences (rMSSD), and sample entropy (SampEn) was calculated for each epoch and used to create new profiles. The dynamics of these profiles were individually quantified using SampEn and recurrence quantification analysis (RQA). To address our central question, the coupling between these profiles with GH was assessed using cross-SampEn and cross-RQA (cRQA). A comparison between the epoched HRV profiles indicated a main effect between profiles for sample entropy (p < 0.001) and several measures from RQA. An interaction between profile and condition was observed for cross-SampEn (p = 0.04) and several measures from cRQA. These findings highlight the potential application of epoched HRV to assess changes in cardiac dynamics, with specific applications to assessing cardio hypothalamic-pituitary coupling. Full article

Metabolism and physiology frequently follow non-linear rhythmic patterns which are reflected in concepts of homeostasis and circadian rhythms, yet few biomarkers are studied as dynamical systems. For instance, healthy human development depends on the assimilation and metabolism of essential elements, often accompanied by exposures to non-essential elements which may be toxic. In this study, we applied laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) to reconstruct longitudinal exposure profiles of essential and non-essential elements throughout prenatal and early post-natal development. We applied cross-recurrence quantification analysis (CRQA) to characterize dynamics involved in elemental integration, and to construct a graph-theory based analysis of elemental metabolism. Our findings show how exposure to lead, a well-characterized toxicant, perturbs the metabolism of essential elements. In particular, our findings indicate that high levels of lead exposure dysregulate global aspects of metabolic network connectivity. For example, the magnitude of each element’s degree was increased in children exposed to high lead levels. Similarly, high lead exposure yielded discrete effects on specific essential elements, particularly zinc and magnesium, which showed reduced network metrics compared to other elements. In sum, this approach presents a new, systems-based perspective on the dynamics involved in elemental metabolism during critical periods of human development. Full article

This article contributes to the discourse on how contemporary computer and information technology may help in improving foreign language learning not only by supporting better and more flexible workflow and digitizing study materials but also through creating completely new use cases made possible by technological improvements in signal processing algorithms. We discuss an approach and propose a holistic solution to teaching the phonological phenomena which are crucial for correct pronunciation, such as the phonemes; the energy and duration of syllables and pauses, which construct the phrasal rhythm; and the tone movement within an utterance, i.e., the phrasal intonation. The working prototype of StudyIntonation Computer-Assisted Pronunciation Training (CAPT) system is a tool for mobile devices, which offers a set of tasks based on a “listen and repeat” approach and gives the audio-visual feedback in real time. The present work summarizes the efforts taken to enrich the current version of this CAPT tool with two new functions: the phonetic transcription and rhythmic patterns of model and learner speech. Both are designed on a base of a third-party automatic speech recognition (ASR) library Kaldi, which was incorporated inside StudyIntonation signal processing software core. We also examine the scope of automatic speech recognition applicability within the CAPT system workflow and evaluate the Levenstein distance between the transcription made by human experts and that obtained automatically in our code. We developed an algorithm of rhythm reconstruction using acoustic and language ASR models. It is also shown that even having sufficiently correct production of phonemes, the learners do not produce a correct phrasal rhythm and intonation, and therefore, the joint training of sounds, rhythm and intonation within a single learning environment is beneficial. To mitigate the recording imperfections voice activity detection (VAD) is applied to all the speech records processed. The try-outs showed that StudyIntonation can create transcriptions and process rhythmic patterns, but some specific problems with connected speech transcription were detected. The learners feedback in the sense of pronunciation assessment was also updated and a conventional mechanism based on dynamic time warping (DTW) was combined with cross-recurrence quantification analysis (CRQA) approach, which resulted in a better discriminating ability. The CRQA metrics combined with those of DTW were shown to add to the accuracy of learner performance estimation. The major implications for computer-assisted English pronunciation teaching are discussed. Full article