Disentangling the initiation from the response in joint attention: an eye-tracking study in toddlers with autism spectrum disorders.

Joint attention (JA), whose deficit is an early risk marker for autism spectrum disorder (ASD), has two dimensions: (1) responding to JA and (2) initiating JA. Eye-tracking technology has largely been used to investigate responding JA, but rarely to study initiating JA especially in young children with ASD. The aim of this study was to describe the differences in the visual patterns of toddlers with ASD and those with typical development (TD) during both responding JA and initiating JA tasks. Eye-tracking technology was used to monitor the gaze of 17 children with ASD and 15 age-matched children with TD during the presentation of short video sequences involving one responding JA and two initiating JA tasks (initiating JA-1 and initiating JA-2). Gaze accuracy, transitions and fixations were analyzed. No differences were found in the responding JA task between children with ASD and those with TD, whereas, in the initiating JA tasks, different patterns of fixation and transitions were shown between the groups. These results suggest that children with ASD and those with TD show different visual patterns when they are expected to initiate joint attention but not when they respond to joint attention. We hypothesized that differences in transitions and fixations are linked to ASD impairments in visual disengagement from face, in global scanning of the scene and in the ability to anticipate object's action.

An efficient unsupervised fetal QRS complex detection from abdominal maternal ECG.

Non-invasive fetal heart rate is of great relevance in clinical practice to monitor fetal health state during pregnancy. To date, however, despite significant advances in the field of electrocardiography, the analysis of abdominal fetal ECG is considered a challenging problem for biomedical and signal processing communities. This is mainly due to the low signal-to-noise ratio of fetal ECG and difficulties in cancellation of maternal QRS complexes, motion and electromyographic artefacts. In this paper we present an efficient unsupervised algorithm for fetal QRS complex detection from abdominal multichannel signal recordings combining ICA and maternal ECG cancelling, which outperforms each single method. The signal is first pre-processed to remove impulsive artefacts, baseline wandering and power line interference. The following steps are then applied: maternal ECG extraction through independent component analysis (ICA); maternal QRS detection; maternal ECG cancelling through weighted singular value decomposition; enhancing of fetal ECG through ICA and fetal QRS detection. We participated in the Physionet/Computing in Cardiology Challenge 2013, obtaining the top official scores of the challenge (among 53 teams of participants) of event 1 and event 2 concerning fetal heart rate and fetal interbeat intervals estimation section. The developed algorithms are released as open-source on the Physionet website.

A personal monitoring architecture to detect muscular fatigue in elderly.

Muscle fatigue and exercise intolerance are common and frequent symptoms complained by patients with neuromuscular disease. Muscle fatigue would occur when the intended physical activity can no longer be continued or is perceived as involving excessive effort and discomfort. Except for several rare myopathies with specific metabolic derangements leading to exercise-induced muscle fatigue, most studies fail to identify precise pathogenic mechanism of fatigue in this population of patients. On the other hand, apart from canonical examples of neuromuscular diseases, a number of conditions in which muscle apparatus can be involved is known to occur with high prevalence among certain people categories, such as elderly or people undergoing immobilization. In these cases exercise intolerance and muscle fatigue can be severely incapacitating in common daily activities. An objective and smart, unobtrusive techniques, able to objectively measure fatigue phenomenon, would be useful in monitoring muscle function in both NMD patients and patients with secondary skeletal muscle involvement. In this study, we report a novel, non-invasive assistive architecture for the elderly to assess muscle fatigue by biomedical sensors (surface electromyography) using wireless platform during exercise in an ergonomic platform.

Automated extraction and classification of dynamic metrical features of morphological development in dissociated Purkinje neurons.

The morphological development of in vitro single cerebellar Purkinje cells obtained from wild type P1 CD1 mice was assessed through a dedicated non-invasive technique based on image processing algorithms and multivariate analysis. Image processing algorithms were implemented to extract metrical features characterizing cell structure and dendritic arborization from sequential optical micrographs. Quantitative morphological features were analyzed in order to identify relevant metrical characteristics common to Purkinje cells in wild type P1 CD1 mice. Cell arborization was found to be characterized by a high fractal dimension and the directionality and level of complexity were shown to be key features for cell morphology classification, as underlined using a three-way PCA analysis.

Assessment and comparison of neural morphology through metrical feature extraction and analysis in neuron and neuron-glia cultures.

The morphology of dissociated single cerebellar Purkinje cells obtained from wild-type P1 CD1 mice was assessed in the absence and in the presence of glia. A dedicated noninvasive technique based on optical microscopy was developed. Image processing algorithms were implemented to extract metrical features characterizing cell structure and dendritic arborization. The morphological features were analyzed in order to identify quantitative differences in Purkinje cell morphology due to interactions with astrocytes.