Factors predicting the mathematics anxiety of adolescents: a structural equation modeling approach.

Introduction: Mathematics anxiety (MA) is a distinct negative emotional state or trait that individuals experience when confronted with mathematical problems in everyday life and academic contexts. This study aims to identify the key predictors of MA among secondary-level students in Bangladesh.

Methods: Utilizing a quantitative cross-sectional research design, data were collected from 486 students across 89 institutions.

CluSem: Accurate clustering-based ensemble method to predict motor imagery tasks from multi-channel EEG data.

Background: The classification of motor imagery electroencephalogram (MI-EEG) is a pivotal task in the biosignal classification process in the brain-computer interface (BCI) applications. Currently, this bio-engineering-based technology is being employed by researchers in various fields to develop cutting-edge applications. The classification of real-time MI-EEG signals is the most challenging task in these applications.

Telemonitoring Parkinson's disease using machine learning by combining tremor and voice analysis.

Background: With the growing number of the aged population, the number of Parkinson's disease (PD) affected people is also mounting. Unfortunately, due to insufficient resources and awareness in underdeveloped countries, proper and timely PD detection is highly challenged. Besides, all PD patients' symptoms are neither the same nor they all become pronounced at the same stage of the illness.

Technological advancements and opportunities in Neuromarketing: a systematic review.

Neuromarketing has become an academic and commercial area of interest, as the advancements in neural recording techniques and interpreting algorithms have made it an effective tool for recognizing the unspoken response of consumers to the marketing stimuli. This article presents the very first systematic review of the technological advancements in Neuromarketing field over the last 5 years. For this purpose, authors have selected and reviewed a total of 57 relevant literatures from valid databases which directly contribute to the Neuromarketing field with basic or empirical research findings.

Smart autism - a mobile, interactive and integrated framework for screening and confirmation of autism.

Smart Autism is a cloud based, automated framework for autism screening and confirmation. In developing countries, due to lack of resources and expertise, autism is detected later than early ages which consequently delays timely intervention. Therefore a mobile, interactive and integrated framework is proposed to screen and confirm autism in different age group (0 to 17 years) with 3 layers of assessment process.

An automated approach towards detecting complex behaviours in deep brain oscillations.

Extracting event-related potentials (ERPs) from neurological rhythms is of fundamental importance in neuroscience research. Standard ERP techniques typically require the associated ERP waveform to have low variance, be shape and latency invariant and require many repeated trials. Additionally, the non-ERP part of the signal needs to be sampled from an uncorrelated Gaussian process.

Ensemble classification for robust discrimination of multi-channel, multi-class tongue-movement ear pressure signals.

In this paper we introduce a robust classification framework for tongue-movement ear pressure signals based around an ensemble voting methodology. The ensemble members are comprised of different combinations of sensor inputs i.e.