Shiva Khoshnoud

• Ph.D.
• Post doctoral researcher at Institute for Neuromodulation and Neurotechnology

Recent studies suggest that time estimation relies on bodily rhythms and interoceptive signals. We provide the first direct electrophysiological evidence suggesting an association between the brain's processing of heartbeat signals and duration judgment. We examined heartbeat-evoked potential (HEP) and contingent negative variation (CNV) during an...

This paper examines the relationship between time and motion perception in virtual environments. Previous work has shown that the perception of motion can affect the perception of time. We developed a virtual environment that simulates motion in a tunnel and measured its effects on the estimation of the duration of time, the speed at which perceive...

Similarity quantification is an important field of study in electroencephalogram (EEG)-based brain activity detection, in which the goal is to compute interdependence between certain cortical areas from inter-hemispheric or intra-hemispheric channel pairs. This study aims to propose a new interdependence EEG feature, namely Dynamic frequency warppi...

The flow state-an experience of complete absorption in an activity-is linked with less self-referential processing and increased arousal. We used the heart-evoked potential (HEP), an index representing brain-heart interaction, as well as indices of peripheral physiology to assess the state of flow in individuals playing a video game. 22 gamers and...

Virtual environments are typically associated with entertainment and a fast subjective passage of time. This study examined the opposite effect by exposing participants (n = 83) to a virtual reality (VR) waiting room for 7.5 min. We assessed the participants' capacity for emotion regulation and self-control as well as their level of boredom, affect...

Flow is a mental state characterized by deep absorption during challenging activities, which was first studied by Mihaly Csikszentmihalyi. One of the defining characteristics of this state is the loss of the sense of time. Despite the widespread scientific interest in flow, there are few quantitative studies specifically on the aspect of time perce...

The flow state is defined by intense involvement in an activity with high degrees of concentration and focused attention accompanied by a sense of pleasure. Video games are effective tools for inducing flow, and keeping players in this state is considered to be one of the central goals of game design. Many studies have focused on the underlying phy...

Attention deficit hyperactivity disorder is a neurodevelopmental condition associated with varying levels of hyperactivity, inattention, and impulsivity. This study investigated brain function in children with attention deficit hyperactivity disorder using measures of nonlinear dynamics in electroencephalogram signals during rest. During eyes-close...

Several neurocognitive studies have indicated that children with attention-deficit/hyperactivity disorder (ADHD) exhibit cognitive deficits in perceptual timing functions; however, only a few electroencephalographic studies have investigated their time reproduction abilities. In the present research, 15 children with ADHD were studied along with 19...

Attention deficit hyperactivity disorder is a neurodevelopmental condition associated with varying levels of hyperactivity, inattention, and impulsivity. This study investigates brain function in children with attention deficit hyperactivity disorder using measures of nonlinear dynamics in EEG signals during rest. During eyes-closed resting, 19 cha...

Time Frequency Signal Analysis and Processing (TFSAP) have been proposed in order to analyse the signal in both the time and the frequency domains. Electroencephalography (EEG) as a time-varying frequency signal is an interesting field in which Time Frequency Distribution (TFD) could be used in order to visualize the simultaneous distributions of s...

Cardiac arrhythmia, which means abnormality of heart rhythm, in fact refers to disorder in electrical conduction system of the heart. The aim of this paper is to present a classifier system based on Probabilistic Neural Networks in order to detect and classify abnormal heart rates, where besides its simplicity, has high resolution capability. The p...

One of the most common cardiovascular diseases is Myocardial Ischemia (MI). The aim of this study is improving the diagnosis level of Ischemic Beat detection from ECG signals which is important in ischemic episode detection process. This improvement is based on appropriate feature extraction via Multi resolution Wavelet analysis and proper classifi...

In this study a new fuzzy expert system for ischemic beat detection based on interpretability is proposed. First, efficacious morphologic features which are useful in ischemia detection are extracted by wavelet analysis. Then, subtractive clustering is performed for clustering of normal patterns. Finally after creation of fuzzy system, rule reducti...