Emotion recognition is an attractive and essential topic in image signal processing. In this paper, we propose a multi-level fusion method to combine visual information physiological signals for emotion recognition. For information, serial of two-stage features enhance the representation facial expression video sequence. We integrate Neural Aggregation Network with Convolutional feature map rei...

Recent studies have shown that physiological signals such as heart beat and breathing can be remotely captured from human faces using a regular color camera under ambient light. This technology, referred to remote photoplethysmography (rPPG), used collect the status of users who are in front camera, which may raise privacy concerns. To avoid abuse rPPG this paper develops PulseEdit, novel effic...

With the fast development of wearable medical device in recent years, it becomes critical to conduct research on continuously measured physiological signals. Entropy is a key metric for quantifying the irregularity and/or complexity contained in human physiological signals. In this review, we focus on exploring how entropy changes in various physiological signals in cardiovascular diseases. Our...

The blood-oxygen-level dependent (BOLD) signal in functional MRI (fMRI) reflects both neuronal activations and global physiological fluctuations. These physiological fluctuations can be attributed to physiological low frequency oscillations (pLFOs), respiration, and cardiac pulsation. With typical TR values, i.e., 2 s or longer, the high frequency physiological signals (i.e., from respiration a...

Wearable physiological monitoring systems have gained popularity in the recent years due to their ability to continuously monitor physiological signals, thereby making them suitable for home-healthcare applications. The electrocardiogram (ECG), phonocardiogram (PCG) and photoplethysmogram (PPG) signals have been studied and it has been observed that there is a correlation between the three sign...

The arousal dimension of human emotions is assessed from two different physiological sources: peripheral signals and electroencephalographic (EEG) signals from the brain. A complete acquisition protocol is presented to build a physiological emotional database for real participants. Arousal assessment is then formulated as a classification problem, with classes corresponding to 2 or 3 degrees of...

Functional Near-Infrared Spectroscopy (fNIRS) is a promising method to study functional organization of the prefrontal cortex. However, in order to realize the high potential of fNIRS, effective discrimination between physiological noise originating from forehead skin haemodynamic and cerebral signals is required. Main sources of physiological noise are global and local blood flow regulation pr...

In this century, the rapid development of large data storage technologies, mobile network technology, and portable medical devices makes it possible to measure, record, store, and track analysis of large amount of data in human physiological signals. Entropy is a key metric for quantifying the irregularity contained in physiological signals. In this review, we focus on how entropy changes in va...