Tiejun Miao

Chaos of plethysmogram in relation to scalp-EEG: a model and experiments

We studied a relation of chaotic dynamics of finger plethysmogram to scalp-EEG in both theoretical and experimental approaches. We proposed a mathematical model to describe emergence of chaos in finger tip pulse wave, which gave a theoretical prediction indicating increased chaoticity in higher cerebral centre leading to an increase of chaos dynamics in plethysmograms. We designed an experiment to observe scalp-EEG and finger plethysmogram using two mental tasks to validate the relationship. We found that scalp-EEG showed an increase of the largest Lyapunov exponents (LLE) during speaking certain voices. Topographical scalp map of LLE showed enhanced arise around occipital and right cerebral area. Whereas, there was decreasing tendency during listening music, where LLE scalp map revealed a drop around centre cerebral area. The same tendency was found from finger plethysmograms under

Effect of anesthesia on chaotic dynamics in finger plethysmograms

Chaotic dynamics in finger plethysmogram system was studied in relation to anesthesia processes. The experiments were conducted to observe the changes in finger plethysmogram before, during, and after the anesthesia for a surgery. The largest Lyapunov exponent of the plethysmograms was found to be significant and can be used to correlate the temporal variations of mental/physical status in the processes. There were lower values o f Lyapunov exponents during anesthesia, showing the block effect of anesthesia on central nervous system. There were highly Lyapunov exponents in recovery consciousness from anesthesia. To understand how the chaos arises and to explain the changes in the Lyapunov exponent in finger plethysmograms in experiments, a mathematical model consisting of baroreflex feedback and autonomous interactions was proposed and studied numerically. The decrease of the largest Lyapunov exponent in plethysmograms was explained successfully by the model in relation to the decreased chaoticity, and hence the depressed or blocked central nervous system in higher cerebral region.

Relationship between fractal dimension and favorability of facial imagery

Why do people feel happy and good or empathize more, with smiling faces than with expressionless faces? To understand the mechanism involved in the recognition of facial imagery, we evaluated the degree of favorability for 46 expressionless and smiling facial images obtained from young persons including 84 subjects having no pre-acquired knowledge to the experiments. Each image was presented to every subject and was asked to rank favorability on a scale from 1 to 10. By using of two types of fractal analysis, i.e., planner and cubic analyses, fractal dimensions of facial images were obtained in order to characterize the complexity of the images. Furthermore, we calculated the local fractal dimensions around parts of eyes and mouths. The results showed a significant difference in the local fractal dimension around mouths between the expressionless and smiling faces. On the other hand, we found a strong correlation between the degree of favorability and fractal dimensions of whole faces. However, a significant correlation between the local fractal dimensions around mouths and favorability was not found. These showed that humans recognized face in the wholly way, rather than locally, when we defined the favorability of facial imagery. These results imply that the fractal dimension obtained in relation to complexity in imagery optically information is useful in characterizing the psychological processes of cognition and awareness.

Relationship between Fractal Dimension and Agreeability of Facial Imagery

Why do people feel happy and good or equivalently empathize more, with smiling face imageries than with ones of expressionless face? To understand what the essential factors are underlying imageries in relating to the feelings, we conducted an experiment by 84 subjects asked to estimate the degree of agreeability about expressionless and smiling facial images taken from 23 young persons to whom the subjects were no any pre‐acquired knowledge. Images were presented one at a time to each subject who was asked to rank agreeability on a scale from 1 to 10. Fractal dimensions of facial images were obtained in order to characterize the complexity of the imageries by using of two types of fractal analysis methods, i.e., planar and cubic analysis methods, respectively. The results show a significant difference in the fractal dimension values between expressionless faces and smiling ones. Furthermore, we found a well correlation between the degree of agreeability and fractal dimensions, implying that the fractal d...

A Self‐Check System for Mental Health Care based on Nonlinear and Chaos Analysis

We applied nonlinear and chaos analysis to fingertip pulse wave data. The largest Lyapunov exponent, a measure of the “divergence” of the trajectory of the attractor in phase space, was found to be a useful index of mental health in humans, particularly for the early detection of dementia and depressive psychosis, and for monitoring mental changes in healthy persons. Most of the methods used for assessing mental health are subjective. A few of existing objective methods, such as those using EEG and ECG, for example, are not simple to use and expansive. Therefore, we developed an easy‐to‐use economical device, a PC mouse with an integrated sensor for measuring the pulse waves, and its required software, to make the measurements. After about 1 min of measurement, the Lyapunov exponent is calculated and displayed as a graph on the PC. An advantage of this system is that the measurements can be made very easily, and hence mental health can be assessed during operating a PC using the pulse wave mouse. Moreover...

Development of the equipment measuring the degree of the mental activity

In order to measure the mental activity, people measured the subjects oral consultation data, cardiac beats, a pulse wave, brain waves, an electromyogram, action patterns, and so on, together with analyzed data. Regarding the vital signs are the information on a complexity system, we were treating a slight change of vital signs as an error. However, very important information was included in this error. The degree of mental activity which is the information on the complexity system was not able to be solved by the conventional method. In this paper, nonlinear analysis of the pulse wave of a fingertip was conducted, and the fluctuation value was computed. Furthermore, the simulation of a mathematical model and the experiment of anesthesia proved that the value had the information on a central system. The apparatus which can measure the degree of mental activity was developed using this.

Plethysmogram and EEG: Effects of Music and Voice Sound

We studied a relation of chaotic dynamics of finger plethysmogram to complexity of high cerebral center in both theoretical and experimental approaches. We proposed a mathematical model to describe emergence of chaos in finger tip pulse wave, which gave a theoretical prediction indicating increased chaoticity in higher cerebral center leading to an increase of chaos dynamics in plethysmograms. We designed an experiment to observe scalp‐EEG and finger plethysmogram using two mental tasks to validate the relationship. We found that scalp‐EEG showed an increase of the largest Lyapunov exponents (LLE) during speaking certain voices. Topographical scalp map of LLE showed enhanced arise around occipital and right cerebral area. Whereas there was decreasing tendency during listening music, where LLE scalp map revealed a drop around center cerebral area. The same tendency was found for LLE obtained from finger plethysmograms as ones of EEG under either speaking or listening tasks. The experiment gave results that...

Consideration for improvement of demetia that uses communications

We measured plethysmograms and calculated Largest Lyapunov Expornent (LLE ) with nonlinear analysis method. We found the value of LLE had significant relation to dementia degree and the communication skill of the ADL index for the measurement of 144 elderly people. We made a mathematical model to discuss the obtained experimental results by studying simulated what kind of information was able to extract from the plethysmograms data. Furthermore, we performed the measurement when we blocked the central nerve by general anesthesia to inspect the mathematical model. As a result, the data of the pulse wave elucidated that we included information of nucleus of the brain origin. In other words we got the conclusive evidence of having meaningful relation to dementia and LLE and a communication skill. We had an old man communicate in friendly care manager to an elderly people from these facts and measured the pulse wave at the same time. We calculated a sympathetic nerve, the value of the parasympathetic (LF/HF, HF) at the same time. As a result, the person whom LLE activated by communication had a low HF, and the person who was not activated understood that HF was in a high state. In other words an effect of the communication was accepted when an elderly people awoke. By this study, the communication was able to prove that we helped the mental activation of the elderly people scientifically.

Chaos in plethysmograms during tracking chaos

A tracking experiment was designed to observe how chaotic variations in ear plethysmogram were related to tracking targets with different predictabilities including chaos. We found the maximum Lyapunov exponent computed from plethysmograms had higher value during tracking chaotic orbital signals in compare with both simply deterministic signal and random ones. Also there was found a lower variance of the difference between target and tracking during tracking the chaos target, whereas there was obviously large variance in tracking random target. A mathematical model consisting of baroreflex feedback and autonomous interactions was proposed to explain the changes in ear plethysmograms, pointing to give a guide in future applications using the tracking experiment. With the help of simulation, the model sowed that there was increased active temporal information processing in higher cerebral region during tracking chaos target.

Is the perceived agreeability of a face related to the fractal dimension of the face

Why do people feel happy and good or empathize more, with smiling faces than with expressionless faces? To understand the mechanism involved in the recognition of facial imagery, we evaluated the degree of agreeability for 46 expressionless and smiling facial images obtained from young persons including 84 subjects having no pre-acquired knowledge to the experiments. Each image was presented to every subject and was asked to rank agreeability on a scale from 1 to 10. By using of two types of fractal analysis, i.e., planner and cubic analyses, fractal dimensions of facial images were obtained in order to characterize the complexity of the images. Furthermore, we calculated the local fractal dimensions around parts of eyes and mouths. The results showed a significant difference in the local fractal dimension around mouths between the expressionless and smiling faces. On the other hand, we found a strong correlation between the degree of agreeability and fractal dimensions of whole faces. However, a significant correlation between the local fractal dimensions around mouths and agreeability was not found. These showed that humans recognized face in the wholly way, rather than locally, when we defined the agreeability of facial imagery. These results imply that the fractal dimension obtained in relation to complexity in imagery optically information is useful in characterizing the psychological processes of cognition and awareness.