Akira Imanishi

Possibility of mental health self-checks using divergence of pulse waves

We conducted a nonlinear analysis of fingertip pulse waves and found that the Lyapunov exponent referencing the “divergence” of chaotic attractor trajectory of fingertip pulse waves is an effective method for determining mental health in humans. In particular, we showed that this method is very effective for the early detection of dementia and depression, as well as in the detection of mental changes in healthy persons. In contrast, current measurement methods to determine mental health are subjective in most cases and are neither objective nor simple enough with respect to time and cost. The development of an apparatus allowing easy measurement for many users is therefore necessary. We illustrate the possibility of mental health self-checks using pulse wave divergence based on a series of examples in previous studies. In addition, we developed software to express the fluctuation of the Lyapunov exponent using time series data from multiple measurements. If changes in mental status can be assessed by studying the fluctuation factor of the Lyapunov exponent, we will be closer to effectively evaluating and controlling mental health problems.

On the largest lyapunov exponents of finger plethysmogram and heart rate under anxiety, fear, and relief states

We investigated the largest Lyapunov exponents (LLEs) of finger plethysmogram (FPG) and heart rate (HR) under anxiety, fear and relief states and compared each measured LLEs with the HR. We devised a task in which the participants experienced the emotions of anxiety, fear, and relief. FPG and HR were recorded during the task, and chaos analysis was applied to FPG to calculate the LLEs. Our results showed significant positive correlations between the LLEs of FPG and the degrees of anxiety and fear. In addition, the degree of relief showed a significant negative correlation with the LLEs of FPG. However, no significant correlation was observed between HR and the degrees of three emotions. These results suggest that the LLEs of FPG are a more sensitive psychological index than the HR.

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.

The application of non-linear methods to the analysis of finger plethysmograms for ergonomics

Chaotic fluctuations in many biological signals have attracted considerable attention since in the assessment of these properties, chaos analysis can extract more informative knowledge than conventional analysis methods such as spectral analysis. Biological signals, particularly chaotic fluctuation of finger plethysmograms, were used to assess the psychophysiological state of workers in ergonomic research of Japan. This paper introduces the method of chaos analysis and the results of our two studies. In both studies, it was shown that chaotic fluctuation (largest Lyapunov exponent) in finger plethysmograms might have the potential to assess the mental workload of workers and to prevent the occurrence of human error. In the future, if we can determine how chaotic fluctuations in finger plethysmograms are related physiological mechanisms, chaos analysis is expected to make a great contribution to various fields.

What affects the Lyapunov exponents of finger plethysmogram

This study investigated the relations between the largest Lyapunov exponents of the finger plethysmogram and pulse indices. First, we made a sine wave that had various pulse intervals and examined the relations using a simulation. Consequently, the largest Lyapunov exponents decreased with the standard deviation of the pulse interval. Next, we carried out two experiments and reexamined the relations using actual measurements of finger plethysmogram recorded during rest and during two mental tasks. We found a significant positive correlation between the standard deviation of the pulse intervals of the finger plethysmogram and the largest Lyapunov exponent, and the correlation coefficient was the highest of pulse indices in two experiments. From these results, we concluded that the largest Lyapunov exponents of the finger plethysmogram are greatly affected by the standard deviation of pulse intervals may be a more reasonable measurement than the largest Lyapunov exponents of the finger plethysmogram.