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.