  Many sexually mature females suffer from premenstrual syndrome (PMS), but
effective coping methods for PMS are limited due to the complexity of symptoms
and unclear pathogenesis. Awareness has shown promise in alleviating PMS
symptoms but faces challenges in long-term recording and consistency. Our
research goal is to establish a convenient and simple method to make individual
female aware of their own psychological, and autonomic conditions. In previous
research, we demonstrated that participants could be classified into non-PMS
and PMS groups based on mood scores obtained during the follicular phase.
However, the properties of neurophysiological activity in the participants
classified by mood scores have not been elucidated. This study aimed to
classify participants based on their scores on a mood questionnaire during the
follicular phase and to evaluate their autonomic nervous system (ANS) activity
using a simple device that measures pulse waves from the earlobe. Participants
were grouped into Cluster I (high positive mood) and Cluster II (low mood).
Cluster II participants showed reduced parasympathetic nervous system activity
from the follicular to the menstrual phase, indicating potential PMS symptoms.
The study demonstrates the feasibility of using mood scores to classify
individuals into PMS and non-PMS groups and monitor ANS changes across
menstrual phases. Despite limitations such as sample size and device
variability, the findings highlight a promising avenue for convenient PMS
self-monitoring.
