Incheol Han

Heart rate variability (HRV) is a non-invasive physiological indicator of autonomic nervous system activity and provides an objective means to assess psychological states such as perceived stress and resilience. This study investigated whether HRV can reflect individual tendencies in terms of perceived stress and resilience, as assessed by the Perceived Stress Scale (PSS), the Connor–Davidson Resilience Scale (CD-RISC), and their combined groups according to the Perceived Stress Scale (PSS), the Connor–Davidson Resilience Scale (CD-RISC), and their combined groups, and examined the autonomic mechanisms underlying these constructs. Ninety-two adults completed both questionnaires and participated in a stress-induction protocol based on the Trier Social Stress Test, consisting of pre-resting, stress session, and post-resting sessions. HRV features across time, frequency, and nonlinear domains were extracted from the resting, reactivity, and recovery phases, analyzed with linear mixed models, and applied in classification models using sequential forward selection and leave-one-subject-out cross-validation. The results showed that high PSS participants exhibited reduced parasympathetic activity primarily at rest, whereas high CD-RISC individuals demonstrated higher parasympathetic activity and autonomic balance across all phases, with greater stability under acute stress and faster recovery. The combined PSS–CD-RISC grouping revealed compounded autonomic dysfunction in the high-stress–low-resilience quadrant. Classification accuracies reached approximately 82% for PSS and CD-RISC separately and 87% when combined, with resilience-related models benefiting particularly from reactivity and recovery features in addition to resting indices. These findings demonstrate that HRV captures distinct autonomic processes underlying stress and resilience, indicating that the two constructions are not redundant but complementary. HRV thus holds promise as a supportive indicator in wearable systems for continuous monitoring and personalized intervention.

The quantification of comfort in binding parts, essential human–machine interfaces (HMI) for the functioning of rehabilitation robots, is necessary to reduce physical strain on the user despite great achievements in their structure and control. This study aims to investigate the physiological impacts of binding parts by measuring electrodermal activity (EDA) and tissue oxygen saturation (StO₂). In Experiment 1, EDA was measured from 13 healthy subjects under three different pressure conditions (10, 20, and 30 kPa) for 1 min using a pneumatic cuff on the right thigh. In Experiment 2, EDA and StO₂ were measured from 10 healthy subjects for 5 min. To analyze the correlation between EDA parameters and the decrease in StO₂, a survey using the visual analog scale (VAS) was conducted to assess the level of discomfort at each pressure. The EDA signal was decomposed into phasic and tonic components, and the EDA parameters were extracted from these two components. RM ANOVA and a post hoc paired t-test were used to determine significant differences in parameters as the pressure increased. The results showed that EDA parameters and the decrease in StO₂ significantly increased with the pressure increase. Among the extracted parameters, the decrease in StO₂ and the mean SCL proved to be effective indicators. Such analysis outcomes would be highly beneficial for studies focusing on the comfort assessment of the binding parts of rehabilitation robots.