Environmental noise may interfere with the reading experience by increasing cognitive load and psychophysiological arousal, yet these effects are difficult to perceive and communicate in real time. This study presents Reading Noise, an interactive installation that combines physiological sensing and sound-driven visualization to externalize perceived noise-related disturbance and psychophysiological strain during reading. In a controlled experiment, 46 participants completed reading tasks under four levels of background conversational noise (0–30, 31–60, 61–90, and >90 dB) while ambient sound level, electrodermal activity (EDA), and electrocardiogram (ECG) were recorded in real time. Following data quality screening, inferential statistical analyses were performed on the analyzable physiological subset (n = 16). Based on these data, a hybrid mapping strategy combining rule-based assignment and LMM-informed exploratory calibration was developed to map acoustic and physiological changes onto dynamic text-based visual parameters, including deformation intensity, jitter, and motion instability, for real-time feedback. Within the analyzable subset, noise level was associated with significant changes in the recorded physiological indicators (all p < 0.05): skin conductance level (SCL) and skin conductance responses per minute (SCRs/min) increased (4.69 ± 2.13 to 5.93 ± 2.19 μS; 1.49 ± 1.59 to 2.51 ± 2.13), whereas the percentage of successive RR intervals differing by more than 50 ms (pNN50) and the root mean square of successive differences (RMSSD) decreased (15.84 ± 16.52% to 10.57 ± 11.35%; 36.63 ± 17.62 to 29.67 ± 16.66 ms). Subjective cognitive load also increased significantly (2.06 ± 0.29 to 6.38 ± 0.31). A follow-up installation study with 24 cross-disciplinary participants, with reported group interaction observations drawn from a 12-participant subset, suggested that the installation may facilitate shared interpretation of attention-related disruption and cognitive strain, indicating the potential of physiology-informed visual translation as a boundary object approach for empathetic, sound-mediated communication.
Li et al. (Mon,) studied this question.