Abstract
Pain assessment in both communicative and non-communicative patients remains a major clinical challenge due to the inherently subjective nature of conventional tools such as the Numeric Rating Scale (NRS). In this study, we introduce a physiologically grounded and objective index, (Formula presented.), derived from fractional-order impedance modeling of nociceptive dynamics. Here, (Formula presented.) represents the transduction, and (Formula presented.) reflects the transmission. These components are extracted non-invasively using the Anspec-Pro device, which records skin bioimpedance in real-time. A positive (Formula presented.) indicates enhanced central excitability, while a negative value suggests dominant inhibition. In a case study of postoperative patients, we show that (Formula presented.) closely follows and often precedes subjective NRS scores, with correlation coefficients reaching up to 0.86 ((Formula presented.)). We also introduce a refined index, (Formula presented.), which incorporates the trend and local variability of (Formula presented.) for improved temporal alignment with reported pain. To address the very limited dataset (three patients, nineteen intervals each), we implemented a data augmentation strategy based on autoregressive modeling of (Formula presented.) and transfer-function mapping to NRS. This approach enabled the generation of synthetic trajectories per patient, thereby enriching the dataset while maintaining physiological plausibility. Analyses of the augmented data revealed consistent lead–lag patterns, correlations, and Granger causality relationships between (Formula presented.), (Formula presented.), and NRS, suggesting that (Formula presented.) may serve both as an anticipatory biomarker of nociceptive activity and as a real-time index aligned with subjective pain reporting. Overall, these results provide proof-of-concept that the Anspec-Pro device can support objective, non-invasive nociceptive tracking in clinical environments.
| Original language | English |
|---|---|
| Article number | 1704303 |
| Journal | Frontiers in Physiology |
| Volume | 16 |
| DOIs | |
| Publication status | Published - 2026 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:Copyright © 2026 Ben Othman, Copot, Ayvaz, De Keyser and Ionescu.
Keywords
- bioimpedance measurement
- conscious patients
- fractional-order impedance modeling
- nociception
- nociceptive variability
- pain
- subjective–objective
- variability
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