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2409.16825

Measurements and System Identification for the Characterization of Smooth Muscle Cell Dynamics

Dilan Öztürk, Pepijn Saraber, Kevin Bielawski, Alessandro Giudici, Leon Schurgers, Koen D. Reesink, Maarten Schoukens

incompletemedium confidence
Category
Not specified
Journal tier
Specialist/Solid
Processed
Sep 28, 2025, 12:56 AM

Audit review

The paper explicitly reports that the LPM noise-only variance is about 30 dB below the FRF estimate and the total variance (noise + nonlinear) is about 10 dB below the FRF estimate, then concludes that when projected back to the output nearly 30% of the system response is due to nonlinearities (Results section, Fig. 9 narrative) . However, the paper does not specify whether those dB offsets are power- or amplitude-based, nor does it show the projection math. Under the standard power-based interpretation consistent with BLA’s variance-additivity y = GBLA u + ys + ny (eq. and discussion) , the correct fraction attributable to nonlinear distortions is about 9% (not 30%). The model solution performs this calculation transparently and is correct on a power basis. The paper’s statement is, at best, ambiguous (likely mixing amplitude-dB with a power fraction) and leaves out key assumptions; hence, the paper is incomplete on this point. Ancillary experimental details (band 0.06–1 Hz, f0 = 0.0781 Hz) align with the model’s context but do not affect the quantitative discrepancy .

Referee report (LaTeX)

\textbf{Recommendation:} minor revisions

\textbf{Journal Tier:} specialist/solid

\textbf{Justification:}

This is a solid integration of multisine-based measurements with LPM/BLA to probe SMC dynamics. The experimental concept and nonparametric identification are timely and useful. However, the quantitative statement that nearly 30\% of the system response is due to nonlinearities is ambiguous and likely arises from mixing amplitude-dB and power fractions. Clarifying the dB convention, providing the exact projection formula, and explicitly stating the assumptions behind the variance decomposition will resolve the discrepancy while preserving the paper’s overall contributions.