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Article
Peer-Review Record

A Novel Multi-Feedback Differential Filter Instrumentation Amplifier for Βiosignals Acquisition Applications

Electronics 2025, 14(1), 95; https://doi.org/10.3390/electronics14010095
by Athanasios Delis 1,*, Despoina-Polyxeni Georgiou 1, Ioannis Stamelos 2, Eleni Alexandratou 1 and Konstantinos Politopoulos 1
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3: Anonymous
Electronics 2025, 14(1), 95; https://doi.org/10.3390/electronics14010095
Submission received: 17 November 2024 / Revised: 21 December 2024 / Accepted: 26 December 2024 / Published: 29 December 2024
(This article belongs to the Special Issue New Advances of Brain-Computer and Human-Robot Interaction)

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript presents a promising advancement in the field of biosignal acquisition through the development of the MFDFIA. By addressing significant challenges in signal processing, the authors contribute valuable insights to the ongoing research in EEG technology and instrumentation amplifiers. With some adjustments in clarity, structure, and validation, the paper has the potential to make a substantial impact in the field.

Comments for author File: Comments.pdf

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript proposes an innovative design for a Multi-feedback Differential Filter Instrumentation Amplifier (MFDFIA), integrating filtering and amplification into a single circuit to address the limitations of conventional EEG signal acquisition designs. The theoretical analysis is clear, particularly the simplified explanation of differential and common-mode signal behaviour, making the design highly practical for engineering applications. Moreover, simulation results demonstrate excellent performance in terms of noise characteristics and Common Mode Rejection Ratio (CMRR), meeting the requirements for EEG signal acquisition.

However, the following problems cannot be ignored:

 

Lack of Hardware Validation:

All performance data in the article are derived from simulations, with no evidence of hardware testing or real EEG acquisition experiments. The actual performance in real-world environments with noise, artifacts, and power line interference may deviate from simulation results. The absence of hardware validation undermines the credibility of the conclusions. 

The authors performed simulation for the EEG signals in the mV range. However, as mentioned by the authors, the amplitude of real EEG signals is in the micro volt range. Therefore, the simulation does not reflect the practical scenarios.

 

Limited Noise Suppression Capability:

The filter’s high-pass and low-pass slopes are limited to 20 dB/decade, which may not be sufficient to suppress strong noise sources, such as 50/60 Hz power line interference. The article does not discuss potential methods to enhance filtering capabilities.

 

Lack of Comparative Analysis:

The article does not provide detailed comparisons with existing academic work or market products (e.g., AD8232, ADS1299), particularly regarding noise performance and integration. This lack of comparative analysis weakens the presentation of the design's relative advantages.

 

Recommendation:

The authors are advised to address the above issues by supplementing hardware testing and comparative analysis to enhance the credibility and academic impact of the work.

 

 

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

PLease, find attached PDF file.

Comments for author File: Comments.pdf

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

The authors have pretty much addressed my comments. 

Reviewer 3 Report

Comments and Suggestions for Authors

The authors have answered to my questions. 

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