Portable Holonomic Educational Robot Platform for Home Laboratory—Study Case: AI-Based Electromyography Control
Round 1
Reviewer 1 Report
Comments and Suggestions for Authorsplease see the attached pdf file
Comments for author File: 
Comments.pdf
Author Response
We are very grateful for the reviewer comments and suggestions, please find the answer in the attached file.
Author Response File: Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsThis study develops a lightweight omnidirectional mobile platform for remote education that integrates a distributed communication architecture with a hybrid convolutional recurrent network for electromyography gesture decoding. After careful assessment of the system integration and experimental validation I recommend a major revision.
(1)Kinematic coupling matrix derivation skips explicit wheel radius measurements.
(2)Bandpass filter settings lacks detailed specification for raw signal conditioning.
(3)For 3D vision robot applications: 3D vision technologies for a self-developed structural external crack damage recognition robot; Automation in Construction.
(4)Normalization procedure ignores channel crosstalk during muscle activation trials.
(5)LSTM sequence length gets truncated without clear justification.
(6)PID tuning parameters omit explicit stability margin calculations.
(7)Communication latency reports miss precise timestamp synchronization methods.
(8)Training dataset composition fails to document variability between subjects.
(9)Power distribution scheme excludes battery discharge curve analysis.
(10)Questionnaire sampling methodology overlooks proper demographic stratification.
(11)Messaging protocol hierarchy lacks explicit service quality definitions.
(12)Validation procedure skips testing across separate sessions entirely.
(13)Chassis structural analysis omits material fatigue threshold specifications.
Author Response
We are very grateful for the reviewer comments and suggestions, please find the answer in the attached file.
Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for Authors
Manuscript title
A Portable Holonomic Educational Robot Platform for Home Laboratory; Study Case: AI-based Electromyography Control
Authors
Erick Noboa, Lourdes Ruiz Salvador, Gyorgy Eigner, Peter Galambos
The holonomic robotic system developed in the presented study is an advanced project in the testing and improvement stage. Such projects exist in the world and are based on the same principles stated in the article.
The bibliography is current and contains thirty-five references, all from the last five years, which is a good selection, with only one self-citation.
The manuscript is descriptive, well structured, the details provided allow the reproduction of the device, and the discussions highlight its performance and accuracy, as training equipment in universities.
The most problematic part is not the holonomic robot, but the human-machine interface: the biological signal is variable, and the robot reacts quickly. Therefore, success depends on filtering, interpretation and safety more than on mechanics.
However, there are several aspects that require more in-depth discussions, such as:
-gesture recognition knowing that the transformation of EMG into commands is not perfect and typical problems could appear (confusion between similar gestures, false classifications of involuntary movements, delay until the algorithm decides, the need for recalibration);
-wireless and latency;
-control sensitivity;
-human ergonomics;
-safety (automatic stop on signal loss, speed limitation, safety zone, obstacle avoidance);
-discrete vs. continuous control.
Considering the above, I believe that the manuscript can be considered for publication after major revision.
Comments on the Quality of English Language
The English phrasing could be improved.
Author Response
We are very grateful for the reviewer comments and suggestions, please find the answer in the attached file.
Author Response File: Author Response.pdf
Reviewer 4 Report
Comments and Suggestions for AuthorsThe manuscript presents a portable holonomic robotic platform for home-based education, integrating embedded control, holonomic kinematics, and EMG-based control using a CNN-LSTM model. The topic is relevant and aligns well with current trends in remote education and human–machine interaction. The paper is suitable for the MDPI journal Technologies. However, in its current form, the manuscript lacks sufficient scientific rigor, particularly in the experimental validation and clarity of the contribution. I have the following comments for the authors:
1. Abstract is too long. Please consider a reduction (up to ~200 words).
2. The novelty of the work is not clearly stated. Please explicitly define what is new compared to existing educational robotic platforms and EMG-based control systems.
3. Important details are missing in the description of the experimental setup (EMG classification), i.e., dataset size, number of subjects, training/testing split, and validation methodology. Without this, the reported accuracies (~80–99%) are not sufficiently supported. Please consider completion.
4. The PID controller evaluation is based only on a single step response. The authors could include quantitative metrics (e.g., rise time, overshoot, steady-state error) and discuss robustness.
5. Key parameters are missing in the description of the AI model training (e.g., loss function, optimizer, batch size, training procedure). The authors should provide sufficient detail to ensure reproducibility.
6. The manuscript does not compare the proposed approach with baseline methods (e.g., SVM, LDA, or simpler models). Such a comparison is necessary to justify the use of CNN-LSTM.
7. The paper has presented a kinematic model, but the derivation and parameter definitions are unclear. Please improve clarity and provide numerical values where applicable.
8. The subjective evaluation lacks methodological detail in the evaluation using NASA-TLX (e.g., number of participants and statistical analysis). Please clarify or reconsider its inclusion.
9. The caption of Figure 1 should also include a description of the individual parts of the device shown (e.g., 1 - ..... 2 - .... etc). Please revise.
10. Please revise the reference list and provide DOIs for all cited journal articles where available.
Author Response
We are very grateful for the reviewer comments and suggestions, please find the answer in the attached file.
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
Comments and Suggestions for AuthorsI am satisfied with this improved version of the paper. In my opinion, the paper can be accepted now.
Reviewer 2 Report
Comments and Suggestions for AuthorsOK
Reviewer 3 Report
Comments and Suggestions for AuthorsManuscript title
A Portable Holonomic Educational Robot Platform for Home Laboratory; Study Case: AI-based Electromyography Control
Authors
Erick Noboa, Lourdes Ruiz Salvador, Gyorgy Eigner, Peter Galambos
I have carefully read the revised version of the manuscript, and I have found that the authors have introduced additional discussions to respond to the recommendations received. Of course, the aspects were not fully covered, and where it was not possible to develop the study, the authors have formulated acceptable justifications. Other issues reported will remain in the attention of researchers for further development, within other future studies.
At this stage, I appreciate that the manuscript has been completed and enriched so that it has become more consistent and comprehensive.
Given the findings, I believe that the work can be accepted for publication in its present form.
Comments for author File: Comments.pdf
The English phrasing could be improved.
Reviewer 4 Report
Comments and Suggestions for AuthorsI thank the authors for addressing all my comments and improving the quality of the paper. I have no further comments for the authors. I suggest that the revised manuscript be accepted for publication. I wish the authors success.
