Electromyography Pattern Likelihood Analysis for Flexion-Relaxation Phenomenon Evaluation
Round 1
Reviewer 1 Report
The study evaluates the flexion-relaxation phenomenon (FRP) and the differences in the electromyography patterns. The proposed method calculates a validity range for FRP. The method could be used to classify healthy and patients with low back pain. The proposed method was better at finding FRP when compared to existing methods. The study also provides baseline RMS values in electromyographic signals.
Overall the manuscript is well organized with a satisfactory description
of the proposed method and analysis of results. However, there are several
typographical and grammatical mistakes that need to be corrected.
For e.g
line 95: rms should be upper case RMS
line 123: Should begin with "It was.."
line 140: "Precisely was taken.." The sentence needs clarification.
line 164 "inner": should be (inside)
line 165 "outer": should be (outside)
line 199: "He was" should be "The subject"
line 201: "And so on" should be removed.
There is also a need to test the method on a larger dataset and more subjects. The conclusion identifies this limitation
and has proposed additional experiments as a future study.
As a result, the reviewer suggests acceptance after minor grammatical corrections.
Author Response
Comment R.1.1:
line 95: rms should be upper case RMS
Response: We thank the reviewer for the opportunity to improve the quality of the paper.
Action(s) taken: We decided to proceed with the change.
Comment R.1.2:
line 123: Should begin with "It was..”
Response: We thank the reviewer for the opportunity to improve the quality of the paper.
Action(s) taken: We decided to proceed with the change.
Comment R.1.3:
line 140: "Precisely was taken.." The sentence needs clarification.
Response: We thank the reviewer for the opportunity to improve the quality of the paper.
Action(s) taken: We decided to proceed with the sentence clarification.
Comment R.1.4:
line 164 "inner": should be (inside)
Response: We thank the reviewer for the opportunity to improve the quality of the paper.
Action(s) taken: We decided to proceed with the change.
Comment R.1.5:
line 165 "outer": should be (outside)
Response: We thank the reviewer for the opportunity to improve the quality of the paper.
Action(s) taken: We decided to proceed with the change.
Comment R.1.6:
line 199: "He was" should be "The subject"
Response: We thank the reviewer for the opportunity to improve the quality of the paper.
Action(s) taken: We decided to proceed with the change.
Comment R.1.7:
line 201: "And so on" should be removed.
Response: We thank the reviewer for the opportunity to improve the quality of the paper.
Action(s) taken: We decided to proceed with the change.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
The paper is clearly structured and with data clearly presented. The main concern is that the choise of golden stand is not necessary very appropriate. Although the author stated that the GS was with the best regular patterns within the tested subjects, it is difficult to quntify regular pattern. It need to be supported in literature, or maybe supproted by simulation model. It is not clear how sensitive the developed algrithem is related to the chosen GS as refernce. If the GS changed, will that change the results significantly?
Also, it is no very clear how the clasification can help the clinician to improve the treatment of the patients? Can the algrithem provide further classification within the patients and the cause of the pain?
The language will also need further proofreading as there are some obvious mistakes. Here some examples are listed below.
In abstract, line 14, imcomplete sentence, there is a full stop after patients which I don't think should be.
Sentence from line 118, suggest to rewrite.
Author Response
Comment R.2.1:
The paper is clearly structured and with data clearly presented. The main concern is that the choice of golden stand is not necessary very appropriate. Although the author stated that the GS was with the best regular patterns within the tested subjects, it is difficult to quantify regular pattern. It needs to be supported in the literature, or maybe supported by simulation model. It is not clear how sensitive the developed algorithm is related to the chosen GS as reference. If the GS changed, will that change the results significantly?
Response: We thank the reviewer for the opportunity to improve the quality of the paper. The use of the gold standard represents one of the innovations introduced by this article to find the threshold validity range, therefore it is not present in the scientific literature as regards the subject matter. Clearly, we have tested other regular patterns as GS and the results are very similar to each other. The choice of the GS was made empirically by choosing the subject who, through visual inspection (VIS), presented a high and regular muscle relaxation. Furthermore, the GS as depicted in the block scheme define the first range and with the other iterations, other subjects with FRP are also taken into consideration to better define the final range.
Action(s) taken: We tried to answer the questions
Comment R.2.2:
Also, it is no very clear how the classification can help the clinician to improve the treatment of the patients? Can the algorithm provide further classification within the patients and the cause of the pain?
Response: We thank the reviewer for the opportunity to improve the quality of the paper. We try to clarify this concept. If the subject considered have not regular patterns and he is affected by low back pain the clinician starts the treatment. The treatment should reduce the levels of myoelectric activity and so the RMS values, improving health conditions. Applying this algorithm, we can see the improvements of the RMS values and when they will have values inside the FRP validity range the treatment can be stopped or reduced. So, this system gives feedback to the clinician to understand if the treatment must continue or not. Assessing the cause of pain on a clinical level is very complex, what you can see is whether the treatment influences muscle relaxation.
Action(s) taken: We tried to answer the questions
Comment R.2.3:
In abstract, line 14, incomplete sentence, there is a full stop after patients which I don't think should be.
Response: We thank the reviewer for the opportunity to improve the quality of the paper.
Action(s) taken: We decided to proceed with the sentence change
Comment R.2.4:
Sentence from line 118, suggest rewriting.
Response: We thank the reviewer for the opportunity to improve the quality of the paper.
Action(s) taken: We decided to proceed with the sentence change
Author Response File: Author Response.pdf
Reviewer 3 Report
This study describes electromyography pattern likelihood analysis for flexion-relaxation phenomenon evaluation. This is an interesting paper, but significant corrections are required:
1. The Introduction section needs to be rewritten:
- It is not clear what the importance of this objective. In this reviewer’s opinion, there needs to be a stronger motivation as to why the stated aims of the study are relevant or useful for clinicians or scientist;
- How does this study differ from the other studies, and what new useful information does it offer?
- Please add an example(s) about the open questions that are still under investigation regarding the algorithms to provide an FRP evaluation.
2. Methods:
- You mentioned that your study is based on the previous study. However, the manuscript is hard to read without sufficient information about the study group. There is no clear information about the patients involved in this study. Please, clarify the subject’s selection criteria;
- There is no mention of how any of the ethical issues inherent in this type of research (confidentiality, etc.) were addressed.
The number of the ethical agreement should be included.
- The measurement protocol should be clearly presented in this study;
- Please provide validity (accuracy/precision and error) and reliability information for the measurement system.
- Did you apply any pre-processing techniques to EMG signal?
- Please, add the statistical analysis plan.
3. Results:
- the demographic data of patients included in this study should be added in the Results section;
- how can the findings present in tab1 of the study be useful?
- what recommendations can be given based on the findings of this study?
4. Please, add the discussion section. Your discussion section should be constructed as follows. Consider revising it to include this information:
· Rephrase the question followed by the answer that was reached from the results.
· Describe how the data support the answers to the questions.
· Compare to other studies.
· Present the strengths and limitations.
· Combine the information in the previous paragraphs into a coherent whole, within the framework of the hypotheses.
Author Response
Comment R.3.1:
The Introduction section needs to be rewritten:
- It is not clear what the importance of this objective. In this reviewer’s opinion, there needs to be a stronger motivation as to why the stated aims of the study are relevant or useful for clinicians or scientist;
- How does this study differ from the other studies, and what new useful information does it offer?
- Please add an example(s) about the open questions that are still under investigation regarding the algorithms to provide an FRP evaluation.
Response: We thank the reviewer for the opportunity to improve the quality of the paper. This research provides an alternative classification method, based on RMS threshold, to find the FRP presence/absence, compared to those present in the literature (for example: Schinkel-Ivy, Alison, Brian C. Nairn, and Janessa DM Drake. "Evaluation of methods for the quantification of the flexion-relaxation phenomenon in the lumbar erector spinae muscles." Journal of manipulative and physiological therapeutics 36.6 (2013): 349-358), starting from a gold standard subject and varying the acceptance range through iteration. The goal is to provide an alternative method, to identify the threshold, that can improve the classification. It also provides reference RMS values for the muscles considered that are not present in the literature. Understand the typical RMS values during the full flexion for longissimus and multifidus is important to understand if the physiotherapy treatments improve muscle relaxation by reducing RMS values compared to the pre-physiotherapy values. The open questions that are still under investigation regard the best method to evaluate the FRP. While in the previous study we have used the FRR method (based on the ratio between signal levels during different phases) there we have used the threshold method, which in Schinkel-Ivy opinion, provided the optimal trade-off between performance, consistency, and feasibility. This study offers a new method useful to identify the threshold because many times empirical threshold values are defined but it is not clear how they were obtained (for example THR1 defined by Alison).
Action(s) taken: We tried to answer the questions
Comment R.3.2:
Methods:
- You mentioned that your study is based on the previous study. However, the manuscript is hard to read without sufficient information about the study group. There is no clear information about the patients involved in this study. Please, clarify the subject’s selection criteria;
- There is no mention of how any of the ethical issues inherent in this type of research (confidentiality, etc.) were addressed.
The number of the ethical agreement should be included.
- The measurement protocol should be clearly presented in this study;
- Please provide validity (accuracy/precision and error) and reliability information for the measurement system.
- Did you apply any pre-processing techniques to EMG signal?
- Please, add the statistical analysis plan.
Response: We thank the reviewer for the opportunity to improve the quality of the paper. We decided to add the subject’s selection section (inclusion and exclusion criteria), ethical statement, and Acknowledgments section. We have added a section with the type of measurement system used and the detailed electrodes positioning.
Action(s) taken: We decided to proceed adding on the text as required
Comment R.3.3:
- the demographic data of patients included in this study should be added in the Results section;
- how can the findings present in tab1 of the study be useful?
- what recommendations can be given based on the findings of this study?
Response: We thank the reviewer for the opportunity to improve the quality of the paper. The data in Table 1 are useful to understand directly the FRP level, if it is present/absent in all the cycles or only in some if it is present/absent in all the channels or only in some. In Table 2 there is a summary of demographic data, but all the other data are in the anamnesis file (Mendeley dataset) together with the physical conditions (disability, perceived pain) [https://data.mendeley.com/datasets/g7pdm5prvp/1].
Action(s) taken: We tried to answer the questions
Comment R.3.4:
Please, add the discussion section. Your discussion section should be constructed as follows. Consider revising it to include this information:
- Rephrase the question followed by the answer that was reached from the results.
- Describe how the data support the answers to the questions.
- Compare to other studies.
- Present the strengths and limitations.
- Combine the information in the previous paragraphs into a coherent whole, within the framework of the hypotheses.
Response: We thank the reviewer for the opportunity to improve the quality of the paper.
Action(s) taken: We have added the discussion section
Author Response File: Author Response.pdf
Round 2
Reviewer 2 Report
Thanks for the reply from the author. I still have the concern about the choise of gold standard. It should be further discussed in the dicussion section about when the chose of goldern stand change, whether the result will still be valid. This could be the limitation of this study. Maybe in future study, a simulation model can be used to simulate a perfect FRP process and generate the GS. Or, further data can be collected and get the mean value as a GS.
In abstract, abbreviation should not use used, for example FRP, as this is the first time this is read by a reader.
Author Response
Comment R.2.1:
Thanks for the reply from the author. I still have the concern about the choice of gold standard. It should be further discussed in the discussion section about when the choice of the gold standard change, whether the result will still be valid. This could be the limitation of this study. Maybe in future study, a simulation model can be used to simulate a perfect FRP process and generate the GS. Or further data can be collected and get the mean value as a GS.
Response: We thank the reviewer for the opportunity to improve the quality of the paper.
Action(s) taken: We decided to proceed by adding in the discussion section a talk about the gold standard and possible other implementations (highlighted in green).
Comment R.2.2:
In abstract, abbreviation should not use used, for example FRP, as this is the first time this is read by a reader.
Response: We thank the reviewer for the opportunity to improve the quality of the paper.
Action(s) taken: We decided to proceed with the removal of the abbreviation adding the synonym “myoelectric silence” (highlighted in green).
Author Response File: Author Response.pdf
Reviewer 3 Report
Some corrections have been made. There is lacks novelty and credible motivation of the study in the Introduction section. The Discussion section still needs improvement!
Author Response
Comment R.3.1:
Some corrections have been made. There is lacks novelty and credible motivation of the study in the Introduction section. The Discussion section still needs improvement!
Response: We thank the reviewer for the opportunity to improve the quality of the paper. The characteristics of the sEMG signals are influenced by many confounding factors and therefore a lot depends on the performance of sEMG pattern recognition systems. It is necessary to translate the complex information inside the sEMG patterns into useful feedback signals, to identify the flexion-relaxation phenomenon and the neuromuscular diseases, using advanced data analysis and algorithms capable of analyzing big data [Phinyomark, Angkoon, and Erik Scheme. "EMG pattern recognition in the era of big data and deep learning." Big Data and Cognitive Computing 2.3 (2018): 21.]. But the problem is that typically the dataset used in each research is too small for machine learning. So, multiple-datasets provided by many publications can be used to investigate the generalization and robustness of sEMG pattern recognition methods, but only to a certain extent. A major limitation of the multiple-dataset investigation approach is that sEMG signals from different datasets cannot be combined into one larger set due to experimental and equipment differences (there is no consensus on the sampling rate, filtering, etc. due to the use of different sEMG acquisition devices). This represents one of the major difficulties in applying machine learning algorithms putting together different datasets acquired with different systems. For this reason, we have used a "classical classification approach" which represents an alternative and/or complementary method to the Visual Inspection (VIS) and Flexion-Relaxation Ratio method.
Action(s) taken: We decided to proceed to add other information in the discussion section hoping that it can be useful in making the article clearer to the reader (highlighted in green).
Author Response File: Author Response.pdf
Round 3
Reviewer 3 Report
I accept the corrections made in the Discussion section. The manuscript has been improved.
