[PRE REVIEW]: CIMAP: Clustering for Identification of Muscle Activation Patterns

[editorialbot]

Submitting author: !--author-handle-->@gregoriodotti<!--end-author-handle-- (GREGORIO DOTTI) Repository: https://github.com/marcoghislieri/CIMAP/ Branch with paper.md (empty if default branch): Version: v1.0.4 Editor: Pending Reviewers: Pending Managing EiC: George K. Thiruvathukal

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Software report:

github.com/AlDanial/cloc v 1.88  T=0.15 s (341.1 files/s, 154505.4 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
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JavaScript                      15           2435           2505           9215
HTML                            11            375             33           2875
SVG                              1              0              0           2671
Python                           5            178            226            808
CSS                              6            189             45            774
reStructuredText                 6            152             51            205
TeX                              1             13              0            123
Markdown                         3             35              0            122
DOS Batch                        1              8              1             26
YAML                             1              1              0             18
make                             1              4              7              9
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SUM:                            51           3390           2868          16846
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gitinspector failed to run statistical information for the repository

[editorialbot]

Wordcount for paper.md is 1152

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Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

OK DOIs

- None

MISSING DOIs

- 10.1016/0013-4694(87)90003-4 may be a valid DOI for title: EMG profiles during normal human walking: stride-to-stride and inter-subject variability
- 10.1016/j.bspc.2016.09.017 may be a valid DOI for title: Muscle activation patterns during gait: A hierarchical clustering analysis
- 10.1109/embc.2017.8036762 may be a valid DOI for title: Muscle contractions in cyclic movements: Optimization of CIMAP algorithm
- 10.1109/tnsre.2019.2903687 may be a valid DOI for title: Asymmetry index in muscle activations
- 10.3390/s19030657 may be a valid DOI for title: The use of wearable sensors for the movement assessment on muscle contraction sequences in post-stroke patients during sit-to-stand
- 10.1016/s0013-4694(96)95190-5 may be a valid DOI for title: A comparison of computer-based methods for the determination of onset of muscle contraction using electromyography
- 10.1109/10.661154 may be a valid DOI for title: A statistical method for the measurement of muscle activation intervals from surface myoelectric signal during gait
- 10.1186/s12984-021-00945-w may be a valid DOI for title: Long short-term memory (LSTM) recurrent neural network for muscle activity detection
- 10.1016/j.gaitpost.2010.06.024 may be a valid DOI for title: Normative EMG activation patterns of school-age children during gait
- 10.1186/s12984-015-0079-4 may be a valid DOI for title: Does texting while walking really affect gait in young adults?
- 10.1109/lsc.2018.8572041 may be a valid DOI for title: Emg asymmetry index in cyclic movements
- 10.1109/memea.2018.8438802 may be a valid DOI for title: Longitudinal assessment of muscle function after Total Hip Arthroplasty: Use of clustering to extract principal activations from EMG signals
- 10.1016/j.arth.2013.12.018 may be a valid DOI for title: Gait parameters and muscle activation patterns at 3, 6 and 12 months after total hip arthroplasty

INVALID DOIs

- None

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[gregoriodotti]

@editorialbot check references

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Reference check summary (note 'MISSING' DOIs are suggestions that need verification):

OK DOIs

- 10.1016/0013-4694(87)90003-4 is OK
- 10.1016/j.bspc.2016.09.017 is OK
- 10.1109/embc.2017.8036762 is OK
- 10.1109/tnsre.2019.2903687 is OK
- 10.3390/s19030657 is OK
- 10.1016/s0013-4694(96)95190-5 is OK
- 10.1109/10.661154 is OK
- 10.1186/s12984-021-00945-w is OK
- 10.1016/j.gaitpost.2010.06.024 is OK
- 10.1186/s12984-015-0079-4 is OK
- 10.1109/lsc.2018.8572041 is OK
- 10.1109/memea.2018.8438802 is OK
- 10.1016/j.arth.2013.12.018 is OK

MISSING DOIs

- None

INVALID DOIs

- None

[arfon]

@editorialbot query scope

@gregoriodotti – apologies for the slow response here but I think we need to put this submission through a scope review with the JOSS editorial team. Looking at the size of the Python code, and it's application, I'm not completely sure this submission is in scope for JOSS.

The scope review may take a couple of weeks to complete. Thanks for your patience!

[editorialbot]

Submission flagged for editorial review.

[arfon]

@gregoriodotti – in order to help with the scope review. Could you confirm which aspects of this submission are novel code? For example, is all of the JavaScript dependencies/libraries?

[gregoriodotti]

@arfon - I will do all that I can to help you with the scope review. The novel code is all Python code and it is stored in the CIMAP folder inside the repository. I think that all JavaScript is the dependencies/libraries. Could it also be code stored in the "docs" folder that contains all the tools for the creation of the "read the docs" documentation?

[gkthiruvathukal]

@arfon Thanks for putting this through scope review. @gregoriodotti Thank you for following up with your input.

I am the track EIC for this submission. I have taken a look at the Python code. As a Python programmer myself, I find the overall organization and documentation a bit lacking. It is not readily apparent how someone would use CIMAP. Your docs mention how to install it but are not clear on how to use it. From what I can tell, there is no command-line interface in this code, so it is very wired for a specific use case and data set. What other data sets have been tested? The code seems confined to a single monolithic Python module, https://github.com/marcoghislieri/CIMAP/blob/main/CIMAP/CIMAP.py with a set of tests in a separate subdirectory. So there are some concerns about the scholarly effort as well.

The more important issue, however, was raised earlier by @arfon. What problem is actually being solved here? It is not clear any other researchers would use it, given the rather stringent limit of focusing on a particular ad hoc data format that could just as easily be replaced with a more open scientific data format (e.g. HDF or XML).

My inclination is to reject this submission but we always give authors a chance to respond to feedback. Please respond by January 12 AOE so I can decide on the next steps.

[gregoriodotti]

We would like to start by thanking you, @gkthiruvathukal and @arfon, for the time spent revising our work and for the insightful feedback. Furthermore, thanks for giving us the chance to respond to your comments. In the following, please find the point-by-point response to all of your concerns.

Q1: As a Python programmer myself, I find the overall organization and documentation a bit lacking. It is not readily apparent how someone would use CIMAP. Your docs mention how to install it but are not clear on how to use it. R1: Thanks for your comment. Following your suggestion, we further improve the documentation by adding more information about how to use our algorithm (see ReadTheDocs page). Moreover, references to the Algorithm functions and Applying CIMAP to gait analysis sections of the ReadTheDocs were added to the README file. The Algorithm functions section contains a description of all the functions used within the CIMAP algorithm, while the Applying CIMAP to gait analysis section contains a complete example of CIMAP application from data loading to the representation of the results step.

Q2: From what I can tell, there is no command-line interface in this code, so it is very wired for a specific use case and data set. What other data sets have been tested? R2: The shared dataset is only a representative dataset containing the muscle activation intervals calculated from sEMG signals of a healthy subject during walking that can be used to test the algorithm and to understand its outputs. However, this algorithm can be potentially applied to muscle activation intervals computed from a great variety of cyclical movements spanning from walking to grasping and reaching. To date, we have successfully applied and tested CIMAP on muscle activation intervals computed during walking in both physiological and pathological conditions (e.g., freely available sEMG dataset (DOI: 10.5281/zenodo.3932767)) and during different cyclical movements (e.g., reach-to-grasp movements). Here is a list of publications in which CIMAP has been used:

• DOI: 10.1109/I2MTC.2017.7969746
• DOI: 10.1109/TNSRE.2019.2903687
• DOI: 10.1109/TNSRE.2020.2965179
• DOI: 10.1109/EMBC46164.2021.9629818
• DOI: 10.1109/MeMeA52024.2021.9478738
• DOI: 10.3390/s21217186

Q3: The code seems confined to a single monolithic Python module, https://github.com/marcoghislieri/CIMAP/blob/main/CIMAP/CIMAP.py with a set of tests in a separate subdirectory. So there are some concerns about the scholarly effort as well.

R3: Following your comment, we reorganized the Python code into smaller modules, each of them containing a specific task performed by the CIMAP algorithm, to increase its interpretability and readability. A detailed description of each module is reported in the Algorithm functions section of the ReadTheDocs page.

Q4: The more important issue, however, was raised earlier by @arfon. What problem is actually being solved here? It is not clear any other researchers would use it, given the rather stringent limit of focusing on a particular ad hoc data format that could just as easily be replaced with a more open scientific data format (e.g. HDF or XML).

R4: The temporal analysis of muscle activations is of great interest in several research areas, spanning from neurorobotic systems to the assessment of altered locomotion patterns in orthopedic and neurological patients and the monitoring of their motor rehabilitation. However, due to the high intra-cycle variability of the muscle activation intervals, an accurate and precise description of the muscle activation patterns (that is required to properly assess orthopedic or neurological patients or rehabilitation outcomes) is difficult. Specific approaches, such as CIMAP, can deal with the intrinsic variability of muscle activation patterns by supporting engineers, clinicians, and physical therapists in the assessment of the muscle activation patterns during specific movements. Thus, CIMAP may represent a useful (and open-source) toolbox for helping researchers (of any programming skill level working in different research areas such as biomedical engineering, robotics, sports, clinics, biomechanics, and neuroscience) to easily characterize and assess muscle activation patterns during cyclical movements. In other words, the algorithm allows for identifying patterns in muscle activation intervals by grouping cycles characterized by similar time patterns and increasing the interpretability of the results. Concerning the open scientific data format, we completely agree that HDF or XML formats are preferable to CSV format in the context of open science, thus, as soon as possible, compatibility with XML data format will be added to allow the user to choose the preferred data format.

Thank you all for giving us the possibility to respond to your concerns. Best regards, GD

[arfon]

@gregoriodotti – many thanks for the detailed feedback. Unfortunately, after further review by the JOSS editorial team we've determined that this submission doesn't meet our substantial scholarly effort criterion. This isn't to say that the submission is of no value to the community, rather this submission simply isn't eligible to be published here.

One possible alternative to JOSS is to follow GitHub's guide on how to create a permanent archive and DOI for your software. This DOI can then be used by others to cite your work.

[arfon]

@editorialbot reject

[editorialbot]

Paper rejected.

[editorialbot]

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