Issue title: [REVIEW]: QPrism: A Python Library for Quality Assessment of Sensor Data Collected in Real-world Settings
 Issue body: **Submitting author:** <!--author-handle-->@RamziHalabi<!--end-author-handle--> (<a href="http://orcid.org/0000-0002-3784-9556">Ramzi Halabi</a>)
**Repository:** <!--target-repository-->https://github.com/aid4mh/QPrism<!--end-target-repository-->
**Branch with paper.md** (empty if default branch): <!--branch--><!--end-branch-->
**Version:** <!--version-->v.0.3.3<!--end-version-->
**Editor:** <!--editor-->@galessiorob<!--end-editor-->
**Reviewers:** <!--reviewers-list-->@lucask07, @jodemaey<!--end-reviewers-list-->
**Archive:** <!--archive-->Pending<!--end-archive-->

## Status

[![status](https://joss.theoj.org/papers/98bd3b1f7a60613fb61f70d4a3092a42/status.svg)](https://joss.theoj.org/papers/98bd3b1f7a60613fb61f70d4a3092a42)

Status badge code:

```
HTML: <a href="https://joss.theoj.org/papers/98bd3b1f7a60613fb61f70d4a3092a42"><img src="https://joss.theoj.org/papers/98bd3b1f7a60613fb61f70d4a3092a42/status.svg"></a>
Markdown: [![status](https://joss.theoj.org/papers/98bd3b1f7a60613fb61f70d4a3092a42/status.svg)](https://joss.theoj.org/papers/98bd3b1f7a60613fb61f70d4a3092a42)
```
**Reviewers and authors**:

Please avoid lengthy details of difficulties in the review thread. Instead, please create a new issue in the <a href="https://github.com/aid4mh/QPrism" target="_blank">target repository</a> and link to those issues (especially acceptance-blockers) by leaving comments in the review thread below. (For completists: if the target issue tracker is also on GitHub, linking the review thread in the issue or vice versa will create corresponding breadcrumb trails in the link target.)

## Reviewer instructions & questions

@lucask07 & @jodemaey, your review will be checklist based. Each of you will have a separate checklist that you should update when carrying out your review.
First of all you need to run this command in a separate comment to create the checklist:

```
@editorialbot generate my checklist
```

The reviewer guidelines are available here: https://joss.readthedocs.io/en/latest/reviewer_guidelines.html. Any questions/concerns please let @galessiorob know.

✨ **Please start on your review when you are able, and be sure to complete your review in the next six weeks, at the very latest** ✨ 


## Checklists

<!--checklist-comments-->
  @lucask07, please create your checklist typing: `@editorialbot generate my checklist`

  @jodemaey, please create your checklist typing: `@editorialbot generate my checklist`

<!--end-checklist-comments-->

 Comments: 
 Comment 0: Hello humans, I'm @editorialbot, a robot that can help you with some common editorial tasks.

For a list of things I can do to help you, just type:

```
@editorialbot commands
```

For example, to regenerate the paper pdf after making changes in the paper's md or bib files, type:

```
@editorialbot generate pdf
```

 Comment 1: ```
Software report:

github.com/AlDanial/cloc v 1.88  T=0.27 s (320.4 files/s, 45870.5 lines/s)
-------------------------------------------------------------------------------
Language                     files          blank        comment           code
-------------------------------------------------------------------------------
Jupyter Notebook                14              0           3896           5081
Python                          44            467            721           1256
reStructuredText                10             88             40            221
Markdown                         3             62              0            115
TeX                              1             12              0             95
TOML                             1              6              0             45
DOS Batch                        1              8              1             26
JSON                            10              0              0             10
make                             1              4              7              9
-------------------------------------------------------------------------------
SUM:                            85            647           4665           6858
-------------------------------------------------------------------------------


gitinspector failed to run statistical information for the repository
```
 Comment 2: Wordcount for `paper.md` is 1409
 Comment 3: :point_right38d1:d2b4:3d06:83e8:96a5:8c2:893d:aba5page_facing_up: [Download article proof](https://raw.githubusercontent.com/openjournals/joss-papers/joss.04839/joss.04839/10.21105.joss.04839.pdf) :page_facing_up: [View article proof on GitHub](https://github.com/openjournals/joss-papers/blob/joss.04839/joss.04839/10.21105.joss.04839.pdf) :page_facing_up: :point_left:
 Comment 4: 👋  @lucask07, @jodemaey

Thank you both for volunteering to review this paper! Please type and comment `@editorialbot generate my checklist`, this will generate a checklist with each of the aspects for you to review regarding the software, documentation, and the paper. Please let me know if you have any questions and feel free to post them directly in this issue.
 Comment 5: @editorialbot generate my checklist
 Comment 6: @editorialbot generate my checklist
 Comment 7: I have concerns regarding _substantial scholarly effort_ and if the contributions are accurately communicated.

1. The [JOSS scope and submission](https://joss.theoj.org/about#code_of_conduct) requirements state:
> Minor 'utility' packages, including 'thin' API clients, and single-function packages are not acceptable.

The functions I have checked seem to be a 'thin' API client. For example: [audio_sample_rate](https://github.com/aid4mh/QPrism/blob/main/QPrism/Audio/audio_sample_rate.py) is 2 lines of code

2. Other functions are unfamiliar and the mathematics are not defined in the documentation. 
For example the [SCR](https://github.com/aid4mh/QPrism/blob/main/QPrism/Sensor/SCR.py) calculation. I understand from the paper that the acronym is the sensor channel ratio. The mathematics and purpose of the sensor channel ratio needs to be defined. 

3. Metrics make unsubstantiated claims. For example, [video artificats](https://github.com/aid4mh/QPrism/blob/main/QPrism/Video/artifacts.py) states to detect video frames of artifacts including "motion blur, too grainy, static". However, the software only calculates the frame histogram and then determines if more than 50% of the pixels in a frame lie within 5% to 100% of the histogram span. This is not sufficient to determine if artifacts are present in an image.

4. Generally sensor evaluation needs a calibrated and defined input. For example, the spatial resolution of a camera is assessed by imaging a resolution chart; the conversion factor, SNR, and linearity of an accelerometer are measured by applying known accelerations. It is not clear how sensors can be assessed without known inputs. 
 Comment 8: @editorialbot add @sidihamady as reviewer
 Comment 9: @sidihamady added to the reviewers list!
 Comment 10: @sidihamady Please type and comment @editorialbot generate my checklist, this will generate a checklist with each of the aspects for you to review regarding the software, documentation, and the paper. Please let me know if you have any questions and feel free to post them directly in this issue.
 Comment 11: @lucask07 I'm reviewing your comment above and will reply soon. Thank you!
 Comment 12: I would like to request some clarifications regarding the **Contribution and authorship** point. I noticed that the main/first author of the paper has only made a single commit with one line. It seems that all the authors are roughly from the same lab so it might be ok, but please clarify it here.
 Comment 13: Regarding the scholarly effort and documentation, I also noticed that the package uses by default pre-trained models to classify audio ([yamnet](https://tfhub.dev/google/yamnet/1)) and detect objects in video ([yolov5](https://docs.ultralytics.com/)) while this being barely documented and linked. 

Also, the functions of the package being involved with these feature mainly channel the result of these models to the users. Therefore I concur with @lucask07 that this is a concern regarding the **Substantial scholarly effort** and *thin API* point.
 Comment 14: > I would like to request some clarifications regarding the **Contribution and authorship** point. I noticed that the main/first author of the paper has only made a single commit with one line. It seems that all the authors are roughly from the same lab so it might be ok, but please clarify it here.

That is correct. I am the first author of this paper, and I am the main contributor to the design and coding of the data quality functions, with emphasis on sensor data quality metrics, as well as drafting the manuscript. We distributed the tasks amongst ourselves to submit to JOSS, and the most repository-contributing co-author to push and publish a clean version of the code to GitHub is Zixiong Lin. I had already written and implemented the functions on a large database for another paper, so have all other members at different contribution levels that may not be measured using the number of Github commits.
@jodemaey  I hope this answers your concern, and I'll be glad to provide feedback whenever needed.
 Comment 15: Yes, thanks for the clarification. 
 Comment 16: @editorialbot generate my checklist
 Comment 17: I agree with my colleagues @lucask07 and @jodemaey that there is a concern about "substantial scientific effort and thin API point". A a reminder, the JOSS guide details this item:

- Age of software (is this a well-established software project) / length of commit history.
- Number of commits.
- Number of authors.
- Total lines of code (LOC). Submissions under 1000 LOC will usually be flagged, those under 300 LOC will be desk rejected.
- Whether the software has already been cited in academic papers.
- Whether the software is sufficiently useful that it is likely to be cited by your peer group.

[https://joss.readthedocs.io/en/latest/submitting.html#substantial-scholarly-effort](https://joss.readthedocs.io/en/latest/submitting.html#substantial-scholarly-effort)

We have to check if each of the points in the list is fulfilled.
 Comment 18: @galessiorob - I read the reviewers' comments on our codes and paper, and I was wondering whether we are expected to interact and provide answers/clarifications at this stage. It would be very helpful to know this before we address the raised concerns. 
Thanks in advance.
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