Consumer Physics Developers Site | Using SCiO Lab Mobile

To start work on a new Data Collection, you’ll need to log into SCiO Lab from a web browser at: sciolab.consumerphysics.com.
Data Collections can only be created in SCiO Lab.

iOS/Android SCiO Universe Mobile Application

SCiO Lab Mobile is the mobile iOS/Android app you’ll use to scan with SCiO and gain initial data and feedback about your scan.

SCiO Lab Mobile is essential for working with SCiO. You won’t be able to sync, calibrate or scan without it.

SCiO Lab Mobile uses the same Consumer Physics universal login as do SCiO Lab and your developer account.

Once you log in, you need to sync your SCiO sensor with the SCiO Lab Mobile app. Click on the red (X) sync icon in the upper right hand side of the screen to view the list of SCiOs within range.

If you have more than one SCiO, choose the one with the most reception in the list. SCiO and your phone are now synced. Re-sync as needed, such as when you upgrade SCiO Lab Mobile etc.

SCiO requires calibration before you can begin scanning. SCiO will alert you via SCiO Lab Mobile when your SCiO requires calibration. Simply insert your SCiO with the optical head into the cover and follow the on screen prompts and your SCiO will be calibrated and ready to use to scan. Expect to calibrate periodically, you will be notified when required.

To calibrate your SCiO, click the menu button and select Calibrate SCiO.

To help you get started, we have provided two default data collections within your SCiO Lab account. The first time you log in to SCiO Lab or SCiO Lab Mobile, you’ll see them listed as shown below.

Scan, Scan, Scan

Once SCiO is synced and calibrated, you can begin to collect your samples, add attributes and start scanning.

You’ll want to make sure you document what is unique, or different about each sample, to help you prove, test and utilize your data model.

Attributes allow you to differentiate samples within SCiO Lab. Automatic attributes are provided by the system and cannot be changed.

Sample attributes are the way to highlight, mark and identify all of the important characteristics of each sample you scan. The more complete you make your attributes, the most useful you’ll find your model later on.

Now that you have scanned and received your results, let’s review the data and learn more about how you can use the features available to analyze it.

Note:While it is easier and more comprehensive to review scan data in SCiO Lab, SCiO Lab Mobile can also be used for this purpose.

Click the data collection to view the summary data for the collection.

Understanding the Data Collections summary screen.

Select the attribute in the drop-down list to group the scan data by. (In this case, we group by Fat).
The attribute description. In this case, the percentage of fat in the sample material.
Tip: Use meaningful names for your attributes.
Click Test Model to test a model you’ve already created on a new sample.
Note: Test scans are not added to the collection.
Click the Spectra icon to go to spectra view.
The total number of scans for that attribute.
Click + to add new scan data.

Clicking the Spectra icon displays the spectra details

Tip: When you rotate your phone to landscape view, SCiO Lab Mobile provides a legend shows you the spectra with the processing algorithms. Tapping the standard share icon will also allow you to share the scan. The spectra legend and spectra share functionality are not available in portrait mode.

SCiO scan records (spectra) look like this:

You can see and select specific data points on the spectrum field.

When viewing the scans of a data collection, the preprocessing options allow you to view your data collection spectrum with different algorithms applied. These can help you identify outliers, inaccurate scans and reveal possible relationships in your data.

Within the graphs SCiO Lab Mobile presents:

X is the wavelength represented in nm (nanometers).

Y is dependent on the state of the toggle buttons you select.

When:

Nothing is selected: Raw reflectance spectrum
Processed (only): Assumes Beer-Lambert model is valid, and transforms the measured signal to be linear with concentration by doing a log transform and adjusting the result for noise and deviations from the model. You can learn more about Beer-Lambert here: http://www.chemguide.co.uk/analysis/uvvisible/beerlambert.html
Normalized (only): Performs normalization of the signal. This is meant to compensate for changing measurement conditions (e.g. varied scanning distances) that typically occur from sample to sample. Y axis still means reflectance but in normalized units instead of raw reflectance.
Both Processed and Normalized: First assumes Beet-Lambert model (Processed) and then normalizes the results to compensate for differences in the optical path between samples. This is useful, for example, when there is variation in the thickness of the samples.

Typically, different models and types of samples will require different pre-processing methods. You should both choose the pre-processing method to match your experimental setup and optimize the performance of your model. If you planned and gathered your data correctly, these efforts will coincide.

Tip: More preprocessing options are available when using SCiO Lab (web). Use SCiO Lab Mobile for initial review and SCiO Lab (web) for deep analysis of your data collections.

SCiO Lab Mobile allows you to share your scans with the world. To share a scan, shift your smartphone to landscape view and use the share icon to share your spectra via social media or email.

Share icon from landscape view