This is a basic implementation of functionality provided in the open-source R package {mnirs}.

Available from: https://github.com/jemarnold/mnirs
Author: Jem Arnold <currently under development>

mNIRS files can be imported and processed using standardised methods, and displayed in a plot and data table. Processed data can be downloaded for further analysis.

Upload File:

Upload an .xls(x) or .csv file containing mNIRS data exported from many common wearable devices. Files exported from common NIRS devices should be automatically recognised, with the first detected nirs_channel returned.

mNIRS Channel Names:

Specify the column name(s) containing mNIRS data. Multiple channels can be specified using comma-separated new_name = file_column_name pairs.

Example: nirs_channels = c(smo2_left = SmO2, smo2_right = SmO2(2))

Time/Sample Channel Name:

Specify the column containing time or sample values. This channel will be estimated from the file, if not specified.

Example: time_channel = c(time = Timestamp (seconds))

Lap/Event Channel Name (optional):

Optionally specify column with lap/event markers.

Sample Rate:

Specify the exported data sample rate in Hz. This will be automatically estimated from the time channel and can be manually overridden.

Re-sample Rate:

Data can be re-sampled to a desired higher or lower sample rate. Also used to correct time_channel values for data with irregular or duplicated samples.

Trim Head/Tail Timespan:

Remove samples from the beginning or end of the recording, specified in units of time_channel (i.e., seconds).

Replace Invalid Values:

Replace specific fixed values (e.g., c(0, 100)) from nirs_channels.

Replace Outliers:

Remove local outliers using a Hampel filter moving window approach.

Replace Missing Values:

Linearly interpolate across missing nirs_channel values.

Digital Filter Method:

Apply smoothing filters to improve signal-to-noise ratio. Methods include a cubic "smoothing-spline", a low-pass "Butterworth" filter, or a simple "moving average". Additional parameters for each filter method can be specified.

Shift Data:

Move nirs_channels values up or down to a new specified reference value, based on the "first", "minimum", or "maximum" data points. Channels can be shifted together ("Ensemble") or independently ("Distinct").

Rescale Data:

Normalise nirs_channels to a new specified range. Channels can be shifted together ("Ensemble") or independently ("Distinct").

Zero Start Time:

Reset time_channel to start at zero.

Place Event Markers:

Manually add event markers at specified time points. Will add an event_channel to the data table if not already specified, otherwise will add events to an existing event_channel.

Keep All Columns:

Either keep all columns in the file data table (the default), or keep only the channels specified.

Download Data:

Export processed data as an Excel file for further analysis.