prouast / inertial-sensor-processing

Import and processing of inertial sensor data for intake gesture recognition. Support for Clemson Cafeteria, Food Intake Cycle, and OREBA datasets.

inertial-sensor-processing

Processing of inertial sensor data for intake gesture detection.

Features

Implemented processing steps include mirroring, gravity removal, smoothing, and standardization. Export as csv or tfrecord files. Specific labels can be selected by including a specification file.

Supported datasets currently include:

• OREBA-DIS and OREBA-SHA
• Clemson Cafeteria
• Food Intake Cycle (FIC)

Usage

Make sure that all requirements are fulfilled

$ pip install -r requirements.txt

Then call main.py.

$ python main.py --src_dir=OREBA-DIS

The following flags can be used to specify the settings:

Argument	Description	Default
--src_dir	Recordings directory	OREBA_Dataset_Public_1_0/oreba_dis/recordings
--exp_dir	Directory for data export	Export
--dataset	Which dataset is used {OREBA-DIS, OREBA-SHA, Clemson, or FIC}	OREBA-DIS
--sampling_rate	Sampling rate of exported signals in Hz	64
--use_vis	If True, enable visualization	False
--use_gravity_removal	If True, remove gravity during preprocessing	True
--use_smoothing	If True, apply smoothing during preprocessing	False
--use_standardization	If True, apply standardization during preprocessing	True
--smoothing_window_size	Size of the smoothing window [number of frames]	1
--smoothing_order	The polynomial used in Savgol filter	1
--smoothing_mode	Smoothing mode {medfilt, savgol_filter, moving_average}	moving_average
--exp_mode	Write file for publication or development {pub, dev}	dev
--exp_uniform	Convert all dominant hands to right and all non-dominant hands to left	True
--exp_format	Format for export {csv, tfrecord}	csv
--label_spec	Filename of label specification	label_spec/OREBA_only_intake.xml
--label_spec_inherit	Inherit label specification for sublabels (if label not included, always keep sublabels as Idle)	True
--dom_hand_spec	Filename containing the dominant hand info	dominant_hand.csv
--organise_data	If True, organise data in train, valid, test subfolders	False
--organise_dir	Directory to copy train, val and test sets using data organiser	Organised
--organise_subfolders	Create sub folder per each file in validation and test set	False

Label specfication

Control what labels are included by selecting or editing the appropriate label_spec file. This only applies to the OREBA and Clemson datasets. Templates are available in the label_spec directory.