Lower Limb Prostheses Environmental Context Dataset

Citation Author(s):
Boxuan
Zhong
Rafael L.
da Silva
Minhan
Li
He
Huang
Edgar
Lobaton
Submitted by:
Boxuan Zhong
Last updated:
Sun, 05/24/2020 - 08:57
DOI:
10.21227/d3z5-n231
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Abstract 

This is the data for paper "Environmental Context Prediction for Lower Limb Prostheses with Uncertainty Quantification" published on IEEE Transactions on Automation Science and Engineering, 2020. DOI: 10.1109/TASE.2020.2993399. For more details, please refer to https://research.ece.ncsu.edu/aros/paper-tase2020-lowerlimb. 

Instructions: 

Seven able-bodied subjects and one transtibial amputee participated in this study. Subject_001 to Subject_007 are able-bodied participants and Subject_008 is a transtibial amputee.

 

Each folder in the subject_xxx.zip file has one continuous session of data with the following items: 

1. folder named "rpi_frames": the frames collected from the lower limb camera. Frame rate: 10 frames per second. 

2. folder named "tobii_frames": the frames collected from the on-glasses camera. Frame rate: 10 frames per second. 

3. labels_fps10.mat: synchronized terrain labels, gaze from the eye-tracking glasses, GPS coordinates, and IMU signals. 

3.1 cam_time: the timestamps for the videos, GPS, gazes, and labeled terrains (unit: second). 10Hz

3.2 imu_time: the timestamps for the IMU sensors (unit: second). 40Hz.

3.3 GPS: the GPS coordinates (latitude, longitude)

3.4 rpi_FrameIds, tobii_FrameIds: the frame ID for the lower-limb and on-glasses cameras respectively. The ids indicate the filenames in "rpi_frames" and "tobii_frames" respectively. 

3.5 rpi_IMUs, tobii_IMUs: the imu signals from the two devices. Columns: (accel_x,accel_y,accel_z,gyro_x,gyro_y,gyro_z)

3.6 terrains: the type of terrains the subjects are current on. Six terrains: tile, brick, grass, cement, upstairs, downstairs. "undefined" and "unlabelled" can be regarded as the same kind of data that needs to be deprecated.

 

The following sessions were collected during busy hours (many pedestrians were around):

'subject_005/01', 

'subject_005/02'

'subject_006/01', 

'subject_006/02', 

'subject_007/01', 

'subject_007/02', 

The following sessions were collected during non-busy hours (few pedestrians were around):

'subject_005/03', 

'subject_005/04',

'subject_006/03', 

'subject_006/04',

'subject_007/03', 

'subject_007/04',

'subject_008/01',

'subject_008/02'

The other sessions were collected without specific collecting hours (e.g. busy or non-busy). 

For the following sessions, the data collection devices were not optimized (e.g. non-optimal brightness balance). Thus, we recommend to use these sessions as training or validation dataset but not as testing data.

'subject_001/02'

'subject_003/01'

'subject_003/02'

'subject_003/03'

'subject_004/01'

'subject_004/02'