Lower Limb Prostheses Environmental Context Dataset
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.
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):
The following sessions were collected during non-busy hours (few pedestrians were around):
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.zip (17.86 GB)
- subject_004.zip (2.92 GB)
- subject_008.zip (3.87 GB)
- subject_003.zip (4.56 GB)
- subject_005.zip (8.16 GB)
- subject_002.zip (11.75 GB)
- subject_006.zip (9.67 GB)
- subject_007.zip (6.83 GB)
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