EgaitSegmentationValidation2014#
Further Links:
A challenge for stride segmentation from continuous IMU data @Lab and in simulated @home environments.
General Information#
- Dataset
The Egait Segmentation Validation 2014 dataset [1] is used for this challenge (usage example, download). It contains 4x10m gait tests from 30 participants (10 controls, 10 Parkinson’s disease, 10 geriatric patients) and 15 simulated @home tests from 5 participants per cohort (5 controls, 5 Parkinson’s disease, 5 geriatric patients ).
- Sensor System
All participants wore Shimmer2R (102.4 Hz) IMUs laterally on both shoes.
- Reference System
All trials where recorded with a video camera to make the original annotations (not used in this challenge). In addition, the data was expert labeled based on the raw gyro data. The original annotations explicitly excluded turns and stairs. The new annotations included all gait like movements (turns, stairs, etc.). This challenge uses the new annotations. For a challenge using the original annotations, see
egait_segmentation_validation_2014_original_label. All annotations where performed following the stride definition by [1].
Implementation Recommendations#
This challenge version (using the new annotations) expects algorithms to be able to segment all types of strides including turns and stairs. This means algorithms likely need be more sensitive.
The data does only contain gait and no other movements. This should make this a relatively easy dataset for gait segmentation.
References#
Barth, Jens, Cäcilia Oberndorfer, Cristian Pasluosta, Samuel Schülein, Heiko Gassner, Samuel Reinfelder, Patrick Kugler, et al. “Stride Segmentation during Free Walk Movements Using Multi-Dimensional Subsequence Dynamic Time Warping on Inertial Sensor Data.” Sensors (Switzerland) 15, no. 3 (March 17, 2015): 6419-40. https://doi.org/10.3390/s150306419.