Katerina Karagiannaki (1,2)
Athanasia Panousopoulou (1)
Panagiotis Tsakalides (1,2)
(1) - Signal Processing Laboratory (SPL), ICS - FORTH
(2) - Computer Science Department, University of Crete
The dataset is collected from 15 participants wearing 5 Shimmer sensor nodes on the locations listed in Table 1. The participants performed a series of 16 activities (7 basic and 9 postural transitions), listed in Table 2.
The captured signals are the following:
- 3-axis accelerometer
- 3-axis gyroscope
- 3-axis magnetometer
The sampling rate of the devices is set to 51.2 Hz.
The dataset contains the following files:
- partX/partXdev1.csv
- partX/partXdev2.csv
- partX/partXdev3.csv
- partX/partXdev4.csv
- partX/partXdev5.csv
Where X corresponds to the participant ID, and numbers 1-5 to the device IDs indicated in Table 1.
Each .csv file has the following format:
- Column1: Device ID
- Column2: accelerometer x
- Column3: accelerometer y
- Column4: accelerometer z
- Column5: gyroscope x
- Column6: gyroscope y
- Column7: gyroscope z
- Column8: magnetometer x
- Column9: magnetometer y
- Column10: magnetometer z
- Column11: Timestamp
- Column12: Activity Label
- Left Wrist
- Right Wrist
- Torso
- Right Thigh
- Left Ankle
(Arrows (->) indicate transitions between activities)
- stand
- sit
- sit and talk
- walk
- walk and talk
- climb stairs (up/down)
- climb stairs (up/down) and talk
- stand -> sit
- sit -> stand
- stand -> sit and talk
- sit and talk -> stand
- stand -> walk
- walk -> stand
- stand -> climb stairs (up/down), stand -> climb stairs (up/down) and talk
- climb stairs (up/down) -> walk
- climb stairs (up/down) and talk -> walk and talk
Use of this dataset in publications must be acknowledged by referencing the following publications:
- Katerina Karagiannaki, Athanasia Panousopoulou, Panagiotis Tsakalides. A Benchmark Study on Feature Selection for Human Activity Recognition. ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp), ACM, 2016.