karayan / FORTH_TRACE_DATASET

FORTH-TRACE Dataset version 1.0

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

EXPERIMENTAL SETUP

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.

DATASET FILES

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

Table 1: LOCATIONS

1. Left Wrist
2. Right Wrist
3. Torso
4. Right Thigh
5. Left Ankle

Table 2: ACTIVITY LABELS

(Arrows (->) indicate transitions between activities)

1. stand
2. sit
3. sit and talk
4. walk
5. walk and talk
6. climb stairs (up/down)
7. climb stairs (up/down) and talk
8. stand -> sit
9. sit -> stand
10. stand -> sit and talk
11. sit and talk -> stand
12. stand -> walk
13. walk -> stand
14. stand -> climb stairs (up/down), stand -> climb stairs (up/down) and talk
15. climb stairs (up/down) -> walk
16. climb stairs (up/down) and talk -> walk and talk

License:

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.