(Please note that this dataset is currently only available in individual csv files for each subject as we are having difficulties uploading zipped folders. We have reached out to IEEEDataport to help us resolve this issue)

This dataset consists of 20 csv files, one for each of the subjects in the dataset (e.g. "spars9x_s0.csv" corresponds to the first subject of the dataset). These are contained in the zip file spars9xcsv.zip.

We have also provided the dataset in a numpy array format (spars9xnpy.zip), consisting of a single array and 20 subarrays, one for each dataset subject. These may be loaded into memory using the load() function of the python library numpy.

Either file needs to be decompressed (unzipped) before use.

Data Labels:

0: Unlabeled Activities of Daily Living (Non-Exercise)

1: External Rotation (Isometric)

2: External Rotation in 90 Degrees Abduction in Scapula Plane

3: Internal Rotation (Isometric)

4: Extension (Isometric)

5: Abduction (Isometric)

6: Biceps Muscle Strengthening

7: Cross Chest Adduction

8: Active Flexion

9: Shoulder Girdle Stabilization with Elevation

10: Triceps Pull Downs

Data Format:

Inertial data and heart rate have been interpolated to 50 Hz (inertial sensor acquisition was approximately 50 Hz, but sensors recorded asynchronously and so interpolation was needed).

Each record consists of an Nx12 array, where numbered columns correspond to:

0-2: Accelerometer (X/Y/Z) in m/s^2

3-5: Magnetometer (X/Y/Z) in μT's

6-8: Gyroscope (X/Y/Z) in rad/s

9: Heart Rate in bpm

10: Shoulder (0 = Unlabeled, 1 = Left Shoulder, 2 = Right Shoulder)

11: Activity Label (0-10 as described above)

Note: All exercise data has left or right shoulder indicated, whereas other activity data does not. Other activity data may be assigned to left or right shoulder for analysis, or split between each as required.

Citation Request:

If using this data in academic publication, please cite the following manuscript:

Boyer, P.; Burns, D.; Whyne, C. Out-of-Distribution Detection of Human Activity Recognition with Smartwatch Inertial Sensors. Sensors 2021, 21, x. https://doi.org/10.3390/xxxxx