Dataset Name: MEx Multi-modal Exercise dataset

Description: The MEx Multi-modal Exercise dataset contains data of 7 different physiotherapy exercises, performed by 30 subjects recorded with 2 accelerometers, a pressure mat, and a depth camera.

Application: The dataset can be used for exercise recognition, exercise quality assessment, and exercise counting, by developing algorithms for pre-processing, feature extraction, multi-modal sensor fusion, segmentation, and classification.

Data Collection Method: Each subject was given a sheet of 7 exercises with instructions to perform the exercise at the beginning of the session. At the beginning of each exercise, the researcher demonstrated the exercise to the subject, then the subject performed the exercise for a maximum of 60 seconds while being recorded with four sensors. During the recording, the researcher did not give any advice or keep count or time to enforce a rhythm.

Sensors:

1. Obbrec Astra Depth Camera

   • Sampling frequency: 15Hz
   • Frame size: 240x320

2. Sensing Tex Pressure Mat

   • Sampling frequency: 15Hz
   • Frame size: 32x16

3. Axivity AX3 3-Axis Logging Accelerometer

   • Sampling frequency: 100Hz
   • Range: 8g

Sensor Placement: All exercises were performed lying down on the mat while the subject wore two accelerometers on the wrist and the thigh. The depth camera was placed above the subject facing downwards, recording an aerial view. The top of the depth camera frame was aligned with the top of the pressure mat frame and the subject’s shoulders, ensuring the face would not be included in the depth camera video.

Data Folder: The MEx folder contains four folders, one for each sensor. Inside each sensor folder, 30 folders can be found, one for each subject. In each subject folder, 8 files can be found for each exercise with 2 files for exercise 4 as it is performed on two sides. (Subject 22 will only have 7 files as they performed exercise 4 on only one side.) Each line in the data files corresponds to one timestamped sensory data.

Attribute Information:

• Accelerometer (act and acw files):

  1. Timestamp
  2. X value
  3. Y value
  4. Z value
  • Min value: -8
  • Max value: +8

• Pressure Mat (pm file):

  1. Timestamp 2-513: Pressure mat data frame (32x16)
  • Min value: 0
  • Max value: 1

• Depth Camera (dc file):

  1. Timestamp 2-193: Depth camera data frame (12x16)
  • Depth camera data frame is scaled down from 240x320 to 12x16 using the OpenCV resize algorithm
  • Min value: 0
  • Max value: 1