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Gesture Recognition Dataset

Dataset Structure

  • Labels: ['Good', 'Null', 'Thirsty', 'Bad', 'Me', 'Hungry']
  • Format: Each record contains a 'label' and a 'batch' field
  • Batch Size: 30 rows per batch (30 time steps)
  • Features: 15 columns per row
  • Selection Method: cosine_similarity - Files selected based on similarity to majority pattern

Column Information

Each row in a batch contains 15 values in this order:

  1. Timestamp - Timestamp
  2. F1 - Flex sensor 1
  3. F2 - Flex sensor 2
  4. F3 - Flex sensor 3
  5. F4 - Flex sensor 4
  6. F5 - Flex sensor 5
  7. Acc_Fin_x - Accelerometer Fin x axis
  8. Acc_Fin_y - Accelerometer Fin y axis
  9. Acc_Fin_z - Accelerometer Fin z axis
  10. Acc_Palm_x - Accelerometer Palm x axis
  11. Acc_Palm_y - Accelerometer Palm y axis
  12. Acc_Palm_z - Accelerometer Palm z axis
  13. Acc_Arm_x - Accelerometer Arm x axis
  14. Acc_Arm_y - Accelerometer Arm y axis
  15. Acc_Arm_z - Accelerometer Arm z axis

Data Format

{
    'label': 'gesture_name',  # One of: ['Good', 'Null', 'Thirsty', 'Bad', 'Me', 'Hungry']
    'batch': [
        [Timestamp,F1, F2, F3, F4, F5, Acc_Fin_x, Acc_Fin_y, Acc_Fin_z, Acc_Palm_x, Acc_Palm_y, Acc_Palm_z, Acc_Arm_x, Acc_Arm_y, Acc_Arm_z],  # Row 1
        [Timestamp,F1, F2, F3, F4, F5, Acc_Fin_x, Acc_Fin_y, Acc_Fin_z, Acc_Palm_x, Acc_Palm_y, Acc_Palm_z, Acc_Arm_x, Acc_Arm_y, Acc_Arm_z],  # Row 2
        ...  # 30 rows total
    ]
}

Sensors

  • F1-F5: Flex sensors measuring finger bend (5 sensors)
  • Acc_Fin: Accelerometer on finger (x, y, z axes)
  • Acc_Palm: Accelerometer on palm (x, y, z axes)
  • Acc_Arm: Accelerometer on arm (x, y, z axes)

Data Quality

Files were selected using cosine_similarity to ensure the most representative samples for each gesture class.

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