In any tracking system, there are three sources of noise that potentially affect the values of dependent variables such as Distance moved or Velocity:
▪System noise. The noisy output of tracking systems means that when you track an object that does not move, the position of the object irregularly oscillates between two or more locations. This way the track may show continuous movement of the object that corresponds to a real-world distance of, for example, 1 cm, while in fact the animal is sitting still. As a result, the data show that the immobile object traveled quite a distance.
▪Outliers resulting from tracking noise. Occasionally the tracking system generates a single outlier which obviously affects a dependent variable such as Velocity.
▪Small movements of the animal ('body wobble'). When you track a moving animal using a high sample rate, sideways movements from the wobbling of the animal's body are also tracked. This results in an overestimation of, for instance, the total distance moved.
Smoothing methods
Smoothing (Lowess)
Use this method to eliminate small movements, such as body wobbling during locomotion, that might affect dependent variables such as total distance moved. See The Lowess smoothing method
Minimal Distance Moved
Use Minimal Distance Moved when the animal sits still, yet the body points move slightly due to system noise or breathing. See The Minimal Distance Moved smoothing method
Maximal Distance Moved
Use Maximal distance moved to remove outliers due to erratic detection, for example in a water maze test when some water reflection is detected as the subject, or in DanioVision experiments when the subject does not move and EthoVision XT detects the margins of the well as the subject. See The Maximum Distance Moved smoothing method
Track smoothing during acquisition
The track smoothing methods listed above affect the tracks after acquisition. In some cases you may already want to smooth the track during acquisition. This may especially be the case if you use Trial and Hardware Control. As an example, if the center-point of an animal is detected in a zone, you want the pellet dispenser to drop a pellet. If the detected center-point is moving rapidly because of noise, this may result in a number of consecutive pellets to be dropped, every time the center-point crosses the border of the zone. Track smoothing does not solve this problem. Instead, use Track noise reduction in the detection settings to smooth the tracks during data acquisition.