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Lameness scoring system for dairy cows using force plates and artificial intelligence.

S Mokaram Ghotoorlar¹, S Mehdi Ghamsari, I Nowrouzian

¹Department of Clinical Sciences, Faculty of Veterinary Medicine, University of Tehran, Tehran, Iran. mokaram@ut.ac.ir

The Veterinary Record

|December 6, 2011

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This study introduces an automated lameness scoring system for dairy cows using artificial neural networks and force plates. The system demonstrates high repeatability and accuracy, offering an objective alternative to subjective lameness scoring methods.

Area of Science:

Animal Science
Veterinary Medicine
Biomechanical Engineering

Background:

Lameness scoring is crucial in dairy herds for early detection and management.
Subjective lameness scoring methods suffer from low agreement and limited monitoring capabilities.
Developing objective, automated systems is essential for improving dairy herd health management.

Purpose of the Study:

To develop an automated lameness scoring system using artificial neural networks (ANNs).
To compare the performance of the automated system with conventional subjective lameness scoring.
To assess the repeatability, sensitivity, and specificity of the automated system.

Main Methods:

Utilized four balanced force plates within a hoof-trimming box to collect ground reaction force (GRF) data.

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Extracted 23 features from GRF data for training ANNs on a dataset of 105 dairy cows.

Validated the trained system on 40% of the data and assessed repeatability using GRF samples from 25 cows.

Main Results:

The automated system exhibited high repeatability, with a mean standard deviation of 0.31 and a mean coefficient of variation of 14.55%.
The system demonstrated good sensitivity and specificity across all locomotion score groups (1-5).
Sensitivity and specificity exceeded 72% for groups 1-4, and were 50% sensitive and 100% specific for group 5.

Conclusions:

The developed automated lameness scoring system is a repeatable and objective tool for dairy cows.
This system offers a viable alternative to subjective scoring, enhancing lameness detection and monitoring.
The technology holds promise for improving dairy herd health and welfare through accurate lameness assessment.