Cross-Species Insights: Drawing Lessons Between Bird Lameness Detection and Human Gait Anomaly Detection

Gait, or the unique way every human walks is widely recognised as an important indicator of overall health and predictor of fall risks. Recently, machine learning based classifiers have been acknowledged and adopted to monitor personal safety specially to detect or predict falls as health and safety anomalies among the older population. It is well known that other animals and birds, including chickens can also suffer from health problems that frequently manifest themselves as gait disorders, one of which is known as lameness. Comparing broiler lameness detection with human fall prediction and detection is meaningful for many reasons, one possible argument being that there are very few bipedal animal models, of which poultry is one. In our multidisciplinary collaborative search for a possible AI-based solution to detecting early lameness among broiler chickens, we discovered formidable challenges in applying anomaly detection techniques. However, prior to this work we had already gained valuable experience in gait anomaly detection for humans. This extension of our experience from humans to broilers has revealed new challenges in anomaly detection that are also relevant to human gait analysis, particularly in monitoring gait to enhance fall prediction and detection through assistive technologies.