| Autor: |
Juan Haladjian, Johannes Haug, Stefan Nüske, Bernd Bruegge |
| Jazyk: |
angličtina |
| Rok vydání: |
2018 |
| Předmět: |
|
| Zdroj: |
Multimodal Technologies and Interaction, Vol 2, Iss 2, p 27 (2018) |
| Druh dokumentu: |
article |
| ISSN: |
2414-4088 |
| DOI: |
10.3390/mti2020027 |
| Popis: |
Cow lameness is a common manifestation in dairy cattle that causes severe health and life quality issues to cows, including pain and a reduction in their life expectancy. In our previous work, we introduced an algorithmic approach to automatically detect anomalies in the walking pattern of cows using a wearable motion sensor. In this article, we provide further insights into a system for automatic lameness detection, including the decisions we made when designing the system, the requirements that drove these decisions and provide further insight into the algorithmic approach. Results from a controlled experiment we conducted indicate that our approach can detect deviations in cows’ gait with an accuracy of 91.1%. The information provided by our system can be useful to spot lameness-related diseases automatically and alarm veterinarians. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
