2016
DOI: 10.1016/j.beproc.2016.09.010
|View full text |Cite
|
Sign up to set email alerts
|

Coding and quantification of a facial expression for pain in lambs

Abstract: Facial expressions are routinely used to assess pain in humans, particularly those who are non-verbal. Recently, there has been an interest in developing coding systems for facial grimacing in non-human animals, such as rodents, rabbits, horses and sheep. The aims of this preliminary study were to: 1. Qualitatively identify facial feature changes in lambs experiencing pain as a result of tail-docking and compile these changes to create a Lamb Grimace Scale (LGS); 2. Determine whether human observers can use th… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

2
95
0
2

Year Published

2016
2016
2024
2024

Publication Types

Select...
6
2
1

Relationship

0
9

Authors

Journals

citations
Cited by 88 publications
(106 citation statements)
references
References 26 publications
2
95
0
2
Order By: Relevance
“…In comparison to the SGS the SPFES comprises more facial expression areas but matches orbital tightening and ear position, which are despite species-specific differences, common parameters for grimace scaling [27]. In line with the recently published Lamb Grimace Scale (LGS) as an indicator for pain in on-farm lambs after tail docking [14] SPFES and SGS are valid and reliable methods for the detection of pain in sheep. However, it is still unclear whether facial expressions change due to other dimensions of severity like stress or suffering, which are likewise related to pain.…”
Section: Discussionmentioning
confidence: 96%
See 1 more Smart Citation
“…In comparison to the SGS the SPFES comprises more facial expression areas but matches orbital tightening and ear position, which are despite species-specific differences, common parameters for grimace scaling [27]. In line with the recently published Lamb Grimace Scale (LGS) as an indicator for pain in on-farm lambs after tail docking [14] SPFES and SGS are valid and reliable methods for the detection of pain in sheep. However, it is still unclear whether facial expressions change due to other dimensions of severity like stress or suffering, which are likewise related to pain.…”
Section: Discussionmentioning
confidence: 96%
“…Langford et al were the first who developed a behavioural coding system based on facial expressions to detect signs of pain in laboratory mice, the Mouse Grimace Scale (MGS) [8]. Following to this, grimace scales for laboratory rats [9] and laboratory rabbits [10] were developed, for domestic cats [11] as well as for farm animals like horses [12], sheep [13] and lambs [14]. Moreover, facial expressions as an indicator for pain are generally applied to assess pain or other emotional states in humans [15].…”
Section: Introductionmentioning
confidence: 99%
“…While additional work is needed on a larger scale to further validate the PGS and confirm the lack of treatment effects, there have been grimace scales developed using less animals. The Lamb Grimace Scale was developed with 16 animals, although the authors do acknowledge that the results should be interpreted with caution due to these low numbers (6). Another study limitation is not having a strong behavioral baseline to compare to post-procedure behaviors.…”
Section: Discussionmentioning
confidence: 99%
“…In an eye-tracking study of pain behavior in rabbits, it was found that observers focused on the rabbits’ facial features rather than other body areas (irrespective of the observer’s experience) (191). A facial grimace scale was first created for laboratory mice (192), and others have since been created for rats (193), rabbits (194), horses (195), and sheep (196, 197). A Piglet Grimace Scale (PGS) has been developed by experienced observers, who identified several facial action units (FAUs) from images of piglets pre- and post-tail docking and castration (198).…”
Section: Potential Future Approaches To Pig Pain Assessmentmentioning
confidence: 99%