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Research trends in equine movement analysis, future opportunities and potential barriers in the digital age: A scoping review from 1978 to 2018.

BACKGROUND
Since Muybridge's 'horse in motion', researchers in the equine movement analysis field continue to improve objective analysis and performance monitoring while ensuring representative data capture. However, subjective evaluation remains the primary method of equine gait analysis in the applied setting, despite evidence highlighting the unreliability of this approach.


OBJECTIVES
To map research trends, limitations and opportunities across the diverse equine gait analysis literature.


STUDY DESIGN
Joanna Briggs Institute and Cochrane systematic scoping review.


METHODS
Search terms were chosen based on the 'PICO' framework and included keywords such as: Equine, Gait, Kinematics and Analysis. Studies were excluded based on predetermined criteria by two independent researchers. Data were extracted from 510 articles from 1978 to 2018.


RESULTS
Insights derived from movement analysis appear to be driven by tool availability. Observational research (42.9%) was the most popular study design. Use of wearable technology as a primary research tool is established within the field, accounting for 13.5% of studies. Analysis of limitations identified 17.8% of studies citing challenges to the transferability of research results. Restricted sample size appears to be an underlying contributor to many of the limitations identified. In terms of research opportunities, advances in intervention studies were called for (10.4% of studies) in the following three areas; clinical, rehabilitative exercise and performance/training.


MAIN LIMITATIONS
This review was confined to research in the English language.


CONCLUSIONS
Standardised research reporting may alleviate sample size issues by facilitating data pooling, database creation and meta-analyses. Large holistic data collections and application frameworks based on wearable technologies are not reflected in the current equine gait analysis literature and thus represent an interesting opportunity for this field. Progress and lessons learned from the human field of movement analysis can be useful in supporting this potential development.