Video Analysis and Artificial Intelligence for the Analysis of Upper Limb Movement in Children. Validation of a Technique in a Pediatric Population Aged 6 to 17 Years
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 入组人数
- 150
- 试验地点
- 1
- 主要终点
- Comparison of a video-assisted clinical examination method with commonly used clinical practices
研究概览
简要总结
The principle of the study is to compare the data obtained using a shoulder movement analysis software with those obtained during a traditional clinical examination, that is, using a goniometer and the modified Mallet classification
详细描述
The children are recorded performing 3 sets of shoulder movements (abduction, adduction, flexion, extension, external rotation 1, external rotation 2, internal rotation 2), first on the left and then on the right, at maximum active range of motion, chosen active range of motion, and maximum passive range of motion. The recordings are made by an RGB-D camera connected to a software (ShoulderLoc from B-com) equipped with artificial intelligence that, after image processing, determines the joint range angle of the shoulder for the given movement. This value is compared to the visual estimation of the examiner and its measurement using a goniometer. The hand-mouth, hand-neck, and internal rotation 1 movements are also performed and compared with the data from the modified Mallet classification.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 6 Years 至 17 Years（Child）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Age between 6 and 17 years old at the time of inclusion
- •No neurological pathology
- •No history of upper limb surgery
- •No upper limb trauma above the hand in the 6 months preceding the examination
- •Ability to stand for a minimum of 2 minutes
- •Consent from the child, both parents, and/or legal representatives for participation in a filmed clinical examination.
排除标准
- •Inability to understand the different movements requested.
结局指标
主要结局
Comparison of a video-assisted clinical examination method with commonly used clinical practices
时间窗: 1 day
Perform 2 sets of 7 to 10 shoulder movements, both active and passive, measure mobility angles using a goniometer and the Mallet classification, as well as the ShoulderLoc software and its artificial intelligence program. Compare the averages obtained for each movement using both methods and compare them using an intraclass correlation coefficient (ICC).
次要结局
- Compare measurements obtained in active and passive motion for the same movement, through video measurement and manual (goniometer) measurement, to simple visual estimation measurements.(1 day)
- Measurement of optimal acquisition distances for video quality,(1 day)
- Exam duration based on age(1 day)
- Technical difficulties.(1 day)
- Obtain objective, quantified data on pure and combined shoulder movements(1 day)
- Study the satisfaction of the contribution of video tools in daily clinical practice(1 day)