Assessment of Facial Asymmetry in people with Bell’s Palsy Using Triangulation photogrammetry based Artificial Intelligence- A Prospective Observational Study.
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 发起方
- 入组人数
- 30
- 试验地点
- 1
- 主要终点
- The data generated based on photogrammetry at various stages of Bell’s palsy prognosis will be used to train artificial intelligence to identify asymmetry and estimate its degree of severity. The photogrammetry data collected from normal subjects will be used as a comparator for training the AI.
研究概览
简要总结
AIM OF THE STUDY:
To Assess Facial Asymmetry in people with Bell’s Palsy Using Triangulation photogrammetry based Artificial Intelligence.
OBJECTIVES OF STUDY:
**1.**To use Triangulation-based photogrammetry techniques for detailed 2D modeling of facial asymmetry in people with Bell’s palsy.
**2.**To Train AI with data of Triangulation-based photogrammetry to capture both static and dynamic asymmetry accurately.
研究设计
- 研究类型
- Observational
入排标准
- 年龄范围
- 18.00 Year(s) 至 90.00 Year(s)（—）
- 性别
- All
入选标准
- •Subjects diagnosed with Bell’s Palsy in acute stages to subacute in the age group 18 and above.
- •Age and gender-matched subjects without facial palsy.
排除标准
- •Subjects with facial asymmetry arising from causes other than Bell’s palsy.
- •Subjects with other neurological conditions
- •Subjects with facial trauma and UMN facial palsy.
- •Subjects with asymmetric loss of dentation.
结局指标
主要结局
The data generated based on photogrammetry at various stages of Bell’s palsy prognosis will be used to train artificial intelligence to identify asymmetry and estimate its degree of severity. The photogrammetry data collected from normal subjects will be used as a comparator for training the AI.
时间窗: The data generated based on photogrammetry at various stages of Bell’s palsy prognosis will be used to train artificial intelligence to identify asymmetry and estimate its degree of severity. The photogrammetry data collected from normal subjects will be used as a comparator for training the AI. The procedure will be carried out twice, on the day of enrolment to the study (0) and after completion of the 4th week.
次要结局
- The data generated based on photogrammetry at various stages of Bell’s palsy prognosis will be used to train artificial intelligence to identify asymmetry & estimate its degree of severity. The photogrammetry data collected from normal subjects will be used as a comparator for training the AI. The procedure will be carried out twice, on the day of enrolment to the study (0) & after completion of the 4th week.(for healthy individuals once)
研究者
Rohan Birajdar
Department of Physiotherapy, Kasturba Medical College, Mangalore,