A Computer Vision-Based Application for the Assessment of Head Posture: A Validation and Reliability Study  
[PERSON], [PERSON].  
1 Department of Physotherapy, Faculty of Medicine and Health Sciences, Universitat Internacional de Catalunya (ULC), C/[PERSON] s/n, Sant Cugat del Valles, 08195 Barcelona, Spain 1  
[PERSON]  
2 Bioengineering Institute of Technology, University of Central  
can influence biomechanics by producing an alteration between the head and the cervical spine [9; 10], causing an increase in tension in the cervical spine muscles. This misalignment would occur because the upper cervical spine is practically in a fully extended position, unlike the lower cervical segments, which are in flexion.  
Neck pain is a frequent reason for consultation; between 22 and 70% of the world's population will experience neck pain at least once during their lives [11]. As mentioned before, neck pain can be related to FHP, which is one of the most common disorders of the cervical spine [12]. Furthermore, subjects with tension-type headache could also present a greater FHP associated with impaired cervical ROM compared with healthy subjects [13]. It has been observed that poor alignment in FHP may be associated with increased use of electronic devices and long periods of sitting in both children and adults [14].  
During clinical examination in patients with neck pain, evaluation of FHP is commonly performed. [15]. The quantification of the cranivertebral angle (CVA) has been the most widely used measurement method to quantify the severity of FHP, being the most appropriate measurement for this task [12; 16; 17]. The CVA has been defined based on two references: the tragus of the ear and the spinous process of C7. The angle is formed by a horizontal line passing through C7 and the line joining the tragus and C7 [18]. An angle less than 50-53\({}^{\circ}\) has been described as the FHP cut-off value [2; 18; 20; 21].  
Photometry is considered the \"gold standard\" to assess the position of the head [21; 22], and its assessment has been shown to be valid and reliable to assess the FHP [15]. To assess the CVA, a photo is taken from the sagittal plane, either standing or sitting, and through postural evaluation software and subsequent analysis, the CVA is estimated [18]. To measure CVA, several tools have been used, such as computer programs (appointments) and mobile applications [23].  
Current technological advances such as computer vision (CV) and artificial intelligence allow us to analyze images and acquire information from them [24]. This fact and the COVID-19 pandemic have made telerehabilitation models grow; that is, rehabilitation services have grown through information and communication technologies [25]. For CV to be integrated into clinical rehabilitation in a real way, the evaluation must be valid and reliable [26]. However, according to a recent systematic review about the reliability and validity of non-radiographic methods of FHP measurement, there is a lack of evidence about the reliability and validity of applications to assess CVA [27].  
Based on current knowledge on FHP and CVA assessment and the ability of AI and CV to perform analysis and acquire image information, an application has been created to enable automatic CVA analysis. Therefore, the purpose of our study was: (1) to analyze the test-retest and the inter-rater reliability of the CV application assessing the CVA in healthy controls, in subjects with neck pain, and in subjects with tension-type headache (TTH); and (2) to analyze the concurrent validity of the CV application comparing it with 2D Kinovea software.