## 1 Introduction  
Hip Osteoarthritis (HOA) is a chronic hip disease that progressively degenerates the cartilage holding the joint together and eventually leads to its dysfunction [1]. The subsequent pain, experienced commonly, causes lateral trunk bending that overloads other parts of the musculoskeletal system for compensation; thus, treatment is generally required [2]. Total Hip Arthroplasty (THA) is commonly considered as an important option that alleviates pain and restores functionality in most subjects. However, the literature reveals that post-THA improvements do not completely reduce pain nor return the quality of life to that of healthy individuals [3]. This is due to muscle weaknesses responsible for gait adaptations after THA [4] affecting even the non-operated limb. The accepted standard in assessing hip functionality before and after THA is through the Harris Hip Score (HHS), which is a validated clinical tool. It focuses on pain, function, and range of motion. The HHS is conducted in questionnaire form. The main drawback is its subjectivity [5], and this is where our DL model could be helpful as an additional tool. Our DL methodology is an objective tool. Alternatively, an objective measure is through radiograph images that depict hip structure anomalies, but still, it has its static nature and does not capture motion features [6]. A more suitable alternative measurement is based on gait, which is defined as a manner of walking. Gait is meticulously studied in several areas such as security, sports, and biomedical applications [7]. The gait features are known to have discriminating abilities. Its non-invasive utilization provides us with an understanding of the wellbeing of athletes as well as biometric authentication for remote and mobile devices [8; 9]. Prominently, the use of gait analysis, in clinical settings, is extensively investigated, focusing on gait abnormalities due to pathological diseases such as multiple sclerosis, Parkinson's Disease [10], and other neuro-muscular diseases. The analysis of gait is the systematic examination of human walking via the observation of an expert with the help of data acquisition (DAQ) devices to measure kinematics, kinetics, and spatio-temporal parameters (STP) [2]. Kinematic parameters describe motion without reference to the force, while kinetics is the study of force, moments, and acceleration without orientation. In the context of HOA research, vision-based clinical gait analysis (CGA) systems are the most popular. They are focused on relevant kinematic angle detection that can classify HOA gaits and predict severity. [PERSON] et al. [11] devised a case study to characterize hip joint kinematics during gait for mild-to-moderate HOA. It was found that the sagittal and transverse hip angles are significantly different from healthy subjects, and the net hip joint loading is altered in HOA, suggesting a progression of the disease. Consequently, [PERSON] et al. [12] investigated the lower limb's gait kinematics of HOA subjects and found out that the sagittal and transverse angles of the pelvis, as well as the front angle of the hip, are discriminative for HOA subjects. Similarly, extensive studies were conducted on gait-related differences before and after THA. [PERSON] et al. [13] utilized the overall gait waveform cycle to detect relevant kinematic parameters to describe asymmetrical gaits in patients after THA. Frontal and sagittal angles of the knee and the sagittal angle of the hip are found to be the most discriminating kinematic parameters with a reported accuracy of 91%. Subsequently, [PERSON] et al. [14] hypothesized that inter-joint coordination information can be used to characterize healthy, HOA, and post-THA gaits through cyclogram analysis. Knee and ankle angles were found to have discriminating patterns for the different classes. Additionally, [PERSON] et al. [15] developed a model to predict pelvic sagittal angle five years after THA utilizing gait information one year after surgery with 91% accuracy.