# Sitting Posture Recognition Systems: Comprehensive Literature Review and Analysis
###### Abstract
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Sr. No.** & **Health Issue** & **Reason** \\ \hline
1 & Poor circulation & Sitting with poor posture for long periods [11] \\
2 & Digestive issues & Slouching compresses your abdominal organs [16] \\
3 & Lower back pain & prolonged awkward postures [17] \\
4 & Neck and shoulder pain & Slouched [12,13] \\
5 & Cardiovascular & Prolonged sitting [18,19] \\
6 & Teeth grinding and jaw pain & Due to leaning forward [20] \\
7 & Diminished lung function & Leaning or hunching over \\
8 & Fatigue & Body out of alignment \\
9 & Reduced Flexibility & Reduced flexibility in the hips, hamstrings, and other \\
10 & Depression & Slumped posture [21] \\
11 & Abnormalities in spine & Poor sitting postures can lead to abnormalities in the \\
12 & Trunk Asymmetry & Prolonged static or cross-legged seated postures [23,24] \\
13 & Musculoskeletal pain, low back pain, and & Asymmetrical sitting postures [25] \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Health issues related to bad posture. By integrating reminders into routines, individuals can endorse better sitting habits and decrease the risk of long-term posture-related diseases. Ergonomic adjustments in the workplace and daily activities can also significantly contribute to posture correction. This includes optimizing workstation setup, using supportive chairs and pillows, and taking frequent breaks to stretch and change positions [29; 30]. Recent advances in IT and sensor technology have enabled the development of real-time supervisory systems that monitor and improve sitting posture. These systems detect poor sitting habits by using pressure sensors embedded in the backrest and seat, helping to encourage a more upright posture. [PERSON] et al. [29] conducted a study indicating a reduction in musculoskeletal risk over 16 months through training individuals in ergonomic posture. Additionally, it has been shown by studies [30] and [31] that ergonomic modifications can reduce pain and symptoms related to musculoskeletal disorders. [PERSON] et al. [32] also found a decrease in posture-related risks within three weeks of using a camera to display the sagittal posture of seated individuals. Several review studies have already been conducted encompassing the topic of posture recognition systems. The review conducted by [33] provides an overview of the application of smart technologies and sensors integrated into offices and other types of chairs for disease prevention. However, it only covers 15 articles published between 2010 and 2020. The study conducted by [34] is similar to our study, suggesting only a few areas for future research, but they do not provide more specific recommendations on methodologies or frameworks for addressing the identified gaps. A most recent review by [27] included 223 research articles but lacked discussion on how recent advancements in deep learning and computer vision contribute to the development of more effective sitting posture recognition systems. This research addresses the gap in synthesizing the vast and fragmented body of research on sitting posture recognition systems, providing a consolidated source of information that highlights the advancements, challenges, and future directions in the field. It provides a comprehensive literature review and analysis of sitting posture recognition systems, encompassing traditional methods and emerging technologies such as machine learning and deep learning algorithms. It also examines various challenges, constraints, and future trends in sitting posture recognition. In short, through an exploration of the available literature, we analyze prevalent practices, including the types of sensors and machine learning algorithms commonly employed, while also identifying potential areas where further research is needed. This research adds value to the subject area by providing a systematic and detailed review of existing sitting posture recognition systems.