This study focuses on developing an intelligent vest to improve posture by integrating Marginal Absolute Relative Gradient (MARG) sensors. The vest, designed with lightweight and flexible materials, provides real-time visual and tactile feedback to enhance posture while ensuring comfort. Utilizing compact Arduino technology from Flora Adafruit, the vest tracks roll and pitch angles at the neck and shoulders. Experimental data showed that when the neck was tilted forward, the average pitch angle was-61.80°, while a rightward lean of the body resulted in a neck pitch angle of-60.34° and a right shoulder roll angle of 13.54°. The correlation matrix revealed a negative correlation of-0.29 between the neck and shoulder roll towards the right and a positive correlation of 0.46 between their pitch movements. The neck and shoulder exhibited synchronized movement, simultaneously flexing forward and tilting right. When the body tilted left, the neck had a pitch angle of-57.48° and the left shoulder a roll angle of-18.24°. A weak correlation coefficient of 0.07 was found for roll movements between the neck and shoulder and-0.18 for pitch, indicating independent movement patterns. User feedback rated LED feedback highly (mean = 4.3), while haptic feedback received low rates (mean = 3.6). Comfort (mean = 4.40) and posture correction (mean = 4.30) were also positively received. The results suggest that the vest effectively provides detailed feedback and continuous monitoring, highlighting its potential in health-related intelligent Garments for posture correction.