Wearable technologies have revolutionized muscle activity monitoring, offering significant advances in fields such as prosthetics, rehabilitation, and human-computer interaction. While Electromyography (EMG) has been a staple in capturing muscle signals, it comes with limitations like precise electrode placement, noise susceptibility, and user discomfort. Force Myography (FMG) emerges as a promising alternative, using pressure variations on the skin to detect muscle movements. This study introduces a novel flexible tactile sensor array, integrated into an armband for FMG applications, aimed at improving muscle signal monitoring. The sensor array was fabricated using piezoresistive materials, specifically Velostat, which offers flexibility and durability. Eight customized sensors were arranged in an armband structure, capturing forearm muscle movements and translating them into electrical signals. The developed FMG armband was tested for hand gesture recognition in five healthy participants, achieving an average classification accuracy of 96.34% ± 2.5% using the Random Forest classifier. This work demonstrates the potential of flexible FMG-based wearable devices, providing an accurate, cost-effective, and user-friendly alternative to traditional methods. It paves the way for applications in neurorehabilitation and human-computer interaction.