Durability and Signal Quality Assessment of Rivet and Snap Connections for Wearable EMG Armband

Wearable textile electromyography (EMG) armbands hold immense potential for applications in healthcare, fitness, and assistive technologies. However, their wide adoption is hindered by challenges related to durability and signal quality. These concerns arise from washing and wearing the armband which can degrade the electrical connections. Snap fasteners are commonly used connections in e-textiles but pose significant challenges due to their limitations in maintaining consistent electrical and mechanical performance compromising the signal quality. The rigidity of the snap fasteners create mismatch with the stretchy textile causing misalignment, therefore, amplifying motion artifacts. This necessitates the need for a low form factor and durable interconnect for wearable EMG armbands. This work presents a novel approach to fabricating a wearable EMG armband using rivets and comparing it to the commonly used snaps. Both armbands were subjected to three washes and the EMG signal was recorded before and after each wash test in stationary (sitting) and dynamic (walking) conditions. The rivets showed a lower and gradual increase in resistance as compared to the snaps before and after every wash. After the third wash, the snaps became unstable whereas the rivet armband monitored EMG in both stationary as well as dynamic conditions highlighting the durability of rivets. Rivets also exhibited higher signal to noise ratio (SNR) in both stationary as well as dynamic conditions indicating higher signal quality as compared to snaps. This work addresses one of the critical challenges in wearable devices, which is reliable and durable interconnects, by demonstrating superior durability and signal quality of rivet connections in wearable EMG armbands.Clinical Relevance- A durable wearable EMG armband can offer practicing clinicians a reliable tool for continuous muscle activity monitoring. Its washable and comfortable design can enable patient compliance by making it ideal for rehabilitation, prosthetic control, and managing neuromuscular disorders not only in a static state but also in dynamic motion. By providing real-time, actionable data in both clinical and remote settings, it can enhance diagnostics, therapy personalization, and long-term care outcomes.