Highly Stretchable Wireless Electromyography Sensor And Circuit

Abstract

Soft, stretchable sensors and circuits that allow for greater comfort and ease of use continue to be developed. Difficulties include conforming to the skin, and any mechanical mismatch between flexible/stretchable materials and hard electronic components. Here, we designed, fabricated, and characterized a sensor and circuit with stiffness and stretchability comparable to human skin. For the sensor we used a molded hydrogel. The Young’s modulus was comparable to human skin, and its stretchability greater than skin. The sensor conformed to the skin, giving both a very small motion artifact, and a signal-to-noise ratio (SNR) that was comparable to ‘gold standard’ medical-grade Ag/AgCl wet gel electrodes. We used the SPICE-based analog circuit simulator LTSpice vXVII to simulate an OpA333 low-pass Sallen-Key filter and an AD627 instrumental amplifier. We used COMSOL Multiphysics v6.2 to assess the effects of deformation on straight and 3D coiled interconnects molded inside the circuit’s EcoFlex. We developed a novel, conformal, stretchable wireless bracelet for surface electromyography (EMG). Surface electromyography involves recording muscle activity from the surface of the skin directly above the muscle, through bio-potential voltage. Recording surface electromyography is challenging due to unavoidable cross-signal interference from the movement of muscles during contraction. This often causes movement of the sensor with respect to the skin and motion artifacts in the EMG signal. Our soft and stretchable circuit has a Young’s modulus of 86.5 kPa and a stretchability of 60%, because we integrated 3D interconnects filled with eutectic gallium indium (EGaIn) liquid metal alloy embedded in an ultrasoft EcoFlex. We developed a fabrication process for the sensor and circuit that uses a three-dimensional printer. The process is simple and flexible. This allows cost-effective production of high-performance, user-friendly, comfortable-to-wear wireless and mobile EMG sensor-circuit patches. There is no need to depend on clean rooms and on micro- or nanofabrication facilities. The devices we develop will enable long-term mobile recording during a person’s daily activities. Such devices have the capability to be integrated with artificial intelligence, and to be used for more effective physiotherapy, medical diagnosis, human-machine interface, and muscle electrical stimulation.