# A Low-Cost Electronic System for Human-Body Communication
## 1 Introduction  
Human-body communication (HBC) uses human-body tissues as a transmission medium for health informatics. It is a promising building block for developing new applications, including healthcare monitoring systems [1; 2; 3]. Continuous health monitoring is a public health concern and challenge, given the growth of the aging population and the prevalence of chronic diseases (e.g., heart diseases, diabetes, and strokes). The continuous monitoring of physiological data benefits the early detection and prevention of diseases. For instance, brain and muscle activities need to be continuously monitored in patients with [PERSON]'s disease, and blood glucose is monitored in patients with diabetes. Body area networks (BANs) enable continuous physiological data monitoring by sensors and actuators collecting physiological data and providing therapeutic functions (e.g., insulin injection and control of a cardiac pacemaker) [4; 5]. One can implement HBC by several communication technologies, including radio or acoustic waves, electromagnetic fields, capacitive coupling, and galvanic coupling. In capacitive coupling, the signal is coupled into the human body via the signal electrode of the transmitter and receiver, establishing a return path via the ground electrode through the path outside the human body [6]. In galvanic coupling, the electrodes (signal and current return) from both transmitter and receiver are in direct contact with the body for coupling differential currents [1]. These two latest techniques are parts of the IEEE 802.15.6 standard [7]. They use the conductivity of the living tissues as a medium for ionic currents to propagate and then interconnect devices through modulated signals [8]. Thus, the external environment has almost no impact on the signal because it is confined within the human body. It also operates at a low frequency, compared to other techniques, enabling stable and reliable signal transmission [9]. Hence, galvanic coupling HBC is suitable for the physiological signal transmission, particularly for implantable device communication [10]. Most of the existing works in this research area focus on the important task of characterizing human-body tissue effects in digital communication. The traditional galvanic coupling HBC systems use differential probes and balun transformers for coupling to measurement instruments, usually vector network analyzers (VNAs) [1,11]. However, these devices are not suitable for data analysis [2, 12]. When the applications handle specific data, such as medical or encrypted data [3], VNAs are replaced by data generation and acquisition systems [9, 12, 13, 14, 15]. Reducing the size of this set is a challenge due to the transformers' physical characteristics. The existing platforms are mostly commercial, and their architectures and digital design are not open-source. These devices are also expensive and inflexible for HBC-specific applications, preventing the development of high-layer solutions, such as data security. These constraints delay the evolution of promising solutions to improve performance and efficiency in body sensor networks. In this paper, we present a low-cost electronic system for galvanic coupling for human-body communications using off-the-shelf components. Our system performs signal coupling to and from an ionic medium, providing digital communication through an HBC structure. Moreover, as an electronic device, miniaturization is not only feasible but is also straightforward. Our system is composed of two modules: a differential current driver and a sensing amplifier. The former generates the signal for coupling. The latter is responsible for capturing and amplifying the signal to be digitized by the processing element. We evaluated the new system through the use of (i) a phantom composed of saline (0.9%) and (ii) a human forearm through adhesive surface electrodes, often used for electrocardiogram (ECG) recordings. In both evaluation scenarios, our system reached 11.11 kbps with online decoding.