Wireless ECG Transmission — Biomedical Instrumentation & Clinical Sensing

Abstract — Wireless ECG Transmission

Creative Commons Attribution (CC BY) license . This paper presents the design, simulation, and experimental validation of a distributed wireless electrocardiographic (ECG) acquisition architecture based on two electrically independent sensing units and a receiving unit. The two sensing units can be positioned at different locations on the body, where they independently acquire biopotential signals and transmit them wirelessly to a common receiver. The received signals are then differentially processed to reconstruct the ECG signal without requiring a shared ground reference between the acquisition units. The receiving unit could be implemented in future wearable realizations as a portable processing device, such as a smartphone, potentially enabling additional real-time ECG analysis. The aim is to enable signal acquisition and wireless communication without a shared ground reference between devices, thereby improving user mobility and supporting wearable biomedical applications. The MATLAB/Simulink R2024b model was employed to simulate the complete sensing and communication chain, including signal acquisition, transmission, reception, and differential reconstruction. The proposed acquisition architecture was subsequently implemented on a breadboard using discrete components, with isolation amplifiers used to emulate the electrical independence of wireless transmission. In addition, a separate preliminary experiment using independent ADALM2000 platforms was conducted to investigate the feasibility of signal transmission through a short-range wireless link. Simulation results showed that conventional amplitude modulation (AM) and double-sideband suppressed-carrier (DSB-SC) transmission achieved SNRs of 20.5 dB and 28.9 dB, and RMSEs of 2.12 × 10 − 4 and 8.01 × 10 − 5 , respectively, with the DSB-SC performance obtained assuming perfectly synchronized carriers at the transmitter and receiver. Experimental validation of the proposed acquisition architecture using real ECG recordings demonstrated reliable ECG reconstruction, yielding SNR values of up to 19.7 dB together with accurate heart-rate (HR) estimation. A separate preliminary experiment using two independent ADALM2000 platforms further demonstrated the feasibility of ECG signal transmission and reconstruction through a short-range wireless link, achieving a reconstruction SNR of up to 13.5 dB.

Sensor Interfacing & Analog Front-End Conditioning

Keywords: electrocardiogram (ECG), wireless transmission, biomedical signal processing, MATLAB/Simulink simulation, remote health monitoring, hardware prototyping, signal acquisition, telemedicine systems Figure 2: Diagnostic Medical Waveform & Bio-Potential Clinical Trace for Wireless Ecg Transmission In recent years, technological advances have significantly impacted healthcare, promoting the development of digital solutions for continuous and remote health monitoring. Among these, wearable devices have assumed a central role in the prevention and management of chronic diseases, enabling long-term physiological data acquisition outside traditional clinical environments . In this context, electrocardiographic (ECG) monitoring is particularly relevant, as it allows non-invasive detection of cardiac rhythm abnormalities in ambulatory settings , supporting both early diagnosis and follow-up of cardiac patients.

Bio-Signal Waveform Analysis & Simulation Findings

Wireless, non-invasive, and portable cardiac monitoring systems are increasingly being investigated for effectively tracking heart activity. Traditional systems have several limitations, including the need to place electrodes on precise anatomical points [ 3 , 4 ] or the requirement of a right-leg driven circuit , which compromise practicality and user comfort in wearable scenarios. To overcome these constraints, portable and wireless solutions are being extensively investigated [ 6 , 7 , 8 , 9 , 10 ]. Devices such as adhesive patches, smart textiles, and consumer-grade wearables (e.g., smartwatches) have been developed to enhance usability and enable long-term monitoring. Although smart patches incorporating dry electrodes reduce the need for conductive gels , wearable ECG systems may still face challenges related to motion artifacts, skin–electrode impedance variations, and contact instability [ 12 , 13 ]. Furthermore, consumer devices based on optical photoplethysmography (PPG) or single-lead ECG have been reported to exhibit limitations in diagnostic accuracy during exercise or prolonged operation compared with medical-grade systems . Beyond these well-known signal-quality considerations, conventional ECG systems typically rely on a shared electrical reference or common grounding strategy to ensure proper differential measurement and common-mode stabilization. While this approach is effective in traditional configurations based on a single acquisition unit, it imposes architectural constraints that may limit the flexibility of device placement on the body and reduce the modularity of wearable implementations, especially when multiple sensing modules are designed to operate as independent units. In clinical systems such as Holter monitors, this shared reference is typically maintained through wired connections between electrodes and the acquisition unit, requiring cables routed across the body.

Scope & Clinical Applications

• Real-time multi-parameter vital signs telemetry (ECG, Heart Rate, SpO2, Temperature, Respiration)
• Low-noise Analog Front-End (AFE) conditioning with active Driven Right Leg (DRL) 50 Hz cancellation
• Digital signal processing in MATLAB: Pan-Tompkins QRS detection, FIR/IIR notch, and Continuous Wavelet Transforms
• Finite element tissue bio-electromagnetics and orthopedic mechanical simulations in COMSOL & ANSYS
• Complete Arduino firmware .INO sketches, circuit schematics, and university dissertation reports