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February 23, 20260 citationsOpen Access

Design of a WI-FI-enabled ECG device for telemedicine and ambulatory monitoring in a robotic platform

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ВИВ. ИвановаBulgarian Academy of SciencesABAni BonevaBulgarian Academy of Sciences

Key Result

The Wi-Fi-enabled ECG device using the MAX30003 chipset achieved a 95% detection rate for P, R, and S peaks and 98% accurate QRS complex segmentation, demonstrating high accuracy and suitability for telemedicine and ambulatory monitoring.

Key Points

  • Develop a Wi-Fi-enabled ECG device integrated into a robotic platform for remote heart monitoring.
  • Designing an ECG device for telemedicine and ambulatory use
  • Integrating with robotic platform for patient management
  • Utilizing the MAX30003 chipset for real-time monitoring
  • Including alert systems for abnormal heart rhythms
  • Ensuring compatibility with other diagnostic functions
  • Device allows high-quality ECG signal transmission
  • Facilitates continuous patient monitoring
  • Exhibits capability for detecting abnormal heart rhythms
  • Supports remote medical consultations
  • Aims for future autonomous functionality

Structured PICO

I
Intervention
Wi-Fi-enabled ECG device integrated with a robotic platform using the MAX30003 chipset

The proposed Wi-Fi-enabled ECG device integrated into a robotic platform provides a technical foundation for advancing remote cardiac monitoring and telemedicine.

Main Result

Effect estimate: 95% detection rate for P, R, and S peaks; 98% accurate QRS complex segmentation

Limitations

  • No clinical trial or comparative effectiveness data reported.
  • Performance data based on device validation studies, not patient outcome trials.
  • No information on sample size, population demographics, or clinical endpoints in patients.

Abstract

This article presents a robotic platform integrated with a Wi-Fi-enabled ECG device designed for telemedicine and ambulatory monitoring. The advancement of portable and wearable ECG monitoring systems remains a key focus in the development of health-related technologies. An ECG device is a critical medical tool used to record the electrical activity of the heart over a specified period, playing a vital role in diagnosing heart diseases and monitoring cardiovascular health. Our objective is to develop a new generation of robotic tools that enhance healthcare and patient management. Specifically, we aim to design an innovative Wi-Fi-enabled ECG device for non-invasive heart rhythm monitoring, capable of receiving, storing, visualizing, and transmitting high-quality electrocardiographic signals remotely. This device enables comprehensive ECG analysis and continuous patient monitoring while seamlessly integrating with other diagnostic and therapeutic functions within the robotic platform's operational framework. A key feature of the proposed device is its ability to detect and promptly alert users to abnormal heart rhythms, making it highly effective for telemedicine and ambulatory care. One of its most notable innovations is the incorporation of the MAX30003 chipset, which facilitates real-time ECG monitoring in portable and wearable systems suitable for both remote medical consultations and personal health tracking. Looking ahead, the system is designed to evolve toward autonomous functionality. Unlike other similar devices, innovative solutions related to the construction and connections of the ECG with the Robotic System are presented here. The research team has extensive experience in surgical robotics, and this development builds upon previous work in the field.

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Cite This Study

Иванова et al. (2025) studied Not applicable (engineering design study). Wi-Fi-enabled ECG device based on MAX30003 chipset integrated into a robotic platform was evaluated on Accuracy and reliability of ECG signal acquisition and monitoring performance (95% detection rate for P, R, and S peaks; 98% accurate QRS complex segmentation). The Wi-Fi-enabled ECG device using the MAX30003 chipset achieved a 95% detection rate for P, R, and S peaks and 98% accurate QRS complex segmentation, demonstrating high accuracy and suitability for telemedicine and ambulatory monitoring.

synapsesocial.com/papers/699bee1c1c6c6bad5397fe59https://doi.org/10.5281/zenodo.18713067
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