Innovative Advances in Non-Invasive Detection Technologies for Heart Failure: Synergistic Application of Multimodal Sensing and Intelligent Algorithms

Figures

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  Fig. 1.. Clinical staging and evolution pathway of heart failure (HF). Core Management Goals during Acute Decompensation, Vulnerable, and Chronic Stable Phases.

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  Fig. 2.. Hemodynamic and tissue fluid status monitoring devices for heart failure (HF). (A) The FloPatch®, with an aperture approximately 3–4 times the width of the carotid artery, is affixed to the patient’s neck using a medical adhesive patch. The device wirelessly connects to a tablet application, enabling the acquisition of real-time hemodynamic parameters within 3 minutes. (B) The ReDS™ System utilizes a non-invasive sensing device, which is typically integrated into a wearable vest for measurement. It provides an intuitive numerical readout and trend analysis of the measured data.

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  Fig. 3.. Electrophysiological signal monitoring devices for heart failure (HF). (A) The Zio® XT Patch features a discreet, bandage-sized oval design, which is adhesively secured on the upper left chest. Its waterproof casing enables continuous ambulatory monitoring for up to 14 days. (B) Optical heart sensor of photoplethysmography (PPG) in the Apple Watch, located on the rear case, central to the skin-contact surface, employs light-emitting diodes (LEDs) to project light onto the subcutaneous vasculature. Photodiodes then detect the backscattered light, which is modulated by blood flow pulsations, enabling heart rate calculation. (C) KardiaMobile 6L Max™ device employs a three-point contact method: the user’s hands contact the two electrodes at each end of the device, establishing Leads I, II, and III. The back electrode contacts the left leg or chest (e.g., parasternal area) to form the Wilson’s central terminal, from which the augmented limb leads (aVR, aVL, aVF) are derived algorithmically. (D) “Wenxin Xiaoyi” Smart Patch features a miniaturized design with dimensions of 6 cm × 3 cm × 1 cm and a weight of approximately 13 g. Its ergonomic structure, fabricated from medical-grade…

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  Fig. 4.. Schematic of an intelligent remote monitoring (RM) platform for heart failure (HF) management. The system operates via a continuous cycle: patients utilize wearable devices (e.g., smartwatches, specialized textiles) to collect cardiac data, which is transmitted via mobile networks to a cloud-based AI analytics platform. This platform processes multi-source medical data using machine learning (ML) to generate diagnostic support, issue intelligent alerts, and provide health guidance to clinicians, enabling optimized treatment plan adjustments and forming a closed-loop, patient-centric management ecosystem.

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  Fig. 5.. Workflow for constructing an intelligent heart failure (HF) detection platform. The process begins with feature representation from multi-source medical data, including electrophysiological, hemodynamic, and fluid status parameters. Following data preprocessing (noise filtering, fusion alignment, and feature extraction), a general diagnostic model is built and refined through quality assessment with human reinforcement. Integration of patient-specific data then enables personalized model development, supporting clinical applications in auxiliary diagnosis, early warning, and tailored health guidance.