Related Experiment Video
Updated: Sep 13, 2025
04:24
A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program
Published on: April 19, 2019
11.7K
AI-Driven Wearable Bioelectronics in Digital Healthcare
Guangqi Huang1,2, Xiaofeng Chen3, Caizhi Liao1,2
1Department of Bioelectronics, Faculty of Biomedical Engineering, Shenzhen University of Advanced Technology, Shenzhen 518055, China.
Biosensors
|July 25, 2025
Summary
Artificial intelligence (AI) integrated with wearable bioelectronics offers proactive, personalized digital healthcare solutions. These AI-driven wearables enable early disease detection and management, shifting healthcare towards prevention despite existing challenges.
Area of Science:
- Digital Health
- Bioelectronics
- Artificial Intelligence
Background:
- Wearable bioelectronics with AI analytics enable real-time monitoring of physiological and biochemical parameters.
- These technologies facilitate early disease detection, chronic condition management, and precision therapeutics.
- AI-driven wearables address challenges like chronic disease burden, aging populations, and healthcare accessibility.
Purpose of the Study:
- To review the current state of AI-enhanced wearable bioelectronics.
- To cover foundational technologies, applications, challenges, and future directions.
- To guide stakeholders toward responsible innovation in digital healthcare.
Main Methods:
- Comprehensive review of AI-enhanced wearable bioelectronics.
- Examination of sensor design, AI algorithms, and hardware.
- Analysis of applications, challenges (scalability, security, regulation), and future trends (5G, IoT).
Main Results:
- AI-powered wearables are revolutionizing healthcare with personalized, data-driven solutions.
- These devices enable continuous monitoring for early detection and management of diseases.
- Key challenges include data interoperability, privacy, algorithmic bias, and regulatory hurdles.
Conclusions:
- AI-enhanced wearable bioelectronics promise to democratize healthcare via remote monitoring and resource optimization.
- Interdisciplinary collaboration is crucial for equitable, secure, and clinically impactful deployment.
- Addressing technical, ethical, and regulatory challenges is imperative for widespread adoption.
