Tracking Recovery: An Up-to-Date Overview of Wearable Sensors in Healthcare Monitoring for Post-Stroke Patients—A Review
Year: 2025
Type: article
Abstract: Stroke is a major global health challenge with high morbidity rate, high risk of recurrence, and increasing incidence. Post-stroke healthcare monitoring involves different physiological functions and is dependent on caregivers, with a high need for regular, long-term, point-of-care monitoring. Recently, many wearable sensors including inertial measurement units, mechanical sensors (example barometric sensors, force sensors, strain sensors, et cetera), and electrodes have been developed to achieve reliable healthcare monitoring for post-stroke patients. The sensors are incorporated in different forms to make it more compact and wearable without altering its measuring abilities. These sensors detect different functions including cardiovascular, respiratory, and neural activities, whereas the majority were focused on body movement. By analyzing the innovative wearable technologies and application scenarios, the merits and limitations of the state-of-the-art sensors are summarized in this review. Artificial intelligence (AI) including edge AI and cloud AI, machine learning and deep learning, hardware optimization, and internet-of-things offer new potentials for overcoming the current challenges in reliable long-term monitoring and standardized data processing towards clinical applications.
Source: IEEE Sensors Journal
Authors: Shriya Marahatta, Ahmed Albagdady, Dingchang Zheng, Haipeng Liu
Institution: Coventry University
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
Funder: Coventry University
OpenAlex ID: W4416649759