ArticleNPJ digital medicine2025
A systematic literature review on integrating AI-powered smart glasses into digital health management for proactive healthcare solutions.
Article in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Advancements in Machine Learning-Assisted Flexible Electronics: Technologies, Applications, and Future Prospects.Biosensors · 2026Pooled it
- Machine Learning for the Interpretation of Serum Protein and Immunofixation Electrophoresis in Multiple Myeloma: A Scoping Review.Diagnostics (Basel, Switzerland) · 2026Review
- Smart Glasses for Older Adults With Cognitive Impairment: Explanatory Mixed Methods Study.JMIR aging · 2026Article
- Digital health interventions for perioperative patient-reported outcomes: a network meta-analysis.NPJ digital medicine · 2026Article
- The Impact of Intelligent Medical Systems Combined with Interdisciplinary Care Teams in Home-Based Care Services for Disabled Elderly Individuals: A Prospective Intervention Study.Journal of multidisciplinary healthcare · 2026Article
- Risk Management of Large Language Model-Based Exercise and Health Guidance: A China-Anchored, Comparatively Informed Six-Dimensional Trigger Matrix and Lifecycle Governance Framework for the Wellness-to-SaMD Continuum.Risk management and healthcare policy · 2026Review
- Nurses as guardians of time: the hidden clinical value of continuous care in geriatrics.Frontiers in public health · 2026Review
- Do we need AI guardians to protect us from health information overload?NPJ digital medicine · 2025Article
- Augmented Reality in Implant and Tooth-Supported Prosthodontics Practice and Education: A Scoping Review.Dentistry journal · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
AI-powered smart glasses are emerging as a highly promising advancement in the field of digital health management, owing to their capabilities in real-time monitoring, chronic disease management, and personalized treatment planning. To comprehensively understand the current state of development, we systematically searched multiple databases, including Web of Science, PubMed, and IEEE Xplore, to collect relevant literature. This paper provides a systematic analysis of the current applications of smart glasses in healthcare, focusing on their potential benefits and limitations. Key issues discussed include user engagement, treatment adherence, data privacy, standardization, battery efficiency, clinical validation, and medical ethics. Our findings suggest that, supported by emerging clinical evidence, smart glasses have demonstrated significant improvements in areas such as assisted medical services, health management, anxiety alleviation in children, and telemedicine. By integrating multi-modal sensors, these devices are capable of accurately tracking certain physiological indicators and synchronizing real-time visual input, thereby enhancing the accuracy and timeliness of health interventions and medical services. Notably, some cutting-edge smart glasses have adopted advanced artificial intelligence algorithms, particularly large language models (LLMs) with context awareness and human-like interaction capabilities. These AI-powered glasses can offer real-time, personalized dietary and health management recommendations tailored to users' daily life scenarios. Building on these findings, this study further proposes a conceptual framework for proactive health management using smart glasses and explores future directions in technological development and practical applications. Overall, AI-enhanced smart glasses show great potential as a critical interface between healthcare providers and patients, poised to play a vital role in the future of personalized medicine and continuous health management.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.