ArticleMed-X2025
Intelligent sensing devices and systems for personalized mental health.
Article in Med-X, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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
7 citing papers in PubMed.
- Real-time facial micromotion tracking enabled by an ultrathin silk fibroin patch.Microsystems & nanoengineering · 2026Article
- From Biosignals to Bedside: A Review of Real-Time Edge Machine Learning for Wearable Health Monitoring.Bioengineering (Basel, Switzerland) · 2026Review
- Organoid Brain-Machine-Interface Devices for Central Nervous System Repair.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Convergent Sensing: Integrating Biometric and Environmental Monitoring in Next-Generation Wearables.Biosensors · 2026Review
- Perceptions, needs, and experiences of kinesiophobia management after total knee arthroplasty: a qualitative study from the perspectives of patients, caregivers, and healthcare providers.Frontiers in public health · 2026Article
- Emotion recognition based on the temporal patterns of electroencephalogram signals and electrodermal response signals using the TRANSFORMER network.Frontiers in neuroscience · 2026Article
- POC Sensor Systems and Artificial Intelligence-Where We Are Now and Where We Are Going?Biosensors · 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
Abstract
Mental disorders disturb the cognition, emotion, and behavior of a diverse patient population, and can reduce their quality of life and even cause death. Despite significant advances in the diagnosis and treatment of mental disorders, challenges remain in achieving objective understanding, accurate assessment, and timely intervention for personalized conditions. Here, we review the recent development of intelligent sensing devices and systems for advancing the diagnosing, monitoring, and managing of mental disorders, with a special emphasis on personalized mental healthcare. We first introduce the mechanisms and clinical symptoms of mental disorders and related diagnostic principles. Then, we discuss the working principle and application of wearable sensors and systems to track various physiological parameters and markers for long-term monitoring, early screening, and treatment evaluation. Furthermore, we highlight recent emerging advancements in Artificial Intelligence (AI) and digital health and give perspectives on their integration with sensing technologies to address the emergent challenges of personalized mental healthcare. We believe innovative intelligent sensing technologies may significantly improve the patient's quality of life, enhance the efficiency and robustness of current healthcare systems, and reduce the socioeconomic burden for mental disorders and other diseases.
Indexed as
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What Socratic 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 Socratic graph.