ArticleScientific reports2023
Multispectral sensor fusion in SmartWatch for in situ continuous monitoring of human skin hydration and body sweat loss.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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
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Who cites it
8 citing papers in PubMed, 18 citations in OpenAlex.
- 3D Localization of Heat Sources Using LiDAR-Thermal Data Fusion and Multisensor Calibration.Sensors (Basel, Switzerland) · 2026Article
- Integrating Artificial Intelligence with Wearable Sensors for Advanced Health Monitoring and Diagnosis.Biosensors · 2026Review
- Development and Phantom Validation of a Small-Form-Factor SWIR Emitter Probe for Hydration-Sensitive Spatial-Ratio Measurements in Gelatin-Intralipid Phantoms.Sensors (Basel, Switzerland) · 2026Article
- Measuring football fever through wearable technology.Scientific reports · 2026Article
- Wearable PPG Multi-Sensor for Skin Humidity, Temperature, and Contact Pressure Measurement in Weak Magnetic Field Environment: First-Step Experiments.Bioengineering (Basel, Switzerland) · 2025Article
- Application-Specific Optimization of Integrated Spectral Sensors.ACS photonics · 2025Article
- AI-Driven Wearable Bioelectronics in Digital Healthcare.Biosensors · 2025Review
- Recent Advancements in Wearable Hydration-Monitoring Technologies: Scoping Review of Sensors, Trends, and Future Directions.JMIR mHealth and uHealth · 2025Article
Corrections and comments
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Authors and funding
11 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Post-pandemic health operations have become a near-term reality, discussions around wearables are on the rise. How do wearable health solutions effectively deploy and use this opportunity to fill the gap between wellness and healthcare? In this paper, we will talk about wearable healthcare diagnosis, with a particular focus on monitoring skin hydration using optical multi-wavelength sensor fusion. Continuous monitoring of human skin hydration is a task of paramount importance for maintaining water loss dynamics for fitness lovers as well as for skin beauty, integrity and the health of the entire body. Preserving the appropriate levels of hydration ensures consistency of weight, positively affects psychological state, and proven to result in a decrease in blood pressure as well as the levels of "bad" cholesterol while slowing down the aging processes. Traditional methods for determining the state of water content in the skin do not allow continuous and non-invasive monitoring, which is required for variety of consumer, clinical and cosmetic applications. We present novel sensing technology and a pipeline for capturing, modeling and analysis of the skin hydration phenomena and associated changes therein. By expanding sensing capabilities built into the SmartWatch sensor and combining them with advanced modeling and Machine Learning (ML) algorithms, we identified several important characteristics of photoplethysmography (PPG) signal and spectral sensitivity corresponding to dynamics of skin water content. In a hardware aspect, we newly propose the expansion of SmartWatch capabilities with InfraRed light sources equipped with wavelengths of 970 nm and 1450 nm. Evaluation of the accuracy and characteristics of PPG sensors has been performed with biomedical optics-based simulation framework using Monte Carlo simulations. We performed rigorous validation of the developed technology using experimental and clinical studies. The developed pipeline serves as a tool in the ongoing studies of the next generation of optical sensing technology.
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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.