Fully integrated microneedle biosensor array for wearable multiplexed fitness biomarkers monitoring

Fitness monitoring has become increasingly important in modern lifestyles; the current fitness monitoring always relies on physical sensors, making it challenging to detect pertinent issues at a deeper level when exercising. Here, we report a fully integrated wearable microneedle sensor that simultaneously measures fitness related biomarkers (e.g., glucose, lactate, and alcohol) during physical exercise. Such a sensor integrates a biocompatible 3D-printed microneedle array that can comfortably access skin interstitial fluid and a small circuit for signal processing and calibration, and wireless communication. The microneedle array features good biocompatibility and highly sensitive biochemical sensors that can detect even the slightest variations within the biomarkers of this fluid. On-body experimental results indicate that such a sensor can monitor fitness-related biomarkers across multiple subjects and support multi-day monitoring, with results showing a good correlation with commercial devices. The data was transmitted to a smartphone via Bluetooth and uploaded to cloud platforms for further health assessment. This study has the potential to boost intelligent wearable devices in sports health.

Authors

Institutions

Publication Details

Journal
Biosensors and Bioelectronics
Published
2024-08-23
DOI
https://doi.org/10.1016/j.bios.2024.116697
Citations
43
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
7.93

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Fully integrated microneedle biosensor array for wearable multiplexed fitness biomarkers monitoring

Qiyu Wang, Tailin Xu, Geng Zhong, Hanlin Li et al.
43 citations
Biosensors and Bioelectronics
Advanced Sensor and Energy Harvesting Materials
7.93
article

Fully integrated microneedle biosensor array for wearable multiplexed fitness biomarkers monitoring

Qiyu Wang, Tailin Xu, Geng Zhong, Hanlin Li, Qingzhou Liu, H Z Qiu
article en
43 citations

Abstract

Fitness monitoring has become increasingly important in modern lifestyles; the current fitness monitoring always relies on physical sensors, making it challenging to detect pertinent issues at a deeper level when exercising. Here, we report a fully integrated wearable microneedle sensor that simultaneously measures fitness related biomarkers (e.g., glucose, lactate, and alcohol) during physical exercise. Such a sensor integrates a biocompatible 3D-printed microneedle array that can comfortably access skin interstitial fluid and a small circuit for signal processing and calibration, and wireless communication. The microneedle array features good biocompatibility and highly sensitive biochemical sensors that can detect even the slightest variations within the biomarkers of this fluid. On-body experimental results indicate that such a sensor can monitor fitness-related biomarkers across multiple subjects and support multi-day monitoring, with results showing a good correlation with commercial devices. The data was transmitted to a smartphone via Bluetooth and uploaded to cloud platforms for further health assessment. This study has the potential to boost intelligent wearable devices in sports health.

Biosensors and BioelectronicsVol. 265
Shenzhen University (CN), University Town of Shenzhen (CN), Shenzhen University Health Science Center (CN), Artificial Intelligence in Medicine (Canada) (CA)
Shenzhen University
Affordable and clean energy
Openalex Percentile: Top 2%
Advanced Sensor and Energy Harvesting Materials
7.93
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.