Flexible Transparent Capacitive Pressure Sensors for Multimodal Ophthalmic Monitoring: Intraocular Pressure Assessment, Movement Disorder Diagnosis, and Eye‐Tracking Human–Computer Interaction System

Abstract Contemporary society faces significant public health challenges due to the increasing prevalence of ocular diseases. Traditional ophthalmic examination techniques, while accurate, are unsuitable for routine monitoring due to their complexity and reliance on specialized equipment. In response, ocular wearable devices have emerged, driven by their cost‐effectiveness and minimal power consumption. This study develops a highly flexible transparent capacitive pressure sensor (TCPS). By utilizing a keratin/polyvinyl alcohol (PVA) nanofiber dielectric layer design in conjunction with indium tin oxide (ITO)/polydimethylsiloxane (PDMS) transparent electrodes, this study successfully tackles the critical challenge of achieving an optimal balance among optical transparency (with a transmittance of 91.3%), sensitivity (2.19 kPa −1 ), and stability (up to 8000 cycles). Demonstrating temperature resilience and biocompatibility, and leveraging advanced deep learning algorithms, the sensor successfully facilitates the development of three integrated application systems: i) a real‐time intraocular pressure monitoring system (sensitivity: 0.296 mmHg −1 , linear regression R 2 = 0.975), ii) an eye‐movement‐disorder auxiliary‐diagnostic system (98% accuracy in classifying four distinct oculomotor pathologies), and iii) an eye‐tracking‐based human‐computer interaction (HCI) system for amyotrophic lateral sclerosis patients (99.87% recognition rate for 100 commands via four‐channel signal fusion). This research establishes a novel paradigm for wearable ocular devices in smart healthcare.

Authors

Institutions

Publication Details

Journal
Advanced Functional Materials
Published
2025-10-09
DOI
https://doi.org/10.1002/adfm.202520580
Citations
3
Primary Topic
Gaze Tracking and Assistive Technology
Type
article
Field-Weighted Citation Impact
5.81
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Flexible Transparent Capacitive Pressure Sensors for Multimodal Ophthalmic Monitoring: Intraocular Pressure Assessment, Movement Disorder Diagnosis, and Eye‐Tracking Human–Computer Interaction System

Chenhao Li, Л. Ф. Черногор, Zihe Li, Shengyu Xie et al.
3 citations
Advanced Functional Materials
Gaze Tracking and Assistive Technology
5.81
article

Flexible Transparent Capacitive Pressure Sensors for Multimodal Ophthalmic Monitoring: Intraocular Pressure Assessment, Movement Disorder Diagnosis, and Eye‐Tracking Human–Computer Interaction System

Chenhao Li, Л. Ф. Черногор, Zihe Li, Shengyu Xie, Zhao Yao, Qihui Zhou, Xueqian Liu, Yang Li, Yuanyue Li, Ho‐Kun Sung
article en
3 citations

Abstract

Abstract Contemporary society faces significant public health challenges due to the increasing prevalence of ocular diseases. Traditional ophthalmic examination techniques, while accurate, are unsuitable for routine monitoring due to their complexity and reliance on specialized equipment. In response, ocular wearable devices have emerged, driven by their cost‐effectiveness and minimal power consumption. This study develops a highly flexible transparent capacitive pressure sensor (TCPS). By utilizing a keratin/polyvinyl alcohol (PVA) nanofiber dielectric layer design in conjunction with indium tin oxide (ITO)/polydimethylsiloxane (PDMS) transparent electrodes, this study successfully tackles the critical challenge of achieving an optimal balance among optical transparency (with a transmittance of 91.3%), sensitivity (2.19 kPa −1 ), and stability (up to 8000 cycles). Demonstrating temperature resilience and biocompatibility, and leveraging advanced deep learning algorithms, the sensor successfully facilitates the development of three integrated application systems: i) a real‐time intraocular pressure monitoring system (sensitivity: 0.296 mmHg −1 , linear regression R 2 = 0.975), ii) an eye‐movement‐disorder auxiliary‐diagnostic system (98% accuracy in classifying four distinct oculomotor pathologies), and iii) an eye‐tracking‐based human‐computer interaction (HCI) system for amyotrophic lateral sclerosis patients (99.87% recognition rate for 100 commands via four‐channel signal fusion). This research establishes a novel paradigm for wearable ocular devices in smart healthcare.

Advanced Functional MaterialsVol. 36(17)
Qingdao University (CN), Shandong University (CN), Korea Advanced Nano Fab Center (KR)
Openalex Percentile: Top 4%
Gaze Tracking and Assistive Technology
5.81
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.