ArticleExploration (Beijing, China)2024
Deep-learning enabled smart insole system aiming for multifunctional foot-healthcare applications.
Article in Exploration (Beijing, China), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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
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
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Application of 3D printing in the treatment of diabetic foot ulcers: current status and new insights.Frontiers in bioengineering and biotechnology · 2024Pooled it
- Back Support Pressure for Severity Evaluation and Long-Term Prognostication in Acute Anterior Circulation Ischemic Stroke: A Prospective Cohort Study.Journal of clinical medicine · 2026Article
- A Gear-Driven Plantar Energy Harvester with Integrated Self-Sensing for Human Locomotion Recognition.Sensors (Basel, Switzerland) · 2026Article
- Intelligent soft robotic gripper for non-destructive grasping and attribute recognition via multi-modal waveguide tactile sensors.Microsystems & nanoengineering · 2026Article
- SoleFusion-Net: an explainable multimodal deep learning framework for diabetic foot syndrome classification in type II diabetes mellitus.Scientific reports · 2026Article
- Emergency Clinical Decision for Sports Injury Management: A Wearable Sensor-Driven Framework from Training to Rehabilitation.Biosensors · 2026Review
- Biomechanical Monitoring of Exercise Fatigue Using Wearable Devices: A Review.Bioengineering (Basel, Switzerland) · 2025Review
- Smart and Sustainable: A Global Review of Smart Textiles, IoT Integration, and Human-Centric Design.Sensors (Basel, Switzerland) · 2025Review
- Design, Fabrication, and Application of Large-Area Flexible Pressure and Strain Sensor Arrays: A Review.Micromachines · 2025Review
- Oxide semiconductor based deep-subthreshold operated read-out electronics for all-printed smart sensor patches.Exploration (Beijing, China) · 2025Article
- Trends and Perspectives in Biosensing and Diagnosis.Biosensors · 2024Article
- IoT-Based Wireless System for Gait Kinetics Monitoring in Multi-Device Therapeutic Interventions.Sensors (Basel, Switzerland) · 2024Article
- A Biomechanical Comparison Study of Plate-Nail and Dual-Plate Fixation in AO/OTA 41-C2 Tibial Plateau Fractures.Bioengineering (Basel, Switzerland) · 2024Article
- Human Activity Recognition Algorithm with Physiological and Inertial Signals Fusion: Photoplethysmography, Electrodermal Activity, and Accelerometry.Sensors (Basel, Switzerland) · 2024Article
- Towards a Remote Patient Monitoring Platform for Comprehensive Risk Evaluations for People with Diabetic Foot Ulcers.Sensors (Basel, Switzerland) · 2024Article
- Deep-learning enabled smart insole system aiming for multifunctional foot-healthcare applications.Exploration (Beijing, China) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Real-time foot pressure monitoring using wearable smart systems, with comprehensive foot health monitoring and analysis, can enhance quality of life and prevent foot-related diseases. However, traditional smart insole solutions that rely on basic data analysis methods of manual feature extraction are limited to real-time plantar pressure mapping and gait analysis, failing to meet the diverse needs of users for comprehensive foot healthcare. To address this, we propose a deep learning-enabled smart insole system comprising a plantar pressure sensing insole, portable circuit board, deep learning and data analysis blocks, and software interface. The capacitive sensing insole can map both static and dynamic plantar pressure with a wide range over 500 kPa and excellent sensitivity. Statistical tools are used to analyze long-term foot pressure usage data, providing indicators for early prevention of foot diseases and key data labels for deep learning algorithms to uncover insights into the relationship between plantar pressure patterns and foot issues. Additionally, a segmentation method assisted deep learning model is implemented for exercise-fatigue recognition as a proof of concept, achieving a high classification accuracy of 95%. The system also demonstrates various foot healthcare applications, including daily activity statistics, exercise injury avoidance, and diabetic foot ulcer prevention.
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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.