A Bioelectrically Enabled Smart Bandage for Accelerated Wound Healing and Predictive Monitoring
<i>Background and Objectives:</i> Chronic wounds pose a significant healthcare burden due to their prolonged healing times and susceptibility to infection. Electric field (EF)-enabled smart bandages offer a promising solution by combining therapeutic stimulation with real-time physiologi...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
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| Series: | Medicina |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1648-9144/61/6/965 |
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| Summary: | <i>Background and Objectives:</i> Chronic wounds pose a significant healthcare burden due to their prolonged healing times and susceptibility to infection. Electric field (EF)-enabled smart bandages offer a promising solution by combining therapeutic stimulation with real-time physiological monitoring. <i>Materials and Methods:</i> This study assessed a smart bandage integrating spiral stainless steel electrodes delivering a 200 millivolts per millimeter (mV/mm) EF for 5 h daily over 14 days to full-thickness excisional wounds in 100 Sprague–Dawley rats. Vital signs including heart rate (BPM), oxygen saturation (SpO<sub>2</sub>), and temperature were monitored continuously. Machine learning models were trained on these data to predict wound healing status. <i>Results:</i> By Day 7, EF-treated wounds demonstrated significantly faster healing, achieving an average wound closure rate of 82.0% ± 2.1% compared to 70.75% ± 2.3% in the control group (<i>p</i> < 0.05). By Day 14, wounds in the experimental group had significantly reduced to 0.01 ± 0.005 cm<sup>2</sup>, while the control group retained a wound size of 0.24 ± 0.03 cm<sup>2</sup> (<i>p</i> < 0.05). Histological analysis revealed enhanced neovascularization, collagen alignment, and epithelial regeneration in the EF group. Physiological data showed no systemic inflammatory response. Predictive modeling using XGBoost and Random Forest achieved >98% accuracy, with SHAP (SHapley Additive exPlanations) analysis identifying EF exposure and treatment duration as key predictors. <i>Conclusions:</i> The findings demonstrate that EF-based smart bandages significantly enhance wound healing and enable highly accurate prediction of outcomes through machine learning models. This bioelectronic approach holds strong potential for clinical translation. |
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| ISSN: | 1010-660X 1648-9144 |