Wearable Electrochemical Biosensors for Monitoring and Management of Chronic Wounds
Abstract
1. Introduction
2. Pathophysiological Mechanisms of Chronic Wounds and Implications for Biosensor Design
2.1. Definition of Chronic Wound
2.2. Pathophysiological Characteristics of Chronic Wound
2.3. Healing Impairment Factors and Sensing Targets
3. Recent Advances in Wearable Electrochemical Biosensors for Wound Management
3.1. Development Status of Functional Materials
3.2. Closed-Loop Theranostic Systems
3.3. Multi-Modal Sensing and AI-Enhanced Diagnostic Analytics
4. Electrochemical Biosensors for Wound Monitoring and Healing
4.1. Real-Time Wound Monitoring
4.2. Early Detection of Wound Infection
4.3. Smart Sensing-Actuating Platforms for Intelligent Wound Management
5. Challenges and Limitations
5.1. Technical Challenges
5.2. Clinical Translation
5.3. Power Management
6. Advancing Technical Solutions: Addressing Key Barriers in Wearable Wound Sensing Technology
6.1. Multimodal Sensing and Signal Enhancement
6.2. Self-Powered Sensing and Active Therapeutics
6.3. Intelligent Telemedicine for Dynamic Wound Management
7. Conclusions and Prospects
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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| Biological Markers | Detection Ranges | Reference Values for Health Status | Abnormal Threshold/Clinical Significance | Multi-Parameter Interlocking Value |
|---|---|---|---|---|
| Temperature | 25–40 °C (Sensor range) | 31.1–36.5 °C (Recovery of normal wound) | Below normal: ↓ 2.2 °C → Blood circulation disorder/Enzyme activity reduction/Lymphocyte decrease Above normal: ↑ 2.2 °C → Infection/Severe inflammation | Linked pH compensation for detecting errors |
| pH | 4.0–9.0 (CW-care) 5–10 (e-ECM) | 4.0–6.5 (Healthy skin/Acute wounds) | >7.0: Markers of chronic wound alkalization >10.0: Severe infection (such as alkaline-producing bacteria/MRSA biofilm) Pathological mechanism: Ischemia-reperfusion injury → Bacterial proliferation | Regulation of collagen synthesis/angiogenesis/pathogen inhibition |
| Uric acid (UA) | 0–150 μM (CW-care) | 220–750 μM (No infection status) | <200 μM: Indicator of bacterial infection | Different from the specific infection indicators of endogenous metabolism |
| Glucose | 0–40 mM (CW-care) 0–8 mM (e-ECM) | Diabetic wound fluctuations: 0–1.2 mM | Hyperglycemia: Inhibits HIF-1α → Promotes angiogenesis; Facilitates tissue necrosis; Bacterial proliferation | The core metabolic indicators for the prognosis of diabetic wounds |
| Lactic acid | 0–4 mM (CW-care) 0–30 mM (e-ECM) | - | Continuity: Oxygen deprivation metabolic markers; Association with inflammation severity | Concurrently assess tissue hypoxia with oxygen |
| Na+ | 133–146 mM | - | Imbalance: Disruption of interstitial fluid osmotic pressure → Delayed healing | Reflecting the homeostasis of the wound microenvironment |
| K+ | 3.2–5.7 mM | - | Imbalance: Abnormal cell membrane potential → Restoration of cell function | Reflect the metabolic state of cells |
| Dissolved oxygen | 0–3.35 mL/L (e-ECM) | - | Low oxygen: Vascularization/Collagen deposition ↓; Macrophage recruitment is blocked High oxygen: Guided oxygen therapy intervention | Linking with ROS to evaluate oxidative stress |
| ROS | - | - | Upregulation-Marker of infection and chronic inflammation; Strongly associated with impaired healing | Sensitive indicators preceding clinical infection |
| Microbial metabolites | - | - | Specific markers: Pseudomonas aeruginosa: Pyocyanin; Staphylococcus aureus: Phospholipase A2/α-hemolysin | Pathogen typing and targeted therapy basis |
| Application Domain | Sensing Principle | Fundamental Advantages | Inherent Limitations | Clinical Adaptability |
|---|---|---|---|---|
| Infection Diagnosis | Specific biorecognition mechanisms (enzyme-substrate or antigen-antibody binding) | High pathogen targeting and molecular resolution capability | Bioprobe degradation and coexisting interferents | In vivo validation is needed to address complex matrix effects |
| Inflammation Monitoring | Immunoelectrochemical methods (labeled or label-free binding detection) | Multiplex compatibility and ultrasensitivity | Antibody instability and narrow dynamic range | Requires validation through in vivo inflammation models |
| Metabolite Analysis | Enzymatic catalysis or direct oxidation of electroactive species | Direct metabolic pathway mapping and real-time tracking | Enzyme denaturation and electroactive interference | Necessitates continuous in vivo monitoring |
| Wound Environment Tracking | Physicochemical signal conversion via electrical changes (potential/resistance/capacitance) | Wide linear range and continuous parameter monitoring | Sensor drift and mechanical stress sensitivity | Requires long-term in vivo stability verification |
| Therapeutic Feedback Control | Closed-loop sensing-actuation coupling triggering therapeutic delivery | Integrated diagnosis-therapy systems and adaptive intervention | System latency and limited drug payload capacity | Mandates in vivo therapeutic efficacy validation |
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Zuo, L.; Liu, Y.; Zhang, J.; Wang, L.; Zhu, J.-J. Wearable Electrochemical Biosensors for Monitoring and Management of Chronic Wounds. Biosensors 2025, 15, 785. https://doi.org/10.3390/bios15120785
Zuo L, Liu Y, Zhang J, Wang L, Zhu J-J. Wearable Electrochemical Biosensors for Monitoring and Management of Chronic Wounds. Biosensors. 2025; 15(12):785. https://doi.org/10.3390/bios15120785
Chicago/Turabian StyleZuo, Lingxia, Yinbing Liu, Jianrong Zhang, Linlin Wang, and Jun-Jie Zhu. 2025. "Wearable Electrochemical Biosensors for Monitoring and Management of Chronic Wounds" Biosensors 15, no. 12: 785. https://doi.org/10.3390/bios15120785
APA StyleZuo, L., Liu, Y., Zhang, J., Wang, L., & Zhu, J.-J. (2025). Wearable Electrochemical Biosensors for Monitoring and Management of Chronic Wounds. Biosensors, 15(12), 785. https://doi.org/10.3390/bios15120785
