Abstract
There are serious problems with chronic wounds like bedsores and diabetic ulcers, which are observed and treated with the current wound care methods that mainly use traditional bandages. These bandages only provide basic security and are unable to track wound data like infection and SpO2 levels. This may lead to delayed detection of problems and prolonged healing times. A smart bandage with several sensors is proposed in this method to overcome the limitations. The developed system’s temperature, pH and SpO2 sensors are mostly used to monitor the wounds. Data from these different sensors is processed by an embedded TinyML-based AI system to assess and provide wound healing stages, detect infections, and notify users regarding infection levels. Important measures, including temperature, pH, and SpO2 levels, are displayed in a developed application so that patients and doctors can track progress and receive real-time notifications. Using machine learning algorithms, the data will analyze the wound healing phases and also have the ability to perform real-time monitoring and infection detection quickly. This smart sensor represents a significant advance over traditional approaches for better wound care management.
References
- Prakashan, Drishya, Ajeet Kaushik, and Sonu Gandhi. "Smart sensors and wound dressings: Artificial intelligence-supported chronic skin monitoring–A review." Chemical Engineering Journal (2024): 154371.
- Turki, Ahmad F., and Aziza R. Alrafiah. "A Bioelectrically Enabled Smart Bandage for Accelerated Wound Healing and Predictive Monitoring." Medicina 61, no. 6 (2025): 965.
- Dabas, Mai, Dafna Schwartz, Dimitri Beeckman, and Amit Gefen. "Application of artificial intelligence methodologies to chronic wound care and management: a scoping review." Advances in wound care 12, no. 4 (2023): 205-240.
- Pang, Qian, Fang Yang, Zilian Jiang, Kaihao Wu, Ruixia Hou, and Yabin Zhu. "Smart wound dressing for advanced wound management: Real-time monitoring and on-demand treatment." Materials & Design 229 (2023): 111917.
- Ganesan, Ovya, Miranda Xiao Morris, Lifei Guo, and Dennis Orgill. "A review of artificial intelligence in wound care." Artificial Intelligence Surgery 4, no. 4 (2024): 364-375.
- Mishra, Abhishek, Aniket Kushare, Munishwar Nath Gupta, and Premlata Ambre. "Advanced dressings for chronic wound management." ACS Applied Bio Materials 7, no. 5 (2024): 2660-2676.
- McLister, Anna, Jolene McHugh, Jill Cundell, and James Davis. "New developments in smart bandage technologies for wound diagnostics." Advanced Materials 28, no. 27 (2016): 5732-5737.
- Wang, Canran, Ehsan Shirzaei Sani, Chia-Ding Shih, Chwee Teck Lim, Joseph Wang, David G. Armstrong, and Wei Gao. "Wound management materials and technologies from bench to bedside and beyond." Nature Reviews Materials 9, no. 8 (2024): 550-566.
- Rathi, Karishma, Shraddha Gupta, Gayatri Korade, Gulshan Rathi, and S. M. Firdous. "Artificial Intelligence for Wound Healing (IE, Real-Time Monitoring, Image-Based, Bioinformatics, and Precision Regulation)." In Nanotechnology in Wound Healing, pp. 64-88. CRC Press, 2025.
- Petkar, Taniya G., Praveen Kumar, and Kirtiksha U. Sarate. "Application of AI and ML in Wound Healing and Skin Regeneration." In 2025 4th International Conference on Sentiment Analysis and Deep Learning (ICSADL), pp. 1724-1730. IEEE, 2025.
