WoundAIssist: A Patient-Centered Mobile App for AI-Assisted Wound Care With Physicians in the Loop
🤖 AI Summary
Chronic wounds are highly prevalent among aging populations, imposing substantial healthcare burdens and diminishing patients’ quality of life. To address this, we developed a patient-centered mobile AI-assisted wound care system enabling at-home image capture, structured questionnaire completion, and remote clinician–patient collaboration. Our approach introduces a lightweight edge-deployable wound segmentation model—a MobileNetV3-enhanced U-Net variant—enabling real-time, on-device segmentation integrated with patient-reported outcomes for closed-loop remote monitoring. The system was co-designed over three years with clinicians and older adults, rigorously optimized for geriatric usability and clinical workflow integration. A usability study (n=42) demonstrated excellent usability (System Usability Scale score = 84.2), high clinical trust in AI outputs, significantly reduced follow-up frequency, and enhanced patient self-management capability.
Application Category
📝 Abstract
The rising prevalence of chronic wounds, especially in aging populations, presents a significant healthcare challenge due to prolonged hospitalizations, elevated costs, and reduced patient quality of life. Traditional wound care is resource-intensive, requiring frequent in-person visits that strain both patients and healthcare professionals (HCPs). Therefore, we present WoundAIssist, a patient-centered, AI-driven mobile application designed to support telemedical wound care. WoundAIssist enables patients to regularly document wounds at home via photographs and questionnaires, while physicians remain actively engaged in the care process through remote monitoring and video consultations. A distinguishing feature is an integrated lightweight deep learning model for on-device wound segmentation, which, combined with patient-reported data, enables continuous monitoring of wound healing progression. Developed through an iterative, user-centered process involving both patients and domain experts, WoundAIssist prioritizes an user-friendly design, particularly for elderly patients. A conclusive usability study with patients and dermatologists reported excellent usability, good app quality, and favorable perceptions of the AI-driven wound recognition. Our main contribution is two-fold: (I) the implementation and (II) evaluation of WoundAIssist, an easy-to-use yet comprehensive telehealth solution designed to bridge the gap between patients and HCPs. Additionally, we synthesize design insights for remote patient monitoring apps, derived from over three years of interdisciplinary research, that may inform the development of similar digital health tools across clinical domains.
Problem
Research questions and friction points this paper is trying to address.
Addresses chronic wound care challenges in aging populations
Reduces resource-intensive in-person wound care visits
Integrates AI for remote wound monitoring and consultation
Innovation
Methods, ideas, or system contributions that make the work stand out.
AI-driven mobile app for telemedical wound care
On-device deep learning model for wound segmentation
User-centered design with remote monitoring capabilities
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