Wearable devices have emerged as pivotal innovations in oncology, revolutionizing cancer therapy and monitoring through continuous, non-invasive physiological tracking. This comprehensive review examines the integration of advanced wearable technologies-such as electrocardiography (ECG), photoplethysmography (PPG), infrared thermometers, galvanic skin response (GSR) meters, and pulse oximeters-in detecting biomarkers associated with cancer progression and treatment efficacy. By leveraging real-time data acquisition, these devices enable early identification of conditions like chemotherapy-induced cardiotoxicity, evidenced by ECG-derived AI models predicting cardiomyopathy risks with 2-5-fold accuracy, and PPG-based systems detecting vascular anomalies indicative of malignancies. The incorporation of artificial intelligence (AI) and machine learning (ML) algorithms further enhances diagnostic precision, exemplified by AI-ECG tools that dynamically forecast cardiotoxicity 12-24 months prior to clinical onset. Additionally, wearable drug delivery mechanisms, including microneedle patches for localized chemotherapy and programmable ambulatory pumps, are explored for their capacity to optimize therapeutic outcomes while mitigating adverse effects. A systematic analysis of literature sourced from Google Scholar, PubMed, and ScienceDirect underscores the transformative potential of these technologies in fostering personalized oncology care, as demonstrated by clinical trials such as the EMBRaCE program, which reported enhanced patient recovery through continuous monitoring. Despite these advancements, challenges related to motion artifact interference, data heterogeneity, and ethical concerns regarding AI transparency necessitate resolution for widespread clinical adoption. Future trajectories highlight the convergence of multimodal sensor networks with AI-driven analytics to establish autonomous monitoring systems, thereby redefining precision oncology. This review underscores the critical role of wearable devices in advancing theranostic paradigms, advocating for their integration into mainstream oncology to improve early detection, treatment personalization, and overall patient prognoses.
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Bera et al. (2025) studied this question.
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