Digital Biomarkers: AI wearable sensors for chemotherapy detection

September 26, 2026

Frontiers Unknown

Overview

This perspective article explores how wearable sensors and digital biomarkers can enable subclinical detection of chemotherapy-induced peripheral neuropathy (CIPN). It proposes a framework for prediction and diagnosis through AI analysis, rather than solely by sensors, emphasizing wearables’ potential to complement patient-reported outcomes with an objective neurotoxicity monitoring layer. Further prospective validation is deemed essential to establish their clinical outcome improvement capabilities.

In Depth

Key Findings

This perspective article advocates for a novel approach to detect chemotherapy-induced peripheral neuropathy (CIPN) before patients manifest overt symptoms, by integrating wearable sensors with digital biomarkers. It highlights the potential value of an AI-driven predictive and diagnostic framework, emphasizing its role as an objective monitoring layer that complements, rather than replaces, traditional subjective patient-reported outcomes (PROs).

Technical / Clinical Details

The proposed framework relies on collecting diverse data from wearable sensors, such as activity levels, gait patterns, sleep quality, and heart rate variability. These data streams are then analyzed using advanced AI and machine learning algorithms to develop digital biomarkers. The goal is to objectively and non-invasively capture subtle early signs and progression of CIPN. CIPN, a debilitating side effect of many cancer treatments, causes numbness, pain, and motor dysfunction in extremities, severely impacting patients’ quality of life. Current diagnostic methods often detect neuropathy only after significant progression, making early intervention challenging. Continuous data collection via wearables, coupled with AI-driven analytics, offers an unprecedented opportunity to detect minute changes in neurotoxicity, allowing for timely treatment adjustments and optimized symptom management.

Background & Context

CIPN remains a significant unmet challenge for many cancer patients, and its early detection and management are directly linked to treatment continuity and maintaining quality of life. Historically, CIPN assessment has largely depended on patient self-reporting and clinical neurological examinations, which can be subjective and lack objective quantification. Advances in wearable technology and the application of AI in medicine offer a promising solution to bridge this gap. The introduction of digital biomarkers also contributes to the progress of personalized medicine, enabling customized monitoring and interventions tailored to each patient’s unique CIPN risk and progression.

Strategic Significance & Outlook

While this approach holds immense potential to revolutionize adverse event management in cancer treatment, extensive prospective validation studies are indispensable to establish its clinical efficacy. Key challenges for widespread adoption include standardizing digital biomarkers, ensuring data privacy and security, and providing adequate training for healthcare professionals. In the future, this technology is expected to extend its application beyond CIPN to the early detection and monitoring of other neurological and chronic diseases, significantly expanding the role of wearable sensors and AI in medicine. This innovation could mark a crucial step towards improving patient quality of life and enhancing the overall efficiency of healthcare systems.

Source: https://www.frontiersin.org/articles/10.3389/fonc.2026.1959858

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