Multi-sensor wearables for chronic heart failure: From signal-rich devices to equitable, implementable pathways

Sir,

The recent narrative review by Elechi et al¹ on multi-sensor wearables in chronic heart failure (CHF) published in the October 2025 issue of Indian Journal of Medical Research (IJMR) offers a timely synthesis of AI-enabled patches, smartwatches, and smart textiles, and clearly distinguishes device-level performance metrics (lead time, alert burden, detection accuracy) from patient-important outcomes.¹ By foregrounding the ‘vulnerable post-discharge phase’ and multi-sensor congestion indices, the authors rightly frame wearables as potential decision-support tools rather than mere gadgets.¹

When viewed against the rapidly expanding global evidence base, however, this review also highlights critical next steps for translation. Scoping and systematic reviews demonstrate that non-invasive wearable technologies can anticipate heart failure decompensation days to weeks in advance, yet most evaluations remain single-vendor, short-term, and conducted in highly selected cohorts.^2,3 Similarly, Artificial Intelligence (AI)-enhanced consumer devices are increasingly capable of continuous cardiovascular screening and risk stratification at scale, but their algorithms are rarely validated across diverse, real-world heart failure populations.⁴ This creates an ‘implementation gap’ where technically sophisticated tools lack decisional transparency, external validation, and robust cost-effectiveness evidence in routine care.

For India and other low- and middle-income countries (LMICs), the more fundamental question is not whether multi-sensor wearables can detect physiological deterioration, but whether they can be deployed in equity-focused, resource-constrained systems without widening the digital divide. Recent equity analyses of digital health show that access to remote patient monitoring, apps, and wearables remains strongly patterned by income, education, and connectivity, with the lowest utilisation in those at highest risk.⁵ The review by Elechi et al¹ appropriately lists equitable access, workflow-linked triage, and cybersecurity as implementation challenges,¹ but there is an opportunity to translate these into a concrete, testable agenda for low –and middle -income countries’ health systems.

We suggest that future IJMR contributions build on this narrative review to: (i) define a minimal ‘decision-grade’ validation set for heart failure wearables (lead time, false-alarm burden, net clinical benefit, and implementation cost) that can be adopted by Indian programmes; (ii) embed wearables within protocolised heart failure care bundles in district hospitals and primary care, with explicit attention to training, task-sharing, and nurse-led virtual wards; (iii) mandate equity stratifiers (gender, rural residence, socioeconomic status, digital literacy) for all remote-monitoring studies; and (iv) encourage open, regulator-ready reporting of algorithms, including their training data, performance across subgroups, and safeguards against automation bias.^2-5

By positioning multi-sensor heart failure wearables as part of a transparent, equity-first learning health system rather than as stand-alone devices, IJMR can help shape a global standard for how digitally enabled cardiology is evaluated and implemented in real-world, resource-limited settings.^1-5 We congratulate the authors and the Journal for spotlighting this rapidly evolving field, and we hope these suggestions will catalyse future research that is not only technologically advanced but also implementable, affordable, and fair.