Evidence map›Paper›PMID 41590295›Full record

ReviewBiosensors2026

Convergent Sensing: Integrating Biometric and Environmental Monitoring in Next-Generation Wearables.

Maria Guarnaccia, Antonio Gianmaria Spampinato, Enrico Alessi, Sebastiano Cavallaro

Abstract readReview
In one paragraph

Review in Biosensors, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Maria GuarnacciaInstitute for Biomedical Research and Innovation, National Research Council, 95126 Catania, Italy.ORCID 0000-0002-3745-9953
Antonio Gianmaria SpampinatoXenia-Software Solution, Aci Castello, 95021 Catania, Italy.
Enrico AlessiAnalog, Power & Discretes, MEMS and Sensors Group, Central R & D, STMicroelectronics, 95121 Catania, Italy.
Sebastiano CavallaroInstitute for Biomedical Research and Innovation, National Research Council, 95126 Catania, Italy.ORCID 0000-0001-7590-1792

Funding

This work was supported by the National Plan for Complementary Investments to the NRRP, project "D34H-Digital Driven Diagnostics, prognostics and therapeutics for sustainable Health care", funded by the Italian Ministry of University and Research. project code: PNC0000001
6 · The paper itself

Abstract

The convergence of biometric and environmental sensing represents a transformative advancement in wearable technology, moving beyond single-parameter tracking towards a holistic, context-aware paradigm for health monitoring. This review comprehensively examines the landscape of multi-modal wearable devices that simultaneously capture physiological data, such as electrodermal activity (EDA), electrocardiogram (ECG), heart rate variability (HRV), and body temperature, alongside environmental exposures, including air quality, ambient temperature, and atmospheric pressure. We analyze the fundamental sensing technologies, data fusion methodologies, and the critical importance of contextualizing physiological signals within an individual's environment to disambiguate health states. A detailed survey of existing commercial and research-grade devices highlights a growing, yet still limited, integration of these domains. As a central case study, we present an integrated prototype, which exemplifies this approach by fusing data from inertial, environmental, and physiological sensors to generate intuitive, composite indices for stress, fitness, and comfort, visualized via a polar graph. Finally, we discuss the significant challenges and future directions for this field, including clinical validation, data security, and power management, underscoring the potential of convergent sensing to revolutionize personalized, predictive healthcare.

Indexed as

BiometryBiosensing TechniquesEnvironmental MonitoringWearable Electronic DevicesDigital HealthHumansMonitoring, Physiologicbiometric monitoringdata fusiondigital healthenvironmental sensinggalvanic skin response (GSR)multi-modal sensingwearable biosensors

Identifiers

PMID41590295
PMCPMC12838745

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.