# Advances in (Bio)Sensors for Physiological Monitoring: A Special Issue Review

**Authors:** Magnus Falk, Sergey Shleev

PMC · DOI: 10.3390/s26020633 · Sensors (Basel, Switzerland) · 2026-01-17

## TL;DR

This paper reviews recent advancements in biosensors for tracking body signals, highlighting their role in personalized healthcare through wearable technology and real-time monitoring.

## Contribution

The paper provides a thematic summary of 18 cutting-edge biosensor studies grouped into five key health monitoring areas.

## Key findings

- Biosensors are enabling real-time tracking of subtle physiological changes for personalized healthcare.
- The reviewed studies span from sensor hardware to data-driven analytics across multiple health domains.
- Themes include cardiovascular monitoring, glucose tracking, wearable movement sensors, neurophysiological interfaces, and sensor innovations.

## Abstract

Physiological monitoring has become an inherently interdisciplinary field, merging advances in engineering, chemistry, biology, medicine, and data analytics to create sensors that continuously track the vital signals of the body. These developments are enabling more personalized and preventive healthcare, as wearable (bio)sensors and intelligent algorithms can detect subtle physiological changes in real-time. In the Special Issue ‘Advances in (Bio)Sensors for Physiological Monitoring’, researchers from diverse domains contributed 18 papers showcasing cutting-edge sensor technologies and applications for health and performance monitoring. In this review, we summarize these contributions by grouping them into logical themes based on their focus: (1) cardiovascular and autonomic monitoring, (2) glucose and metabolic monitoring, (3) wearable sensors for movement and musculoskeletal health, (4) neurophysiological monitoring and brain–computer interfaces, and (5) innovations in sensor technology and methods. This thematic organization highlights the breadth of the research, spanning from fundamental sensor hardware to data-driven analytics, and underscores how modern (bio)sensors are breaking traditional boundaries in healthcare.

## Full-text entities

- **Chemicals:** glucose (MESH:D005947)

## Full text

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## Figures

7 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12845666/full.md

## References

58 references — full list in the complete paper: https://tomesphere.com/paper/PMC12845666/full.md

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Source: https://tomesphere.com/paper/PMC12845666