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Research and Commercialization Progress of Wearable Multiphysiological Parameter Sensors

  • Pengrui Zhu
  • , Yifan Liu
  • , Hongju Zheng
  • , Bojing Shi*
  • *Corresponding author for this work
  • Beihang University

Research output: Contribution to journalReview articlepeer-review

Abstract

Clinical diagnosis and treatment of patients can be carried out by measuring human physiological parameters such as pulse wave, blood pressure, blood flow rate, body temperature, and sweat. By wearing more sensors, people can monitor their physiological indicators in their daily lives, which plays a key role in the early detection and diagnosis of diseases. This review mainly outlines the research on wearable physiological signal detection devices in the last five years and the commercial physiological signal detection devices that are commonly used today. There are three main aspects: pulse wave signal, blood flow rate signal detection, and sweat signal detection. In terms of pulse wave signal detection, we reviewed piezoelectric, piezoresistive, triboelectric, capacitive, magnetoelasticity, and photoplethysmographic methods. In terms of blood flow velocity detection, a review of noninvasive blood flow velocity detection devices based on the ultrasonic Doppler frequency shift principle is presented in this section. In terms of sweat signal detection, a review of sweat collection and analysis devices is presented, mainly from the perspective of sweat electrolytes, lactate glucose, and other markers. This review aims to introduce and summarize the latest monitoring technologies for wearable sensors and provide technical references and support for further research.

Original languageEnglish
JournalAdvanced Materials Technologies
DOIs
StateAccepted/In press - 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • blood flow velocity
  • commercial sensing devices
  • pulse wave
  • sweat
  • wearable sensing

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