Smartphone-Based Biosensor Devices

A special issue of Biosensors (ISSN 2079-6374). This special issue belongs to the section "Biosensor and Bioelectronic Devices".

Deadline for manuscript submissions: 1 August 2025 | Viewed by 565

Special Issue Editors


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Guest Editor
Department of Chemistry “Giacomo Ciamician”, University of Bologna, 40126 Bologna, Italy
Interests: optical biosensors; chemiluminescence biosensors; chemosensors; paper-based devices
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Chemistry “Giacomo Ciamician”, University of Bologna, 40126 Bologna, Italy
Interests: optical biosensors; chemiluminescence biosensors; chemosensors; paper-based devices
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Smartphones are becoming valuable tools for detecting optical and electrochemical signals, either on their own or paired with external sensors. With their high-resolution cameras and advanced processing capabilities, they are especially suited for analyzing light-based signals (e.g., fluorescence, colorimetry, plasmonic resonance, and bio/chemiluminescence) or electrochemical outputs. This makes them ideal for on-site applications in healthcare, environmental monitoring, food safety, and security. Recent innovations have expanded the capabilities of biosensors that incorporate smartphones as detection units. These biosensors rely on biological recognition elements, such as enzymes; aptamers; antibodies; living cells, in both 2D and 3D formats; and artificial receptors like molecularly imprinted polymers (MIPs) and nanomaterials. These components ensure the highly selective and sensitive detection of specific chemicals and biomolecules, enabling fast and reliable diagnostics directly in the field. The integration of smartphone apps further enhances usability, providing intuitive interfaces for signal interpretation and real-time data visualization. These portable systems effectively bridge the gap between complex laboratory analyses and the need for rapid, cost-effective solutions. This Special Issue highlights the potential of smartphones as detectors in biosensor systems, exploring challenges, opportunities, and innovative applications, aiming to revolutionize how we approach diagnostics and monitoring in critical areas of health and environmental management.

Dr. Donato Calabria
Dr. Mara Mirasoli
Guest Editors

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Keywords

  • biosensors
  • optical biosensing
  • surface plasmon resonance
  • fluorescence
  • (bio)chemiluminescence
  • colorimetry
  • electrochemiluminescence
  • paper-based analytical devices
  • microfluidics
  • smartphone-based biosensors
  • portable devices

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Published Papers (1 paper)

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Research

17 pages, 3441 KiB  
Article
Validity and Reliability of a Smartphone-Based Gait Assessment in Measuring Temporal Gait Parameters: Challenges and Recommendations
by Sam Guoshi Liang, Ho Yin Chung, Ka Wing Chu, Yuk Hong Gao, Fong Ying Lau, Wolfe Ixin Lai, Gabriel Ching-Hang Fong, Patrick Wai-Hang Kwong and Freddy Man Hin Lam
Biosensors 2025, 15(7), 397; https://doi.org/10.3390/bios15070397 - 20 Jun 2025
Viewed by 305
Abstract
Smartphone-embedded inertia sensors are widely available nowadays. We have developed a smartphone application that could assess temporal gait characteristics using the built-in inertia measurement unit with the aim of enabling mass screening for gait abnormality. This study aimed to examine the test–retest reliability [...] Read more.
Smartphone-embedded inertia sensors are widely available nowadays. We have developed a smartphone application that could assess temporal gait characteristics using the built-in inertia measurement unit with the aim of enabling mass screening for gait abnormality. This study aimed to examine the test–retest reliability and concurrent validity of the smartphone-based gait assessment in assessing temporal gait parameters in level-ground walking. Twenty-six healthy young adults (mean age: 20.8 ± 0.7) were recruited. Participants walked at their comfortable pace on a 10 m pathway repetitively in two walking sessions. Gait data were simultaneously collected by the smartphone application and a VICON system during the walk. Gait events of heel strike and toes off were detected from the sensors signal by a peak detection algorithm. Further gait parameters were calculated and compared between the two systems. Pearson Product–Moment Correlation was used to evaluate the concurrent validity of both systems. Test–retest reliability was examined by the intraclass correlation coefficients (ICCs) between measurements from two sessions scheduled one to four weeks apart. The validity of smartphone-based gait assessment was moderate to excellent for parameters involving only heel strike detection (r = 0.628–0.977), poor to moderate for parameters involving detection of both heel strike and toes off (r = 0.098–0.704), and poor for the proportion of gait phases within a gait cycle. Reliability was good to fair for heel strike-related parameters (ICC = 0.845–0.388), good to moderate for heel strike and toes-off-related parameters (ICC = 0.827–0.582), and moderate to fair for proportional parameters. Validity was adversely affected when toe off was involved in the calculation, when there was an insufficient number of effective steps taken, or when calculating sub-phases with short duration. The use of smartphone-based gait assessment is recommended in calculating step time and stride time, and we suggest collecting no less than 100 steps per leg during clinical application for better validity and reliability. Full article
(This article belongs to the Special Issue Smartphone-Based Biosensor Devices)
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