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Wearable Biomedical Sensors 2019

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biosensors".

Deadline for manuscript submissions: closed (20 July 2019) | Viewed by 49987

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Special Issue Editors

Prof. Dr. Eiichi Tamiya

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Guest Editor

1. Advanced Photonics and Biosensing Open Innovation Laboratory, National Institute of Advanced Industrial Science and Technology, 2-1 Yamadaoka, Suita 565-0871, Osaka, Japan
2. Institute of Scientific and Industrial Research, Osaka University, 8-1 Mihogaoka, Ibaraki 567-0047, Osaka, Japan
Interests: nanobiotechnology; advanced biosensor; bioMEMS; cell based device; biosensors for IoT
Special Issues, Collections and Topics in MDPI journals

Dr. Mun'delanji Vestergaard

E-Mail Website
Guest Editor

Department of Food Science and Biotechnology, Kagoshima University, 1-21-24 Korimoto, Kagoshima, Kagoshima Prefecture 890-8580, Japan
Interests: bio-efficacy of natural products; biofunctional materials; point-of-need application; biomimetic membranes
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Patrick Degenaar

E-Mail Website
Guest Editor

School of Electrical and Electronic Engineering, Newcastle University, Newcastle NE1 7RU, UK
Interests: implantable electronics; neuroprosthetics; visual prosthesis; bionics; bioelectronics; electroceuticals; bioelectronic medicine; optogenetics; optoelectronics

Dr. Shin-ichi Wakida

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Guest Editor

Dupty Director, PhotoBIO-OIL National Institute of Advanced Industrial Science and Technology, Tokyo, Japan

Special Issue Information

Dear Colleagues,

Biosensors have given us excellent tools for monitoring evidential biomarkers, which are related to medical diagnosis, healthcare, food safety and environmental monitoring. Biomarkers indicate molecular information, such as proteins, genes, metabolites, pathogens. Biosensors consist of a molecular recognition part and a transducer part in principle. Selective and sensitive monitoring is considered to be an advantageous aspect in biosensors. Miniaturization and nano technology are powerful and can produce smaller, highly-integrated and functional biosensors for shaping wearable devices. Wearable biosensors can be applied to non-invasive monitoring using sweat, tear, and saliva samples, which include good bioindicators. Implanted biosensor are available for semi-continuous monitoring of glucose for diabetic patients. Microneedle devices will be applied to painlessly monitor target biomarkers from skin. Biosensors can be operated using smartphones and pocket PCs connected to the Internet, the so-called Internet of Things (IoT). Needless to say, e-glass and e-watches are able to function as wearable devices, linking biosensors. Electrochemistry, photonics, electronics-based device would be reliable and reproductive for biosensors. Wearable biomedical biosensors would contribute to good health and maintain a high activity in global aging communities. They also could produce on-site monitoring tools for developing areas, which have suffered from food and environmental pollution.

Dr. Eiichi Tamiya
Dr. Mun'delanji Vestergaard
Dr. Patrick Degenaar
Dr. Shin-ichi Wakida
Guest Editors

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Keywords

Biomarkers; Healthcare; Medical Diagnosis; Food/environmental safety; e-health; Airborne monitoring; Pathogen monitoring; Immunosensors; DNA sensors; Breath; Sweat; Skin; Urine; Tear; Saliva; Drop of blood; Implantable; Microneedle; Electrochemical biosensors; Photonic biosensors; Mass biosensors; Wireless transmission; Flexible sensors; Watch type; Eye glass type; Patch type; Ring type; Smartphone; Pocket PC

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Published Papers (6 papers)

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Research

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18 pages, 1777 KiB

Open AccessArticle

Comparison of Active Electrode Materials for Non-Contact ECG Measurement

by Shun Peng, Ke Xu and Wei Chen

Sensors 2019, 19(16), 3585; https://doi.org/10.3390/s19163585 - 17 Aug 2019

Cited by 33 | Viewed by 6363

Abstract

For long-term and more convenience electrocardiograph (ECG) monitoring, an active- electrode-based ECG monitoring system, which can measure ECG through clothes, is proposed in this paper. The hardware of the system includes active electrodes, signal processing and data transmission modules and the software mainly includes a denoising algorithm based on empirical mode decomposition (EMD). Then the proposed system was verified using the comparison of the ECG signals measured synchronously by active electrodes and Ag/AgCl electrodes. In addition, three flexible materials, including conductive textile, copper foil tape and a flexible printed circuit (FPC) are developed for the sensing layer with active electrodes. To compare the performance of these three materials for the sensing layer, the ECG signals of 10 subjects were measured by different materials in three postures and several indexes for quality evaluation were calculated. Results show that effective and clear ECG waveforms can be measured by all three kinds of materials and the quality of ECG signals measured by FPC is the best by conducting a significant t-test for signal quality indexes of three materials. Full article

(This article belongs to the Special Issue Wearable Biomedical Sensors 2019)

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23 pages, 2518 KiB

Open AccessArticle

Design and Implementation of an Ultra-Low Resource Electrodermal Activity Sensor for Wearable Applications ^‡

by Gunnar C. Pope and Ryan J. Halter

Sensors 2019, 19(11), 2450; https://doi.org/10.3390/s19112450 - 29 May 2019

Cited by 15 | Viewed by 5495

Abstract

While modern low-power microcontrollers are a cornerstone of wearable physiological sensors, their limited on-chip storage typically makes peripheral storage devices a requirement for long-term physiological sensing—significantly increasing both size and power consumption. Here, a wearable biosensor system capable of long-term recording of physiological signals using a single, 64 kB microcontroller to minimize sensor size and improve energy performance is described. Electrodermal (EDA) signals were sampled and compressed using a multiresolution wavelet transformation to achieve long-term storage within the limited memory of a 16-bit microcontroller. The distortion of the compressed signal and errors in extracting common EDA features is evaluated across 253 independent EDA signals acquired from human volunteers. At a compression ratio (CR) of 23.3×, the root mean square error (RMSErr) is below 0.016

μ

S and the percent root-mean-square difference (PRD) is below 1%. Tonic EDA features are preserved at a CR = 23.3× while phasic EDA features are more prone to reconstruction errors at CRs > 8.8×. This compression method is shown to be competitive with other compressive sensing-based approaches for EDA measurement while enabling on-board access to raw EDA data and efficient signal reconstructions. The system and compression method provided improves the functionality of low-resource microcontrollers by limiting the need for external memory devices and wireless connectivity to advance the miniaturization of wearable biosensors for mobile applications. Full article

(This article belongs to the Special Issue Wearable Biomedical Sensors 2019)

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19 pages, 1916 KiB

Open AccessArticle

A Wearable Wrist Band-Type System for Multimodal Biometrics Integrated with Multispectral Skin Photomatrix and Electrocardiogram Sensors

by Hanvit Kim, Haena Kim, Se Young Chun, Jae-Hwan Kang, Ian Oakley, Youryang Lee, Jun Oh Ryu, Min Joon Kim, In Kyu Park, Hyuck Ki Hong, Young Chang Jo and Sung-Phil Kim

Sensors 2018, 18(8), 2738; https://doi.org/10.3390/s18082738 - 20 Aug 2018

Cited by 9 | Viewed by 10735

Abstract

Multimodal biometrics are promising for providing a strong security level for personal authentication, yet the implementation of a multimodal biometric system for practical usage need to meet such criteria that multimodal biometric signals should be easy to acquire but not easily compromised. We developed a wearable wrist band integrated with multispectral skin photomatrix (MSP) and electrocardiogram (ECG) sensors to improve the issues of collectability, performance and circumvention of multimodal biometric authentication. The band was designed to ensure collectability by sensing both MSP and ECG easily and to achieve high authentication performance with low computation, efficient memory usage, and relatively fast response. Acquisition of MSP and ECG using contact-based sensors could also prevent remote access to personal data. Personal authentication with multimodal biometrics using the integrated wearable wrist band was evaluated in 150 subjects and resulted in 0.2% equal error rate (

EER

) and 100% detection probability at 1%

FAR

(false acceptance rate) (

PD . 1

), which is comparable to other state-of-the-art multimodal biometrics. An additional investigation with a separate MSP sensor, which enhanced contact with the skin, along with ECG reached 0.1%

EER

and 100%

PD . 1

, showing a great potential of our in-house wearable band for practical applications. The results of this study demonstrate that our newly developed wearable wrist band may provide a reliable and easy-to-use multimodal biometric solution for personal authentication. Full article

(This article belongs to the Special Issue Wearable Biomedical Sensors 2019)

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17 pages, 1821 KiB

Open AccessArticle

An Auto-Calibrating Knee Flexion-Extension Axis Estimator Using Principal Component Analysis with Inertial Sensors

by Timothy McGrath, Richard Fineman and Leia Stirling

Sensors 2018, 18(6), 1882; https://doi.org/10.3390/s18061882 - 8 Jun 2018

Cited by 52 | Viewed by 6759 | Correction

Abstract

Inertial measurement units (IMUs) have been demonstrated to reliably measure human joint angles—an essential quantity in the study of biomechanics. However, most previous literature proposed IMU-based joint angle measurement systems that required manual alignment or prescribed calibration motions. This paper presents a simple, physically-intuitive method for IMU-based measurement of the knee flexion/extension angle in gait without requiring alignment or discrete calibration, based on computationally-efficient and easy-to-implement Principle Component Analysis (PCA). The method is compared against an optical motion capture knee flexion/extension angle modeled through OpenSim. The method is evaluated using both measured and simulated IMU data in an observational study (n = 15) with an absolute root-mean-square-error (RMSE) of 9.24

^{\circ}

and a zero-mean RMSE of 3.49

^{\circ}

. Variation in error across subjects was found, made emergent by the larger subject population than previous literature considers. Finally, the paper presents an explanatory model of RMSE on IMU mounting location. The observational data suggest that RMSE of the method is a function of thigh IMU perturbation and axis estimation quality. However, the effect size for these parameters is small in comparison to potential gains from improved IMU orientation estimations. Results also highlight the need to set relevant datums from which to interpret joint angles for both truth references and estimated data. Full article

(This article belongs to the Special Issue Wearable Biomedical Sensors 2019)

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Review

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24 pages, 3145 KiB

Open AccessFeature PaperReview

Wearable Potentiometric Sensors for Medical Applications

by María Cuartero, Marc Parrilla and Gaston A. Crespo

Sensors 2019, 19(2), 363; https://doi.org/10.3390/s19020363 - 17 Jan 2019

Cited by 117 | Viewed by 16661

Abstract

Wearable potentiometric sensors have received considerable attention owing to their great potential in a wide range of physiological and clinical applications, particularly involving ion detection in sweat. Despite the significant progress in the manner that potentiometric sensors are integrated in wearable devices, in terms of materials and fabrication approaches, there is yet plenty of room for improvement in the strategy adopted for the sample collection. Essentially, this involves a fluidic sampling cell for continuous sweat analysis during sport performance or sweat accumulation via iontophoresis induction for one-spot measurements in medical settings. Even though the majority of the reported papers from the last five years describe on-body tests of wearable potentiometric sensors while the individual is practicing a physical activity, the medical utilization of these devices has been demonstrated on very few occasions and only in the context of cystic fibrosis diagnosis. In this sense, it may be important to explore the implementation of wearable potentiometric sensors into the analysis of other biofluids, such as saliva, tears and urine, as herein discussed. While the fabrication and uses of wearable potentiometric sensors vary widely, there are many common issues related to the analytical characterization of such devices that must be consciously addressed, especially in terms of sensor calibration and the validation of on-body measurements. After the assessment of key wearable potentiometric sensors reported over the last five years, with particular attention paid to those for medical applications, the present review offers tentative guidance regarding the characterization of analytical performance as well as analytical and clinical validations, thereby aiming at generating debate in the scientific community to allow for the establishment of well-conceived protocols. Full article

(This article belongs to the Special Issue Wearable Biomedical Sensors 2019)

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