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Special Issue "Flexible Sensors for Medical Applications"

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

Deadline for manuscript submissions: closed (31 July 2023) | Viewed by 9808

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Special Issue Editors

Prof. Dr. Ning Xue

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Guest Editor

State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
Interests: flexible medical sensing systems (implantable and wearable)
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Jun Zhou
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Guest Editor

School of Communication and Information Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
Interests: intelligence circuit and algorithm embedded in flexible sensor for medical applcations

Prof. Dr. Chia-Ching Chang

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Guest Editor

Department of Biological Science and Technology, National Chiao Tung University, 75 Bo-Ai Street, Hsinchu 30068, Taiwan
Interests: biointerface science and technology; biomaterials; biophotonics; biosensors; bioelectronics; soft condensed matter; biological physics
Special Issues, Collections and Topics in MDPI journals

Dr. Wing Cheung Mak

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Guest Editor

Department of Physics, Chemistry and Biology, Linköping University, 58183 Linköping, Sweden
Interests: electrochemical biosensors; organic bioelectronics; conducting polymer transducers; bionics; biointerfaces; optical sensors; lateral flow tests; paper-based analytical devices
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Over the past few decades, great progress has been made in flexible sensors for biomedical applications. Many biomedical devices, such as electronic skin and implatable recorder devices, are already on the market and have been crucial to improving the quality of life of patients. There is still great demand for developing newer and better technologies for many other biomedical applications with attributes such as disease monotring, health monotring with minimum invasiveness, skin friendly, and good biocompatibility. To realize smaller, more accurate, and highly reliable sensing functions for wearable and implantable flexible devices, interdisciplinary technologies, i.e., microfabrication, tissue engineering, artificial intelligence algorithms, and integrated circuits, have been explored. In this Special Issue entitled Flexible Sensors for Medical Applications, we wish to highlight studies on constructing flexible sensing devices or systems for biomedical applications, including but not limited to biomaterial synthesis, device fabrication, bio-circuits.

Prof. Dr. Ning Xue
Prof. Dr. Jun Zhou
Prof. Dr. Chia-Ching Chang
Dr. Wing Cheung Mak
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biosensors is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

flexible biosensors
wearable sensors
implantable sensors
medical sensors
neural interface
bio-MEMS
flexible prosthetics
electronic skin
bio-sensors

Published Papers (6 papers)

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Research

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Open AccessArticle

Elderly Fall Detection Based on GCN-LSTM Multi-Task Learning Using Nursing Aids Integrated with Multi-Array Flexible Tactile Sensors

and

Biosensors 2023, 13(9), 862; https://doi.org/10.3390/bios13090862 - 31 Aug 2023

Viewed by 437

Abstract

Due to the frailty of elderly individuals’ physical condition, falling can lead to severe bodily injuries. Effective fall detection can significantly reduce the occurrence of such incidents. However, current fall detection methods heavily rely on visual and multi-sensor devices, which incur higher costs and complex wearable designs, limiting their wide-ranging applicability. In this paper, we propose a fall detection method based on nursing aids integrated with multi-array flexible tactile sensors. We design a kind of multi-array capacitive tactile sensor and arrange the distribution of tactile sensors on the foot based on plantar force analysis and measure tactile sequences from the sole of the foot to develop a dataset. Then we construct a fall detection model based on a graph convolution neural network and long-short term memory network (GCN-LSTM), where the GCN module and LSTM module separately extract spatial and temporal features from the tactile sequences, achieving detection on tactile data of foot and walking states for specific time series in the future. Experiments are carried out with the fall detection model, the Mean Squared Error (MSE) of the predicted tactile data of the foot at the next time step is 0.0716, with the fall detection accuracy of 96.36%. What is more, the model can achieve fall detection on 5-time steps with 0.2-s intervals in the future with high confidence results. It exhibits outstanding performance, surpassing other baseline algorithms. Besides, we conduct experiments on different ground types and ground morphologies for fall detection, and the model showcases robust generalization capabilities. Full article

(This article belongs to the Special Issue Flexible Sensors for Medical Applications)

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Open AccessArticle

A Self-Powered Multifunctional Bracelet for Pulse Monitoring and Personal Rescue

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Biosensors 2023, 13(5), 552; https://doi.org/10.3390/bios13050552 - 16 May 2023

Cited by 1 | Viewed by 1089

Abstract

For outdoor workers or explorers who may be exposed to extreme or wild environments for a long time, wearable electronic devices with continuous health monitoring and personal rescue functions in emergencies could play an important role in protecting their lives. However, the limited battery capacity leads to a limited serving time, which cannot ensure normal operation anywhere and at any time. In this work, a self-powered multifunctional bracelet is proposed by integrating a hybrid energy supply module and a coupled pulse monitoring sensor with the inherent structure of the watch. The hybrid energy supply module can harvest rotational kinetic energy and elastic potential energy from the watch strap swinging simultaneously, generating a voltage of 69 V and a current of 87 mA. Meanwhile, with a statically indeterminate structure design and the coupling of triboelectric and piezoelectric nanogenerators, the bracelet enables stable pulse signal monitoring during movement with a strong anti-interference ability. With the assistance of functional electronic components, the pulse signal and position information of the wearer can be transmitted wirelessly in real-time, and the rescue light and illuminating light can be driven directly by flipping the watch strap slightly. The universal compact design, efficient energy conversion, and stable physiological monitoring demonstrate the wide application prospects of the self-powered multifunctional bracelet. Full article

(This article belongs to the Special Issue Flexible Sensors for Medical Applications)

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Open AccessArticle

A High Accuracy & Ultra-Low Power ECG-Derived Respiration Estimation Processor for Wearable Respiration Monitoring Sensor

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Biosensors 2022, 12(8), 665; https://doi.org/10.3390/bios12080665 - 22 Aug 2022

Viewed by 1312

Abstract

The respiratory rate is widely used for evaluating a person’s health condition. Compared to other invasive and expensive methods, the ECG-derived respiration estimation is a more comfortable and affordable method to obtain the respiration rate. However, the existing ECG-derived respiration estimation methods suffer from low accuracy or high computational complexity. In this work, a high accuracy and ultra-low power ECG-derived respiration estimation processor has been proposed. Several techniques have been proposed to improve the accuracy and reduce the computational complexity (and thus power consumption), including QRS detection using refractory period refreshing and adaptive threshold EDR estimation. Implemented and fabricated using a 55 nm processing technology, the proposed processor achieves a low EDR estimation error of 0.73 on CEBS database and 1.2 on MIT-BIH Polysomnographic Database while demonstrating a record-low power consumption (354 nW) for the respiration monitoring, outperforming the existing designs. The proposed processor can be integrated in a wearable sensor for ultra-low power and high accuracy respiration monitoring. Full article

(This article belongs to the Special Issue Flexible Sensors for Medical Applications)

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Open AccessArticle

A Flexible Ultrasound Array for Local Pulse Wave Velocity Monitoring

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Biosensors 2022, 12(7), 479; https://doi.org/10.3390/bios12070479 - 30 Jun 2022

Cited by 5 | Viewed by 1792

Abstract

Pulse wave velocity (PWV) measured at a specific artery location is called local PWV, which provides the elastic characteristics of arteries and indicates the degree of arterial stiffness. However, the large and cumbersome ultrasound probes require an appropriate sensor position and pressure maintenance, [...] Read more.

μ

m) flexible ultrasound array by encapsulating 1–3 composite piezoelectric transducers with a silicone elastomer. It can capture the distension waveforms of four arterial positions with a spacing of 10 mm and calculate the local PWV by multi-point fitting. This is illustrated by in vivo experiments, where the local PWV value of five normal subjects ranged from 3.07 to 4.82 m/s, in agreement with earlier studies. The beat-to-beat coefficient of variation (CV) is 12.0% ± 3.5%, showing high reliability. High reproducibility is shown by the results of two groups of independent measurements of three subjects (the error between the mean values is less than 0.3 m/s). These properties of the developed flexible ultrasound array enable the bandage-like application of local PWV monitoring to skin surfaces. Full article

(This article belongs to the Special Issue Flexible Sensors for Medical Applications)

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Open AccessArticle

An iEEG Recording and Adjustable Shunt-Current Conduction Platform for Epilepsy Treatment

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Biosensors 2022, 12(4), 247; https://doi.org/10.3390/bios12040247 - 15 Apr 2022

Cited by 3 | Viewed by 1840

Abstract

This paper proposes a compact bioelectronics sensing platform, including a multi-channel electrode, intracranial electroencephalogram (iEEG) recorder, adjustable galvanometer, and shunt-current conduction circuit pathway. The developed implantable electrode made of polyurethane-insulated stainless-steel materials is capable of recording iEEG signals and shunt-current conduction. The electrochemical impedance of the conduction, ground/reference, and working electrode were characterized in phosphate buffer saline solution, revealing in vitro results of 517.2 Ω@1 kHz (length of 0.1 mm, diameter of 0.8 mm), 1.374 kΩ@1 kHz (length of 0.3 mm, diameter of 0.1 mm), and 3.188 kΩ@1 kHz (length of 0.1 mm, diameter of 0.1 mm), respectively. On-bench measurement of the system revealed that the input noise of the system is less than 2 μVrms, the signal frequency bandwidth range is 1 Hz~10 kHz, and the shunt-current detection range is 0.1~3000 μA with an accuracy of above 99.985%. The electrode was implanted in the CA1 region of the right hippocampus of rats for the in vivo experiments. Kainic acid (KA)-induced seizures were detected through iEEG monitoring, and the induced shunt-current was successfully measured and conducted out of the brain through the designed circuit-body path, which verifies the potential of current conduction for the treatment of epilepsy. Full article

(This article belongs to the Special Issue Flexible Sensors for Medical Applications)

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Review

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Open AccessEditor’s ChoiceReview

A Review: Research Progress of Neural Probes for Brain Research and Brain–Computer Interface

Jiahui Luo

Ning Xue

and

Jiamin Chen

Biosensors 2022, 12(12), 1167; https://doi.org/10.3390/bios12121167 - 14 Dec 2022

Cited by 3 | Viewed by 1725

Abstract

Neural probes, as an invasive physiological tool at the mesoscopic scale, can decipher the code of brain connections and communications from the cellular or even molecular level, and realize information fusion between the human body and external machines. In addition to traditional electrodes, two new types of neural probes have been developed in recent years: optoprobes based on optogenetics and magnetrodes that record neural magnetic signals. In this review, we give a comprehensive overview of these three kinds of neural probes. We firstly discuss the development of microelectrodes and strategies for their flexibility, which is mainly represented by the selection of flexible substrates and new electrode materials. Subsequently, the concept of optogenetics is introduced, followed by the review of several novel structures of optoprobes, which are divided into multifunctional optoprobes integrated with microfluidic channels, artifact-free optoprobes, three-dimensional drivable optoprobes, and flexible optoprobes. At last, we introduce the fundamental perspectives of magnetoresistive (MR) sensors and then review the research progress of magnetrodes based on it. Full article

(This article belongs to the Special Issue Flexible Sensors for Medical Applications)

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