1
|
Ding S, Zhao D, Chen Y, Dai Z, Zhao Q, Gao Y, Zhong J, Luo J, Zhou B. Single Channel Based Interference-Free and Self-Powered Human-Machine Interactive Interface Using Eigenfrequency-Dominant Mechanism. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2302782. [PMID: 38287891 PMCID: PMC10987133 DOI: 10.1002/advs.202302782] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 09/28/2023] [Indexed: 01/31/2024]
Abstract
The recent development of wearable devices is revolutionizing the way of human-machine interaction (HMI). Nowadays, an interactive interface that carries more embedded information is desired to fulfill the increasing demand in era of Internet of Things. However, present approach normally relies on sensor arrays for memory expansion, which inevitably brings the concern of wiring complexity, signal differentiation, power consumption, and miniaturization. Herein, a one-channel based self-powered HMI interface, which uses the eigenfrequency of magnetized micropillar (MMP) as identification mechanism, is reported. When manually vibrated, the inherent recovery of the MMP causes a damped oscillation that generates current signals because of Faraday's Law of induction. The time-to-frequency conversion explores the MMP-related eigenfrequency, which provides a specific solution to allocate diverse commands in an interference-free behavior even with one electric channel. A cylindrical cantilever model is built to regulate the MMP eigenfrequencies via precisely designing the dimensional parameters and material properties. It is shown that using one device and two electrodes, high-capacity HMI interface can be realized when the magnetic micropillars (MMPs) with different eigenfrequencies have been integrated. This study provides the reference value to design the future HMI system especially for situations that require a more intuitive and intelligent communication experience with high-memory demand.
Collapse
Affiliation(s)
- Sen Ding
- Joint Key Laboratory of the Ministry of EducationInstitute of Applied Physics and Materials EngineeringUniversity of MacauAvenida da Universidade, TaipaMacau999078China
| | - Dazhe Zhao
- Department of Electromechanical EngineeringUniversity of MacauAvenida da Universidade, TaipaMacau999078China
| | - Yongyao Chen
- Research Center of Flexible Sensing Materials and DevicesSchool of Applied Physics and MaterialsWuyi UniversityJiangmen529020China
| | - Ziyi Dai
- Joint Key Laboratory of the Ministry of EducationInstitute of Applied Physics and Materials EngineeringUniversity of MacauAvenida da Universidade, TaipaMacau999078China
| | - Qian Zhao
- Joint Key Laboratory of the Ministry of EducationInstitute of Applied Physics and Materials EngineeringUniversity of MacauAvenida da Universidade, TaipaMacau999078China
| | - Yibo Gao
- Shenzhen Shineway Technology CorporationShenzhenGuangdong518000China
| | - Junwen Zhong
- Department of Electromechanical EngineeringUniversity of MacauAvenida da Universidade, TaipaMacau999078China
| | - Jianyi Luo
- Research Center of Flexible Sensing Materials and DevicesSchool of Applied Physics and MaterialsWuyi UniversityJiangmen529020China
| | - Bingpu Zhou
- Joint Key Laboratory of the Ministry of EducationInstitute of Applied Physics and Materials EngineeringUniversity of MacauAvenida da Universidade, TaipaMacau999078China
| |
Collapse
|
2
|
Shishvan OR, Abdelwahab A, da Rosa NB, Saulnier GJ, Mueller JL, Newell J, Isaacson D. ACT5 Electrical Impedance Tomography System. IEEE Trans Biomed Eng 2024; 71:227-236. [PMID: 37459258 PMCID: PMC10798853 DOI: 10.1109/tbme.2023.3295771] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2023]
Abstract
OBJECTIVE This article introduces the Adaptive Current Tomograph 5 (ACT5) Electrical Impedance Tomography (EIT) system. ACT5 is a 32 electrode applied-current multiple-source EIT system that can display real-time images of conductivity and susceptivity at 27 frames per second. The adaptive current sources in ACT5 can apply fully programmable current patterns with frequencies varying from 5 kHz to 500 kHz. The system also displays real-time ECG readings during the EIT imaging process. METHODS The hardware and software design and specifications are presented, including the current source design, FPGA hardware, safety features, calibration, and shunt impedance measurement. RESULTS Images of conductivity and susceptivity are presented from ACT5 data collected on tank phantoms and a human subject illustrating the system's ability to provide real-time images of pulsatile perfusion and ECG traces. SIGNIFICANCE The portability, high signal-to-noise ratio, and flexibility of applied currents over a wide range of frequencies enable this instrument to be used to obtain useful human subject data with relative clinical ease.
Collapse
|
3
|
Pessoa D, Rocha BM, Strodthoff C, Gomes M, Rodrigues G, Petmezas G, Cheimariotis GA, Kilintzis V, Kaimakamis E, Maglaveras N, Marques A, Frerichs I, Carvalho PD, Paiva RP. BRACETS: Bimodal repository of auscultation coupled with electrical impedance thoracic signals. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2023; 240:107720. [PMID: 37544061 DOI: 10.1016/j.cmpb.2023.107720] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 06/27/2023] [Accepted: 07/10/2023] [Indexed: 08/08/2023]
Abstract
BACKGROUND AND OBJECTIVE Respiratory diseases are among the most significant causes of morbidity and mortality worldwide, causing substantial strain on society and health systems. Over the last few decades, there has been increasing interest in the automatic analysis of respiratory sounds and electrical impedance tomography (EIT). Nevertheless, no publicly available databases with both respiratory sound and EIT data are available. METHODS In this work, we have assembled the first open-access bimodal database focusing on the differential diagnosis of respiratory diseases (BRACETS: Bimodal Repository of Auscultation Coupled with Electrical Impedance Thoracic Signals). It includes simultaneous recordings of single and multi-channel respiratory sounds and EIT. Furthermore, we have proposed several machine learning-based baseline systems for automatically classifying respiratory diseases in six distinct evaluation tasks using respiratory sound and EIT (A1, A2, A3, B1, B2, B3). These tasks included classifying respiratory diseases at sample and subject levels. The performance of the classification models was evaluated using a 5-fold cross-validation scheme (with subject isolation between folds). RESULTS The resulting database consists of 1097 respiratory sounds and 795 EIT recordings acquired from 78 adult subjects in two countries (Portugal and Greece). In the task of automatically classifying respiratory diseases, the baseline classification models have achieved the following average balanced accuracy: Task A1 - 77.9±13.1%; Task A2 - 51.6±9.7%; Task A3 - 38.6±13.1%; Task B1 - 90.0±22.4%; Task B2 - 61.4±11.8%; Task B3 - 50.8±10.6%. CONCLUSION The creation of this database and its public release will aid the research community in developing automated methodologies to assess and monitor respiratory function, and it might serve as a benchmark in the field of digital medicine for managing respiratory diseases. Moreover, it could pave the way for creating multi-modal robust approaches for that same purpose.
Collapse
Affiliation(s)
- Diogo Pessoa
- University of Coimbra Centre for Informatics and Systems of the University of Coimbra, Department of Informatics Engineering, 3030-290 Coimbra, Portugal.
| | - Bruno Machado Rocha
- University of Coimbra Centre for Informatics and Systems of the University of Coimbra, Department of Informatics Engineering, 3030-290 Coimbra, Portugal
| | - Claas Strodthoff
- Department of Anesthesiology, and Intensive Care Medicine, University Medical Center Schleswig-Holstein Campus Kiel, Kiel 24105, Schleswig-Holstein, Germany
| | - Maria Gomes
- Lab3R - Respiratory Research and Rehabilitation Laboratory, School of Health Sciences (ESSUA), University of Aveiro, 3810-193 Aveiro, Portugal
| | - Guilherme Rodrigues
- Lab3R - Respiratory Research and Rehabilitation Laboratory, School of Health Sciences (ESSUA), University of Aveiro, 3810-193 Aveiro, Portugal
| | - Georgios Petmezas
- 2nd Department of Obstetrics and Gynaecology, The Medical School, 54124 Thessaloniki, Greece
| | | | - Vassilis Kilintzis
- 2nd Department of Obstetrics and Gynaecology, The Medical School, 54124 Thessaloniki, Greece
| | - Evangelos Kaimakamis
- 1st Intensive Care Unit, "G. Papanikolaou" General Hospital of Thessaloniki, 57010 Pilea Hortiatis, Greece
| | - Nicos Maglaveras
- 2nd Department of Obstetrics and Gynaecology, The Medical School, 54124 Thessaloniki, Greece
| | - Alda Marques
- Lab3R - Respiratory Research and Rehabilitation Laboratory, School of Health Sciences (ESSUA), University of Aveiro, 3810-193 Aveiro, Portugal; Institute of Biomedicine (iBiMED), University of Aveiro, 3810-193 Aveiro, Portugal
| | - Inéz Frerichs
- Department of Anesthesiology, and Intensive Care Medicine, University Medical Center Schleswig-Holstein Campus Kiel, Kiel 24105, Schleswig-Holstein, Germany
| | - Paulo de Carvalho
- University of Coimbra Centre for Informatics and Systems of the University of Coimbra, Department of Informatics Engineering, 3030-290 Coimbra, Portugal
| | - Rui Pedro Paiva
- University of Coimbra Centre for Informatics and Systems of the University of Coimbra, Department of Informatics Engineering, 3030-290 Coimbra, Portugal
| |
Collapse
|
4
|
Pennati F, Angelucci A, Morelli L, Bardini S, Barzanti E, Cavallini F, Conelli A, Di Federico G, Paganelli C, Aliverti A. Electrical Impedance Tomography: From the Traditional Design to the Novel Frontier of Wearables. SENSORS (BASEL, SWITZERLAND) 2023; 23:1182. [PMID: 36772222 PMCID: PMC9921522 DOI: 10.3390/s23031182] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 01/16/2023] [Accepted: 01/17/2023] [Indexed: 06/18/2023]
Abstract
Electrical impedance tomography (EIT) is a medical imaging technique based on the injection of a current or voltage pattern through electrodes on the skin of the patient, and on the reconstruction of the internal conductivity distribution from the voltages collected by the electrodes. Compared to other imaging techniques, EIT shows significant advantages: it does not use ionizing radiation, is non-invasive and is characterized by high temporal resolution. Moreover, its low cost and high portability make it suitable for real-time, bedside monitoring. However, EIT is also characterized by some technical limitations that cause poor spatial resolution. The possibility to design wearable devices based on EIT has recently given a boost to this technology. In this paper we reviewed EIT physical principles, hardware design and major clinical applications, from the classical to a wearable setup. A wireless and wearable EIT system seems a promising frontier of this technology, as it can both facilitate making clinical measurements and open novel scenarios to EIT systems, such as home monitoring.
Collapse
Affiliation(s)
| | - Alessandra Angelucci
- Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milan, Italy
| | | | | | | | | | | | | | | | | |
Collapse
|
5
|
Showkat I, Khanday FA, Beigh MR. A review of bio-impedance devices. Med Biol Eng Comput 2023; 61:927-950. [PMID: 36637716 DOI: 10.1007/s11517-022-02763-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 12/27/2022] [Indexed: 01/14/2023]
Abstract
Bio-impedance measurement analysis primarily refers to a safe and a non-invasive technique to analyze the electrical changes in living tissues on the application of low-value alternating current. It finds applications both in the biomedical and the agricultural fields. This paper concisely reviews the origin and measurement approaches for concepts and fundamentals of bio-impedance followed by a critical review on bio-impedance portable devices with main emphasis on the embedded system approach which is in demand due to its miniature size and present lifestyle preference of monitoring health in real time. The paper also provides a comprehensive review of various bio-impedance circuits with emphasis on the measurement and calibration techniques.
Collapse
Affiliation(s)
- Insha Showkat
- Department of Electronics and Instrumentation Technology, University of Kashmir, Hazratbal, Srinagar, Jammu and Kashmir, India
| | - Farooq A Khanday
- Department of Electronics and Instrumentation Technology, University of Kashmir, Hazratbal, Srinagar, Jammu and Kashmir, India.
| | - M Rafiq Beigh
- Department of Electronics, Govt. Degree College Sumbal, Sumbal, J&K, India
| |
Collapse
|
6
|
Braun F, Bonnier G, Rapin M, Yilmaz G, Proust YM, Schneider S, Radan AP, Strahm KM, Surbek D, Lemay M, Delgado-Gonzalo R. Evaluation of a Wearable System for Fetal ECG Monitoring Using Cooperative Sensors. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2022; 2022:3131-3134. [PMID: 36085640 DOI: 10.1109/embc48229.2022.9871458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Fetal electrocardiography (fECG) has gotten widespread interest in the last years as technology for fetal monitoring. Compared to cardiotocography (CTG), the current state of the art, it can be designed in smaller formfactor and is thus suited for long-term and unsupervised monitoring. In the present study we evaluated a wearable system which is based on CSEM's cooperative sensors, a versatile technology that allows for the measurement of multiple biosignals and an easy integration into a garment or patch. The system was tested on 25 patients with singleton pregnancies and an age of gestation ≥ 37 weeks. To reject unreliable fetal heart rate (fHR) estimations, the signal processing algorithm provides a signal quality index. In 12 out of 21 patients available for analysis, a good performance of fHR estimations was obtained with a mean absolute error < 5 bpm and an acceptance rate >70%. However, the remaining 9 patients showed low acceptance rates and high errors. Besides investigating the source of these high errors, future work includes the investigating improved signal processing algorithms, different body positions and the use of dry electrodes. Clinical Relevance - The aim of this work is to develop a wearable system that can be offered in hospitals as an alternative to cardiotocography, or as a home monitoring tool for at risk fetuses, in the era of evolving telemedicine.
Collapse
|
7
|
He J, Li Y, Zhang X, Li J. Missing and Corrupted Data Recovery in Wireless Sensor Networks Based on Weighted Robust Principal Component Analysis. SENSORS 2022; 22:s22051992. [PMID: 35271138 PMCID: PMC8914969 DOI: 10.3390/s22051992] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 02/27/2022] [Accepted: 03/01/2022] [Indexed: 11/16/2022]
Abstract
Although wireless sensor networks (WSNs) have been widely used, the existence of data loss and corruption caused by poor network conditions, sensor bandwidth, and node failure during transmission greatly affects the credibility of monitoring data. To solve this problem, this paper proposes a weighted robust principal component analysis method to recover the corrupted and missing data in WSNs. By decomposing the original data into a low-rank normal data matrix and a sparse abnormal matrix, the proposed method can identify the abnormal data and avoid the influence of corruption on the reconstruction of normal data. In addition, the low-rankness is constrained by weighted nuclear norm minimization instead of the nuclear norm minimization to preserve the major data components and ensure credible reconstruction data. An alternating direction method of multipliers algorithm is further developed to solve the resultant optimization problem. Experimental results demonstrate that the proposed method outperforms many state-of-the-art methods in terms of recovery accuracy in real WSNs.
Collapse
|
8
|
Frerichs I, Lasarow L, Strodthoff C, Vogt B, Zhao Z, Weiler N. Spatial Ventilation Inhomogeneity Determined by Electrical Impedance Tomography in Patients With Chronic Obstructive Lung Disease. Front Physiol 2021; 12:762791. [PMID: 34966289 PMCID: PMC8712108 DOI: 10.3389/fphys.2021.762791] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2021] [Accepted: 11/16/2021] [Indexed: 11/13/2022] Open
Abstract
The aim of this study was to examine whether electrical impedance tomography (EIT) could determine the presence of ventilation inhomogeneity in patients with chronic obstructive lung disease (COPD) from measurements carried out not only during conventional forced full expiration maneuvers but also from forced inspiration maneuvers and quiet tidal breathing and whether the inhomogeneity levels were comparable among the phases and higher than in healthy subjects. EIT data were acquired in 52 patients with exacerbated COPD (11 women, 41 men, 68 ± 11 years) and 14 healthy subjects (6 women, 8 men, 38 ± 8 years). Regional lung function parameters of forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1), forced inspiratory vital capacity (FIVC), forced inspiratory volume in 1 s (FIV1), and tidal volume (V T ) were determined in 912 image pixels. The spatial inhomogeneity of the pixel parameters was characterized by the coefficients of variation (CV) and the global inhomogeneity (GI) index. CV and GI values of pixel FVC, FEV1, FIVC, FIV1, and VT were significantly higher in patients than in healthy subjects (p ≤ 0.0001). The ventilation distribution was affected by the analyzed lung function parameter in patients (CV: p = 0.0024, GI: p = 0.006) but not in healthy subjects. Receiver operating characteristic curves showed that CV and GI discriminated patients from healthy subjects with an area under the curve (AUC) of 0.835 and 0.852 (FVC), 0.845 and 0.867 (FEV1), 0.903 and 0.903 (FIVC), 0.891 and 0.882 (FIV1), and 0.821 and 0.843 (VT), respectively. These findings confirm the ability of EIT to identify increased ventilation inhomogeneity in patients with COPD.
Collapse
Affiliation(s)
- Inéz Frerichs
- Department of Anesthesiology and Intensive Care Medicine, University Medical Center Schleswig-Holstein, Kiel, Germany
| | - Livia Lasarow
- Department of Anesthesiology and Intensive Care Medicine, University Medical Center Schleswig-Holstein, Kiel, Germany
| | - Claas Strodthoff
- Department of Anesthesiology and Intensive Care Medicine, University Medical Center Schleswig-Holstein, Kiel, Germany
| | - Barbara Vogt
- Department of Anesthesiology and Intensive Care Medicine, University Medical Center Schleswig-Holstein, Kiel, Germany
| | - Zhanqi Zhao
- Department of Biomedical Engineering, Fourth Military Medical University, Xi'an, China.,Institute of Technical Medicine, Furtwangen University, Villingen-Schwenningen, Germany
| | - Norbert Weiler
- Department of Anesthesiology and Intensive Care Medicine, University Medical Center Schleswig-Holstein, Kiel, Germany
| |
Collapse
|
9
|
Mobile 5P-Medicine Approach for Cardiovascular Patients. SENSORS 2021; 21:s21216986. [PMID: 34770292 PMCID: PMC8587644 DOI: 10.3390/s21216986] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Revised: 10/16/2021] [Accepted: 10/18/2021] [Indexed: 12/13/2022]
Abstract
Medicine is heading towards personalized care based on individual situations and conditions. With smartphones and increasingly miniaturized wearable devices, the sensors available on these devices can perform long-term continuous monitoring of several user health-related parameters, making them a powerful tool for a new medicine approach for these patients. Our proposed system, described in this article, aims to develop innovative solutions based on artificial intelligence techniques to empower patients with cardiovascular disease. These solutions will realize a novel 5P (Predictive, Preventive, Participatory, Personalized, and Precision) medicine approach by providing patients with personalized plans for treatment and increasing their ability for self-monitoring. Such capabilities will be derived by learning algorithms from physiological data and behavioral information, collected using wearables and smart devices worn by patients with health conditions. Further, developing an innovative system of smart algorithms will also focus on providing monitoring techniques, predicting extreme events, generating alarms with varying health parameters, and offering opportunities to maintain active engagement of patients in the healthcare process by promoting the adoption of healthy behaviors and well-being outcomes. The multiple features of this future system will increase the quality of life for cardiovascular diseases patients and provide seamless contact with a healthcare professional.
Collapse
|
10
|
Haris K, Vogt B, Strodthoff C, Pessoa D, Cheimariotis GA, Rocha B, Petmezas G, Weiler N, Paiva RP, de Carvalho P, Maglaveras N, Frerichs I. Identification and analysis of stable breathing periods in electrical impedance tomography recordings. Physiol Meas 2021; 42. [PMID: 34098533 DOI: 10.1088/1361-6579/ac08e5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 06/07/2021] [Indexed: 11/11/2022]
Abstract
Objective. In this paper, an automated stable tidal breathing period (STBP) identification method based on processing electrical impedance tomography (EIT) waveforms is proposed and the possibility of detecting and identifying such periods using EIT waveforms is analyzed. In wearable chest EIT, patients breathe spontaneously, and therefore, their breathing pattern might not be stable. Since most of the EIT feature extraction methods are applied to STBPs, this renders their automatic identification of central importance.Approach. The EIT frame sequence is reconstructed from the raw EIT recordings and the raw global impedance waveform (GIW) is computed. Next, the respiratory component of the raw GIW is extracted and processed for the automatic respiratory cycle (breath) extraction and their subsequent grouping into STBPs.Main results. We suggest three criteria for the identification of STBPs, namely, the coefficient of variation of (i) breath tidal volume, (ii) breath duration and (iii) end-expiratory impedance. The total number of true STBPs identified by the proposed method was 294 out of 318 identified by the expert corresponding to accuracy over 90%. Specific activities such as speaking, eating and arm elevation are identified as sources of false positives and their discrimination is discussed.Significance. Simple and computationally efficient STBP detection and identification is a highly desirable component in the EIT processing pipeline. Our study implies that it is feasible, however, the determination of its limits is necessary in order to consider the implementation of more advanced and computationally demanding approaches such as deep learning and fusion with data from other wearable sensors such as accelerometers and microphones.
Collapse
Affiliation(s)
- K Haris
- Lab of Computing, Medical Informatics and Biomedical Imaging Technologies, Aristotle University, Thessaloniki, Greece.,Department of Informatics and Computer Engineering, University of West Attica, Greece
| | - B Vogt
- Department of Anaesthesiology and Intensive Care Medicine, University Medical Centre Schleswig-Holstein, Campus Kiel, Germany
| | - C Strodthoff
- Department of Anaesthesiology and Intensive Care Medicine, University Medical Centre Schleswig-Holstein, Campus Kiel, Germany
| | - D Pessoa
- University of Coimbra, Centre for Informatics and Systems of the University of Coimbra, Department of Informatics Engineering, 3030-290 Coimbra, Portugal
| | - G-A Cheimariotis
- Lab of Computing, Medical Informatics and Biomedical Imaging Technologies, Aristotle University, Thessaloniki, Greece
| | - B Rocha
- University of Coimbra, Centre for Informatics and Systems of the University of Coimbra, Department of Informatics Engineering, 3030-290 Coimbra, Portugal
| | - G Petmezas
- Lab of Computing, Medical Informatics and Biomedical Imaging Technologies, Aristotle University, Thessaloniki, Greece
| | - N Weiler
- Department of Anaesthesiology and Intensive Care Medicine, University Medical Centre Schleswig-Holstein, Campus Kiel, Germany
| | - R P Paiva
- University of Coimbra, Centre for Informatics and Systems of the University of Coimbra, Department of Informatics Engineering, 3030-290 Coimbra, Portugal
| | - P de Carvalho
- University of Coimbra, Centre for Informatics and Systems of the University of Coimbra, Department of Informatics Engineering, 3030-290 Coimbra, Portugal
| | - N Maglaveras
- Lab of Computing, Medical Informatics and Biomedical Imaging Technologies, Aristotle University, Thessaloniki, Greece.,Department of Electrical and Computer Engineering, Northwestern University, Evanston, IL, United States of America
| | - I Frerichs
- Department of Anaesthesiology and Intensive Care Medicine, University Medical Centre Schleswig-Holstein, Campus Kiel, Germany
| |
Collapse
|
11
|
Groenendaal W, Lee S, van Hoof C. Wearable Bioimpedance Monitoring: Viewpoint for Application in Chronic Conditions. JMIR BIOMEDICAL ENGINEERING 2021; 6:e22911. [PMID: 38907374 PMCID: PMC11041432 DOI: 10.2196/22911] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 03/01/2021] [Accepted: 04/06/2021] [Indexed: 01/20/2023] Open
Abstract
Currently, nearly 6 in 10 US adults are suffering from at least one chronic condition. Wearable technology could help in controlling the health care costs by remote monitoring and early detection of disease worsening. However, in recent years, there have been disappointments in wearable technology with respect to reliability, lack of feedback, or lack of user comfort. One of the promising sensor techniques for wearable monitoring of chronic disease is bioimpedance, which is a noninvasive, versatile sensing method that can be applied in different ways to extract a wide range of health care parameters. Due to the changes in impedance caused by either breathing or blood flow, time-varying signals such as respiration and cardiac output can be obtained with bioimpedance. A second application area is related to body composition and fluid status (eg, pulmonary congestion monitoring in patients with heart failure). Finally, bioimpedance can be used for continuous and real-time imaging (eg, during mechanical ventilation). In this viewpoint, we evaluate the use of wearable bioimpedance monitoring for application in chronic conditions, focusing on the current status, recent improvements, and challenges that still need to be tackled.
Collapse
Affiliation(s)
| | - Seulki Lee
- Imec the Netherlands / Holst Centre, Eindhoven, Netherlands
| | - Chris van Hoof
- Imec, Leuven, Belgium
- One Planet Research Center, Wageningen, Netherlands
- Department of Engineering Science, KU Leuven, Leuven, Belgium
| |
Collapse
|
12
|
Electrical Tomography Reconstruction Using Reconfigurable Waveforms in a FPGA. SENSORS 2021; 21:s21093272. [PMID: 34068457 PMCID: PMC8125997 DOI: 10.3390/s21093272] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 04/24/2021] [Accepted: 04/28/2021] [Indexed: 11/16/2022]
Abstract
The principal objective of this research is to conceive a mobile system based on electrical tomography for subsurface imaging and monitoring in order to enable simultaneous recording of electrical potentials of cardiac and pulmonary activity. For an exploration of excitation waveforms in electrical tomography, specialized hardware is required. As the main principle of tomography is the measurement of electrical perturbations on an unknown object, it is crucial to synchronize excitation and sensing processes in a very precise way for the purpose of acquiring meaningful data. To cope with this problem, an FPGA device is used, with an architecture that allows us to trigger excitation signals and to read sensed data simultaneously via independent processes that share the same clock. In this way, waveform reconfiguration on frequency and shape can be provided and studied. The system is connected to a standard microcontroller SoC with a simple API that allows for IoT capabilities for on-line operation and tracking, given that the design is targeted for in vivo medical monitoring. As a result of the research work, a measuring device was developed, the surface data analyzed and the image was reconstructed using the selected configuration.
Collapse
|
13
|
Shi Y, Wu Y, Wang M, Tian Z, Kong X, He X. Sparse image reconstruction of intracerebral hemorrhage with electrical impedance tomography. J Med Imaging (Bellingham) 2021; 8:014501. [PMID: 33457443 DOI: 10.1117/1.jmi.8.1.014501] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Accepted: 12/22/2020] [Indexed: 12/12/2022] Open
Abstract
Purpose: Intracerebral hemorrhage (ICH) is a common disease that is known for its high morbidity, high mortality, and high disability. The fast and accurate detection of ICH is essential for the acute care of patients. Electrical impedance tomography (EIT) offers an alternative with which pathological tissues can be detected by reconstructing conductivity variation. Nevertheless, the sensitive field of EIT is greatly affected by medium distribution, which is referred to as soft-field effect. In addition, the image reconstruction is a severely ill-posed inverse problem. Furthermore, due to the low conductivity of skull, the sensitivity in the sensing area is extremely low. Therefore, the reconstruction of ICH with EIT is great challenge. Approach: A sparse image reconstruction method is proposed for EIT to visualize the conductivity variation caused by ICH. To reduce the impact of soft-field effect, the normalization of sensitivity distribution is conducted for monolayer and three-layer head model. In addition, a constrained sparse L 1 -norm minimization model is developed for the image reconstruction. Augmented Lagrangian multiplier method and alternating minimization scheme are adopted to solve the proposed model. Results: The results show that the sensitivity in the sensing area is largely enhanced. Numerical simulation based on monolayer head model and three-layer head model is respectively carried out. Both the reconstructed images and the quantitative evaluations show that image reconstructed by the proposed method is much better than that reconstructed by traditional Tikhonov method. The reconstructions evaluated under the impact of noise also show that the proposed method has superior anti-noise performance. Conclusions: With the proposed method, the quality of the reconstructed image would be greatly improved. It is an effective approach for imaging ICH with EIT technique.
Collapse
Affiliation(s)
- Yanyan Shi
- Henan Normal University, Department of Electronic and Electrical Engineering, Xinxiang, China.,Fourth Military Medical University, College of Biomedical Engineering, Xi'an, China
| | - Yuehui Wu
- Henan Normal University, Department of Electronic and Electrical Engineering, Xinxiang, China
| | - Meng Wang
- Henan Normal University, Department of Electronic and Electrical Engineering, Xinxiang, China
| | - Zhiwei Tian
- Henan Normal University, Department of Electronic and Electrical Engineering, Xinxiang, China
| | - Xiaolong Kong
- Henan Normal University, Department of Electronic and Electrical Engineering, Xinxiang, China
| | - Xiaoyue He
- Henan Normal University, Department of Electronic and Electrical Engineering, Xinxiang, China
| |
Collapse
|
14
|
Development of a Portable, Reliable and Low-Cost Electrical Impedance Tomography System Using an Embedded System. ELECTRONICS 2020. [DOI: 10.3390/electronics10010015] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Electrical impedance tomography (EIT) is a useful procedure with applications in industry and medicine, particularly in the lungs and brain area. In this paper, the development of a portable, reliable and low-cost EIT system for image reconstruction by using an embedded system (ES) is introduced herein. The novelty of this article is the hardware development of a complete low-cost EIT system, as well as three simple and efficient algorithms that can be implemented on ES. The proposed EIT system applies the adjacent voltage method, starting with an impedance acquisition stage that sends data to a Raspberry Pi 4 (RPi4) as ES. To perform the image reconstruction, a user interface was developed by using GNU Octave for RPi4 and the EIDORS library. A statistical analysis is performed to determine the best average value from the samples measured by using an analog-to-digital converter (ADC) with a capacity of 30 kSPS and 24-bit resolution. The tests for the proposed EIT system were performed using materials such as metal, glass and an orange to simulate its application in food industry. Experimental results show that the statistical median is more accurate with respect to the real voltage measurement; however, it represents a higher computational cost. Therefore, the mean is calculated and improved by discarding data values in a transitory state, achieving better accuracy than the median to determine the real voltage value, enhancing the quality of the reconstructed images. A performance comparison between a personal computer (PC) and RPi4 is presented. The proposed EIT system offers an excellent cost-benefit ratio with respect to a traditional PC, taking into account precision, accuracy, energy consumption, price, light weight, size, portability and reliability. The proposed EIT system has potential application in mechanical ventilation, food industry and structural health monitoring.
Collapse
|
15
|
Yilmaz G, Rapin M, Pessoa D, Rocha BM, de Sousa AM, Rusconi R, Carvalho P, Wacker J, Paiva RP, Chételat O. A Wearable Stethoscope for Long-Term Ambulatory Respiratory Health Monitoring. SENSORS (BASEL, SWITZERLAND) 2020; 20:E5124. [PMID: 32911861 PMCID: PMC7571051 DOI: 10.3390/s20185124] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/02/2020] [Revised: 08/30/2020] [Accepted: 09/05/2020] [Indexed: 01/04/2023]
Abstract
Lung sounds acquired by stethoscopes are extensively used in diagnosing and differentiating respiratory diseases. Although an extensive know-how has been built to interpret these sounds and identify diseases associated with certain patterns, its effective use is limited to individual experience of practitioners. This user-dependency manifests itself as a factor impeding the digital transformation of this valuable diagnostic tool, which can improve patient outcomes by continuous long-term respiratory monitoring under real-life conditions. Particularly patients suffering from respiratory diseases with progressive nature, such as chronic obstructive pulmonary diseases, are expected to benefit from long-term monitoring. Recently, the COVID-19 pandemic has also shown the lack of respiratory monitoring systems which are ready to deploy in operational conditions while requiring minimal patient education. To address particularly the latter subject, in this article, we present a sound acquisition module which can be integrated into a dedicated garment; thus, minimizing the role of the patient for positioning the stethoscope and applying the appropriate pressure. We have implemented a diaphragm-less acousto-electric transducer by stacking a silicone rubber and a piezoelectric film to capture thoracic sounds with minimum attenuation. Furthermore, we benchmarked our device with an electronic stethoscope widely used in clinical practice to quantify its performance.
Collapse
Affiliation(s)
- Gürkan Yilmaz
- Swiss Center for Electronics and Microtechnology (CSEM), 2002 Neuchâtel, Switzerland; (M.R.); (A.M.d.S.); (R.R.); (J.W.); (O.C.)
| | - Michaël Rapin
- Swiss Center for Electronics and Microtechnology (CSEM), 2002 Neuchâtel, Switzerland; (M.R.); (A.M.d.S.); (R.R.); (J.W.); (O.C.)
| | - Diogo Pessoa
- University of Coimbra, Centre for Informatics and Systems of the University of Coimbra, Department of Informatics Engineering, 3030-290 Coimbra, Portugal; (D.P.); (B.M.R.); (P.C.); (R.P.P.)
| | - Bruno M. Rocha
- University of Coimbra, Centre for Informatics and Systems of the University of Coimbra, Department of Informatics Engineering, 3030-290 Coimbra, Portugal; (D.P.); (B.M.R.); (P.C.); (R.P.P.)
| | - Antonio Moreira de Sousa
- Swiss Center for Electronics and Microtechnology (CSEM), 2002 Neuchâtel, Switzerland; (M.R.); (A.M.d.S.); (R.R.); (J.W.); (O.C.)
| | - Roberto Rusconi
- Swiss Center for Electronics and Microtechnology (CSEM), 2002 Neuchâtel, Switzerland; (M.R.); (A.M.d.S.); (R.R.); (J.W.); (O.C.)
| | - Paulo Carvalho
- University of Coimbra, Centre for Informatics and Systems of the University of Coimbra, Department of Informatics Engineering, 3030-290 Coimbra, Portugal; (D.P.); (B.M.R.); (P.C.); (R.P.P.)
| | - Josias Wacker
- Swiss Center for Electronics and Microtechnology (CSEM), 2002 Neuchâtel, Switzerland; (M.R.); (A.M.d.S.); (R.R.); (J.W.); (O.C.)
| | - Rui Pedro Paiva
- University of Coimbra, Centre for Informatics and Systems of the University of Coimbra, Department of Informatics Engineering, 3030-290 Coimbra, Portugal; (D.P.); (B.M.R.); (P.C.); (R.P.P.)
| | - Olivier Chételat
- Swiss Center for Electronics and Microtechnology (CSEM), 2002 Neuchâtel, Switzerland; (M.R.); (A.M.d.S.); (R.R.); (J.W.); (O.C.)
| |
Collapse
|
16
|
Munir B, Murphy EK, Mallick A, Gutierrez H, Zhang F, Verga S, Smith C, Levy S, McIlduff C, Sarbesh P, Halter RJ, Rutkove SB. A robust and novel electrical impedance metric of pulmonary function in ALS patients. Physiol Meas 2020; 41:044005. [PMID: 32240997 DOI: 10.1088/1361-6579/ab85cf] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
OBJECTIVE Pulmonary function tests (PFTs) are important for assessing respiratory function in amyotrophic lateral sclerosis (ALS) patients. However, weakness of oral and glottal closure, due to concomitant bulbar dysfunction, may result in unreliable PFT values stemming from leakage of air around the breathing tube and through the glottis. In this study, we assessed whether standard thoracic electrical impedance tomography (EIT) could serve as a surrogate measure for PFTs. APPROACH Thoracic EIT was performed simultaneously with standard PFTs on seven ALS patients without clinical bulbar weakness (six men and one woman, mean age of 63 years) and ten healthy volunteers (seven men and three women, mean age of 57 years). A raw impedance metric along with more standard EIT measures were computed and correlated with the normalized forced vital capacity (FVC). Additionally, test/re-test metrics and EIT images were analyzed. MAIN RESULTS The impedance metric was found to be robust and sensitive to lung activity. We also identified qualitative EIT differences between healthy volunteers and ALS patients, with the ALS images showing greater heterogeneity. Significant correlations with FVC were found for both impedance and EIT metrics in ALS patients (r2 = 0.89) and for the impedance metric only in healthy volunteers (r2 = 0.49). SIGNIFICANCE This suggests that EIT, using our novel impedance metric, has the potential to serve as an alternative technology to standard PFTs for assessing pulmonary function in patients with ALS, offering new metrics of disease status for those with bulbar weakness.
Collapse
Affiliation(s)
- Badria Munir
- Department of Neurology, Beth Israel Deaconess Medical Center (BIDMC), Boston, MA 02215, United States of America. Harvard Medical School, Boston, MA 02115, United States of America
| | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
17
|
Frerichs I, Vogt B, Wacker J, Paradiso R, Braun F, Rapin M, Caldani L, Chételat O, Weiler N. Multimodal remote chest monitoring system with wearable sensors: a validation study in healthy subjects. Physiol Meas 2020; 41:015006. [DOI: 10.1088/1361-6579/ab668f] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
|
18
|
Wu Y, Jiang D, Bardill A, Bayford R, Demosthenous A. A 122 fps, 1 MHz Bandwidth Multi-Frequency Wearable EIT Belt Featuring Novel Active Electrode Architecture for Neonatal Thorax Vital Sign Monitoring. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2019; 13:927-937. [PMID: 31283510 DOI: 10.1109/tbcas.2019.2925713] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
A highly integrated, wearable electrical impedance tomography (EIT) belt for neonatal thorax vital multiple sign monitoring is presented. The belt has 16 active electrodes. Each electrode has an application-specific integrated circuit (ASIC) connected to it. The ASIC contains a fully differential current driver, a high-performance instrumentation amplifier, a digital controller, and multiplexors. The belt features a new active electrode architecture that allows programmable flexible electrode current drive and voltage sense patterns under simple digital control. It provides intimate connections to the electrodes for the current drive and to the IA for direct differential voltage measurement, providing superior common-mode rejection ratio. The ASIC was designed in a CMOS 0.35-μm high-voltage technology. The high-specification EIT belt has an image frame rate of 122 fps, a wide operating bandwidth of 1 MHz, and multi-frequency operation. It measures impedance with 98% accuracy and has less than 0.5 Ω and 1° variation across all possible channels. The image results confirmed the advantage of the new active electrode architecture and the benefit of wideband, multi-frequency EIT operation. The system successfully captured high-quality lung-respiration EIT images, breathing cycle, and heart rate. It can also provide boundary-shape information by using an array of MEMS sensors interfaced to the ASICs.
Collapse
|
19
|
Vogt B, Deuß K, Hennig V, Zhao Z, Lautenschläger I, Weiler N, Frerichs I. Regional lung function in nonsmokers and asymptomatic current and former smokers. ERJ Open Res 2019; 5:00240-2018. [PMID: 31321224 PMCID: PMC6628636 DOI: 10.1183/23120541.00240-2018] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Accepted: 05/01/2019] [Indexed: 11/05/2022] Open
Abstract
Electrical impedance tomography (EIT) is able to detect rapid lung volume changes during breathing. The aim of our observational study was to characterise the heterogeneity of regional ventilation distribution in lung-healthy adults by EIT and to detect the possible impact of tobacco consumption. A total of 219 nonsmokers, asymptomatic ex-smokers and current smokers were examined during forced full expiration using EIT. Forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC) and FEV1/FVC were determined in 836 EIT image pixels for the analysis of spatial and temporal ventilation distribution. Coefficients of variation (CVs) of these pixel values were calculated. Histograms and medians of FEV1/FVCEIT and times required to exhale 50%, 75%, 90% of FVCEIT (t50, t75 and t90) were generated. CV of FEV1/FVCEIT distinguished among all groups (mean±sd: nonsmokers 0.43±0.05, ex-smokers 0.52±0.09, smokers 0.62±0.16). Histograms of FEV1/FVCEIT differentiated between nonsmokers and the other groups (p<0.0001). Medians of t50, t75 and t90 showed the lowest values in nonsmokers. Median t90 separated all groups (median (interquartile range): nonsmokers 0.82 (0.67-1.15), ex-smokers 1.41 (1.03-2.21), smokers 1.91 (1.33-3.53)). EIT detects regional ventilation heterogeneity during forced expiration in healthy nonsmokers and its increase in asymptomatic former and current smokers. Therefore, EIT-derived reference values should only be collected from nonsmoking lung-healthy adults.
Collapse
Affiliation(s)
- Barbara Vogt
- Dept of Anesthesiology and Intensive Care Medicine, University Medical Center Schleswig-Holstein, Campus Kiel, Kiel, Germany
| | - Kathinka Deuß
- Dept of Anesthesiology and Intensive Care Medicine, University Medical Center Schleswig-Holstein, Campus Kiel, Kiel, Germany
| | - Victoria Hennig
- Dept of Anesthesiology and Intensive Care Medicine, University Medical Center Schleswig-Holstein, Campus Kiel, Kiel, Germany
| | - Zhanqi Zhao
- Dept of Biomedical Engineering, Fourth Military Medical University, Xi'an, China.,Dept of Biomedical Engineering, Furtwangen University, Villingen-Schwenningen, Germany
| | - Ingmar Lautenschläger
- Dept of Anesthesiology and Intensive Care Medicine, University Medical Center Schleswig-Holstein, Campus Kiel, Kiel, Germany
| | - Norbert Weiler
- Dept of Anesthesiology and Intensive Care Medicine, University Medical Center Schleswig-Holstein, Campus Kiel, Kiel, Germany
| | - Inéz Frerichs
- Dept of Anesthesiology and Intensive Care Medicine, University Medical Center Schleswig-Holstein, Campus Kiel, Kiel, Germany
| |
Collapse
|