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Publications (10 of 121) Show all publications
Eyre, S., Stenberg, J., Wallengren, O., Keane, D., Avesani, C. M., Bosaeus, I., . . . Trondsen, M. (2023). Bioimpedance analysis in patients with chronic kidney disease. Journal of Renal Care, 49(3), 147-157
Open this publication in new window or tab >>Bioimpedance analysis in patients with chronic kidney disease
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2023 (English)In: Journal of Renal Care, ISSN 1755-6678, E-ISSN 1755-6686, Vol. 49, no 3, p. 147-157Article in journal, Editorial material (Other academic) Published
Abstract [en]

In recent years the use of bioimpedance analysis (BIA) for assessment of fluid status as well as body composition as a mean to assess nutritional status in CKD has increased. The interest in the method is due to the associations between fluid overload and cardiovascular disease, and between fluid overload and malnutrition, both of which contribute to an increased risk of morbidity and mortality (Hur et al., 2013; Onofriescu et al., 2014). Moreover, BIA devices are suitable for clinical use, since they are portable, easy to use and, with a median to low price. However, the results can be difficult to interpret and integrate into routine clinical care, and although impedance measurements can contribute to an increased understanding of the patient's fluid balance, the results should be used with caution and in combination with other physiological parameters and clinical assessments (de Ruiter et al., 2020; Scotland et al., 2018). The aim of this editorial is to contribute to increased awareness of the benefits and limitations of using bioimpedance in patients with CKD with or without dialysis, and contribute to improving the measurement quality, facilitating interpretations, and highlighting possible sources of error.

National Category
Urology and Nephrology
Identifiers
urn:nbn:se:hb:diva-30334 (URN)10.1111/jorc.12474 (DOI)001038006500001 ()2-s2.0-85165873361 (Scopus ID)
Available from: 2023-08-15 Created: 2023-08-15 Last updated: 2024-02-01Bibliographically approved
Fernandez-Llatas, C., Gatta, R., Seoane, F. & Valentini, V. (2023). Editorial: Artificial intelligence in process modelling in oncology. Frontiers in Oncology, 13
Open this publication in new window or tab >>Editorial: Artificial intelligence in process modelling in oncology
2023 (English)In: Frontiers in Oncology, E-ISSN 2234-943X, Vol. 13Article in journal, Editorial material (Other academic) Published
National Category
Cancer and Oncology
Identifiers
urn:nbn:se:hb:diva-31328 (URN)10.3389/fonc.2023.1298446 (DOI)001133539300001 ()2-s2.0-85180885492 (Scopus ID)
Available from: 2024-01-16 Created: 2024-01-16 Last updated: 2024-02-01
Seoane, F., Yang, L., Dai, M. & Zhao, Z. (2023). Multidimensional physiology: novel techniques and discoveries with bioimpedance measurements. Frontiers in Physiology, 14, Article ID 1243850.
Open this publication in new window or tab >>Multidimensional physiology: novel techniques and discoveries with bioimpedance measurements
2023 (English)In: Frontiers in Physiology, E-ISSN 1664-042X, Vol. 14, article id 1243850Article in journal, Editorial material (Refereed) Published
Place, publisher, year, edition, pages
Frontiers Media SA, 2023
Keywords
bioelectrical impedance analysis, bioimpedance measurements, clinical applications of bioimpedance, electrical impedance tomography, impedance cardiography, clinical practice, computer assisted impedance tomography, Editorial, human, measurement, physiology
National Category
Medical Laboratory and Measurements Technologies
Identifiers
urn:nbn:se:hb:diva-30319 (URN)10.3389/fphys.2023.1243850 (DOI)001029392600001 ()2-s2.0-85164982090 (Scopus ID)
Available from: 2023-08-14 Created: 2023-08-14 Last updated: 2024-02-01Bibliographically approved
Simic, M., Freeborn, T. J., Veletic, M., Seoane, F. & Stojanovic, G. M. (2023). Parameter Estimation of the Single-Dispersion Fractional Cole-Impedance Model With the Embedded Hardware. IEEE Sensors Journal, 23(12), 12978-12987
Open this publication in new window or tab >>Parameter Estimation of the Single-Dispersion Fractional Cole-Impedance Model With the Embedded Hardware
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2023 (English)In: IEEE Sensors Journal, ISSN 1530-437X, E-ISSN 1558-1748, Vol. 23, no 12, p. 12978-12987Article in journal (Refereed) Published
Abstract [en]

Bioimpedance modeling with equivalent electrical circuits has an important role in various biomedical applications, as it facilitates understanding of underlying physical and electrochemical processes in applications such as body composition measurements and assessment of clinical conditions. However, the estimation of model parameter values is not a straightforward task, especially when complex circuits with fractional-order components [e.g., constant phase elements (CPEs)] are used. In this article, we propose a low-complexity method for parameter estimation of the Cole-impedance model suitable for low-cost embedded hardware (e.g., 8-bit microcontrollers). Our approach uses only the measured real and imaginary impedance, without any specific software package/toolbox, or initial values provided by the user. The proposed method was validated with synthetic (noiseless and noisy) data and experimental right-side, hand-to-foot bioimpedance data from a healthy adult participant. Moreover, the proposed method was compared in terms of accuracy with the recently published relevant work and commercial Electrical Impedance Spectroscopy software (Bioimp 2.3.4). The performance evaluation in terms of complexity (suitable for deployment for the microcontroller-based platform with 256 kB of RAM and 16 MHz clock speed), execution time (18 s for the dataset with 256 points), and cost (< 25) confirms the proposed method in regards to reliable bioimpedance processing using embedded hardware. 

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023
Keywords
Bioimpedance, Cole equation, equivalent circuits, estimation, fractional-order circuits, Biochemistry, Medical applications, Microcontrollers, Parameter estimation, Timing circuits, Bio-impedance, Biomedical applications, Electrochemical process, Embedded hardware, Equivalent electrical circuits, Fractional-order circuit, Impedance modeling, Parameters estimation, Physical process
National Category
Medical Laboratory and Measurements Technologies
Identifiers
urn:nbn:se:hb:diva-30268 (URN)10.1109/JSEN.2023.3269952 (DOI)001014626700062 ()2-s2.0-85159726029 (Scopus ID)
Available from: 2023-08-15 Created: 2023-08-15 Last updated: 2024-02-01Bibliographically approved
Chen, K., Abtahi, F., Carrero, J.-J., Fernandez-Llatas, C. & Seoane, F. (2023). Process mining and data mining applications in the domain of chronic diseases: A systematic review. Artificial Intelligence in Medicine, 144, Article ID 102645.
Open this publication in new window or tab >>Process mining and data mining applications in the domain of chronic diseases: A systematic review
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2023 (English)In: Artificial Intelligence in Medicine, ISSN 0933-3657, E-ISSN 1873-2860, Vol. 144, article id 102645Article in journal (Refereed) Published
Abstract [en]

The widespread use of information technology in healthcare leads to extensive data collection, which can be utilised to enhance patient care and manage chronic illnesses. Our objective is to summarise previous studies that have used data mining or process mining methods in the context of chronic diseases in order to identify research trends and future opportunities. The review covers articles that pertain to the application of data mining or process mining methods on chronic diseases that were published between 2000 and 2022. Articles were sourced from PubMed, Web of Science, EMBASE, and Google Scholar based on predetermined inclusion and exclusion criteria. A total of 71 articles met the inclusion criteria and were included in the review. Based on the literature review results, we detected a growing trend in the application of data mining methods in diabetes research.

Additionally, a distinct increase in the use of process mining methods to model clinical pathways in cancer research was observed. Frequently, this takes the form of a collaborative integration of process mining, data mining, and traditional statistical methods. In light of this collaborative approach, the meticulous selection of statistical methods based on their underlying assumptions is essential when integrating these traditional methods with process mining and data mining methods. Another notable challenge is the lack of standardised guidelines for reporting process mining studies in the medical field. Furthermore, there is a pressing need to enhance the clinical interpretation of data mining and process mining results.

National Category
Other Civil Engineering
Identifiers
urn:nbn:se:hb:diva-31342 (URN)10.1016/j.artmed.2023.102645 (DOI)001071512500001 ()2-s2.0-85170100827 (Scopus ID)
Available from: 2024-01-16 Created: 2024-01-16 Last updated: 2024-02-01
Gunnarsson, E., Rödby, K. & Seoane, F. (2023). Seamlessly integrated textile electrodes and conductive routing in a garment for electrostimulation: design, manufacturing and evaluation. Scientific Reports, 13, Article ID 17408.
Open this publication in new window or tab >>Seamlessly integrated textile electrodes and conductive routing in a garment for electrostimulation: design, manufacturing and evaluation
2023 (English)In: Scientific Reports, E-ISSN 2045-2322, Vol. 13, article id 17408Article in journal (Refereed) Published
Abstract [en]

Electro-stimulation to alleviate spasticity, pain and to increase mobility has been used successfully for years. Usually, gelled electrodes are used for this. In a garment intended for repeated use such electrodes must be replaced. The Mollii-suit by the company Inerventions utilises dry conductive rubber electrodes. The electrodes work satisfactory, but the garment is cumbersome to fit on the body. In this paper we show that knitted dry electrodes can be used instead. The knitted electrodes present a lower friction against the skin and a garment is easily fitted to the body. The fabric is stretchable and provides a tight fit to the body ensuring electrical contact. We present three candidate textrodes and show how we choose the one with most favourable features for producing the garment. We validate the performance of the garment by measuring three electrical parameters: rise time (10–90%) of the applied voltage, net injected charge and the low frequency value of the skin–electrode impedance. It is concluded that the use of flat knitting intarsia technique can produce a garment with seamlessly integrated conductive leads and electrodes and that this garment delivers energy to the body as targeted and is beneficial from manufacturing and comfort perspectives.

National Category
Textile, Rubber and Polymeric Materials
Research subject
Textiles and Fashion (General)
Identifiers
urn:nbn:se:hb:diva-30621 (URN)10.1038/s41598-023-44622-5 (DOI)001086926800050 ()2-s2.0-85174163302 (Scopus ID)
Available from: 2023-10-16 Created: 2023-10-16 Last updated: 2024-02-21Bibliographically approved
Hafid, A., Gunnarsson, E., Ramos, A., Rödby, K., Abtahi, F., Bamidis, P. D., . . . Seoane, F. (2023). Sensorized T-Shirt with Intarsia-Knitted Conductive Textile Integrated Interconnections: Performance Assessment of Cardiac Measurements during Daily Living Activities. Sensors, 23(22), Article ID 9208.
Open this publication in new window or tab >>Sensorized T-Shirt with Intarsia-Knitted Conductive Textile Integrated Interconnections: Performance Assessment of Cardiac Measurements during Daily Living Activities
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2023 (English)In: Sensors, E-ISSN 1424-8220, Vol. 23, no 22, article id 9208Article in journal (Refereed) Published
Abstract [en]

The development of smart wearable solutions for monitoring daily life health status is increasingly popular, with chest straps and wristbands being predominant. This study introduces a novel sensorized T-shirt design with textile electrodes connected via a knitting technique to a Movesense device. We aimed to investigate the impact of stationary and movement actions on electrocardiography (ECG) and heart rate (HR) measurements using our sensorized T-shirt. Various activities of daily living (ADLs), including sitting, standing, walking, and mopping, were evaluated by comparing our T-shirt with a commercial chest strap. Our findings demonstrate measurement equivalence across ADLs, regardless of the sensing approach. By comparing ECG and HR measurements, we gained valuable insights into the influence of physical activity on sensorized T-shirt development for monitoring. Notably, the ECG signals exhibited remarkable similarity between our sensorized T-shirt and the chest strap, with closely aligned HR distributions during both stationary and movement actions. The average mean absolute percentage error was below 3%, affirming the agreement between the two solutions. These findings underscore the robustness and accuracy of our sensorized T-shirt in monitoring ECG and HR during diverse ADLs, emphasizing the significance of considering physical activity in cardiovascular monitoring research and the development of personal health applications. 

Keywords
activities of daily living, ECG, HR, sensorized T-shirt, textile electrodes, wearable monitoring
National Category
Textile, Rubber and Polymeric Materials Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Textiles and Fashion (General)
Identifiers
urn:nbn:se:hb:diva-31004 (URN)10.3390/s23229208 (DOI)001119563200001 ()2-s2.0-85177759577 (Scopus ID)
Available from: 2023-12-13 Created: 2023-12-13 Last updated: 2024-02-21Bibliographically approved
Illueca Fernández, E., Fernández Llatas, C., Jara Valera, A. J., Fernández Breis, J. T. & Seoane, F. (2023). Sequence-oriented sensitive analysis for PM2.5 exposure and risk assessment using interactive process mining. PLOS ONE, 18(8), e0290372-e0290372
Open this publication in new window or tab >>Sequence-oriented sensitive analysis for PM2.5 exposure and risk assessment using interactive process mining
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2023 (English)In: PLOS ONE, E-ISSN 1932-6203, Vol. 18, no 8, p. e0290372-e0290372Article in journal (Refereed) Published
Abstract [en]

The World Health Organization has estimated that air pollution will be one of the most significant challenges related to the environment in the following years, and air quality monitoring and climate change mitigation actions have been promoted due to the Paris Agreement because of their impact on mortality risk. Thus, generating a methodology that supports experts in making decisions based on exposure data, identifying exposure-related activities, and proposing mitigation scenarios is essential. In this context, the emergence of Interactive Process Mining—a discipline that has progressed in the last years in healthcare—could help to develop a methodology based on human knowledge. For this reason, we propose a new methodology for a sequence-oriented sensitive analysis to identify the best activities and parameters to offer a mitigation policy. This methodology is innovative in the following points: i) we present in this paper the first application of Interactive Process Mining pollution personal exposure mitigation; ii) our solution reduces the computation cost and time of the traditional sensitive analysis; iii) the methodology is human-oriented in the sense that the process should be done with the environmental expert; and iv) our solution has been tested with synthetic data to explore the viability before the move to physical exposure measurements, taking the city of Valencia as the use case, and overcoming the difficulty of performing exposure measurements. This dataset has been generated with a model that considers the city of Valencia’s demographic and epidemiological statistics. We have demonstrated that the assessments done using sequence-oriented sensitive analysis can identify target activities. The proposed scenarios can improve the initial KPIs—in the best scenario; we reduce the population exposure by 18% and the relative risk by 12%. Consequently, our proposal could be used with real data in future steps, becoming an innovative point for air pollution mitigation and environmental improvement.

National Category
Public Health, Global Health, Social Medicine and Epidemiology
Identifiers
urn:nbn:se:hb:diva-31322 (URN)10.1371/journal.pone.0290372 (DOI)001067701100084 ()2-s2.0-85168741646 (Scopus ID)
Available from: 2024-01-16 Created: 2024-01-16 Last updated: 2024-02-01Bibliographically approved
Jacobsson, M., Seoane, F. & Abtahi, F. (2023). The role of compression in large scale data transfer and storage of typical biomedical signals at hospitals. Health Informatics Journal, 29(4)
Open this publication in new window or tab >>The role of compression in large scale data transfer and storage of typical biomedical signals at hospitals
2023 (English)In: Health Informatics Journal, ISSN 1460-4582, E-ISSN 1741-2811, Vol. 29, no 4Article in journal (Refereed) Published
Abstract [en]

In modern hospitals, monitoring patients' vital signs and other biomedical signals is standard practice. With the advent of data-driven healthcare, Internet of medical things, wearable technologies, and machine learning, we expect this to accelerate and to be used in new and promising ways, including early warning systems and precision diagnostics. Hence, we see an ever-increasing need for retrieving, storing, and managing the large amount of biomedical signal data generated. The popularity of standards, such as HL7 FHIR for interoperability and data transfer, have also resulted in their use as a data storage model, which is inefficient. This article raises concern about the inefficiency of using FHIR for storage of biomedical signals and instead highlights the possibility of a sustainable storage based on data compression. Most reported efforts have focused on ECG signals; however, many other typical biomedical signals are understudied. In this article, we are considering arterial blood pressure, photoplethysmography, and respiration. We focus on simple lossless compression with low implementation complexity, low compression delay, and good compression ratios suitable for wide adoption. Our results show that it is easy to obtain a compression ratio of 2.7:1 for arterial blood pressure, 2.9:1 for photoplethysmography, and 4.1:1 for respiration. 

Keywords
biomedical signals, large-scale health data, compression, downsampling, variable length coding
National Category
Bioinformatics and Systems Biology
Research subject
Textiles and Fashion (General)
Identifiers
urn:nbn:se:hb:diva-31041 (URN)10.1177/14604582231213846 (DOI)001117255200001 ()2-s2.0-85179305751 (Scopus ID)
Available from: 2023-12-18 Created: 2023-12-18 Last updated: 2024-01-10Bibliographically approved
Gunnarsson, E. & Seoane, F. (2023). Three-lead in vivo measurement method for determining the skin-electrode impedance of textile electrodes: A fast, accurate and easy-to-use measurement method suitable for characterization of textile electrodes. Textile research journal
Open this publication in new window or tab >>Three-lead in vivo measurement method for determining the skin-electrode impedance of textile electrodes: A fast, accurate and easy-to-use measurement method suitable for characterization of textile electrodes
2023 (English)In: Textile research journal, ISSN 0040-5175, E-ISSN 1746-7748Article in journal (Refereed) Published
Abstract [en]

The rise of interest in wearable sensing of bioelectrical signals conducted via smart textile systems over the past decades has resulted in many investigations on how to develop and evaluate such systems. All measurements of bioelectrical signals are done by way of electrodes. The most critical parameter for an electrode is the skin-electrode impedance. A common method for measuring skin-electrode impedance is the two-lead method, but it has limitations because it relies on assumptions of symmetries of the body impedance in different parts of the body as well as of the skin-electrode impedances. To address this, in this paper we present an easy-to-use and reliable three-lead in vivo method as a more accurate alternative. We aim to show that the in vivo three-lead method overcomes all such limitations. We aim at raising the awareness regarding the possibility to characterize textile electrodes using a correct, accurate and robust method rather than limited and sometimes inadequate and uninformative methods. The three-lead in vivo method eliminates the effect of body impedance as well as all other contact impedances during measurements. The method is direct and measures only the skin-electrode impedance. This method is suitable for characterization of skin-electrode interface of textile electrodes intended for both bioelectrical signals as well as for electrostimulation of the human body. We foresee that the utilization of the three-lead in vivo method has the potential to impact the further development of wearable sensing by enabling more accurate and reliable measurement of bioelectrical signals. 

Place, publisher, year, edition, pages
SAGE Open, 2023
Keywords
in vivo measurement, skin-electrode impedance, smart textile, Textile electrode, textrode, three-lead measurement, wearable sensing, Electrodes, Wearable technology, Bioelectrical signals, In-vivo, In-vivo measurement, LED measurements, Textile electrodes, Textride, Vivo methods, Smart textiles
National Category
Medical Laboratory and Measurements Technologies
Identifiers
urn:nbn:se:hb:diva-30288 (URN)10.1177/00405175231188143 (DOI)001027188900001 ()2-s2.0-85165257341 (Scopus ID)
Available from: 2023-08-14 Created: 2023-08-14 Last updated: 2024-02-21Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0002-6995-967X

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