WELMO: Wearable Electronics for Effective Lung Monitoring
Scope
International
Research Group
coordinator
Synopsis
Leveraging the capabilities of ASIC and based-on the trend of exploiting novel electronics for medical-related purposes the 42-month project WELMO aims to develop, and validate a new generation of low-cost and low-power miniaturized sensors, integrated to a comfortable vest, enabling the effective and accurate monitoring of the lungs, through the collection of sound and image signals, that can be combined, processed and linked with specific clinical outcome by applying innovative algorithms. The newly developed technology will be prototyped and demonstrated for Electrical Impedance tomography (EIT ) and for lung sounds. It will also allow easy extension to biopotentials (e.g., multi-channel ECG) or other type of bioimpedance (e.g., galvanic skin response or BIS, bioimpedance spectrography) as well as to any other signals, especially those are be sensed at distant points on the body (e.g., temperature map), thereby providing a modular technology platform opening the way to a multitude of form factors and products in a short time to market. Overall the WELMO approach will rely on the following technology offerings: (i) low-cost and low-power innovative cooperative sensors integrated in a wearable vest through a single-wired connection, (ii) continuously monitoring of the lungs’ condition through EIT and lung sound recordings, (iii) implementation of novel algorithms for processing the data collected and (iv) presentation of the processing and monitoring outcomes through a set of applications. The impact and, acceptances usability of the proposed solution will be validated in a realistic setup through the execution of excessive validation studies. Finally a business sustainability study will be carried out, aiming to the mid-term exploitation of the proposed solution.
Funding
H2020 ICT: H2020-825572
Total budget
€ 3 999 680.00
Keywords
Medical Informatics
Start Date
2019-01-19
Partners
EXODUS S. A. (Coordinator, Greece), CSEM (Switzerland), University of Thessaloniki (Greece), Kiel University (Germany), Smartex s.r.l. (Italy), Elsys (Serbia), Artec Design (Estonia), Wellics Ltd. (UK)
CISUC budget
€ 402 500.00
End Date
2022-07-18
Publications
2024
D. Pessoa and B. M. M. Rocha and M. Gomes and G. Rodrigues and G. Petmezas and G. Cheimariotis and N. Maglaveras and A. Marques and I. Frerichs and P. d. Carvalho and R. P. Paiva, "Ensemble deep learning model for dimensionless respiratory airflow estimation using respiratory sound", Biomedical Signal Processing and Control, vol. 87, pp. 105451-105451, 2024
B. M. M. Rocha and E. Kaimakamis and G. Cheimariotis and G. Petmezas and V. Kilintzis and D. Pessoa and A. Marques and P. d. Carvalho and R. P. Paiva and N. Maglaveras and W. Yunan and E. Chatzis and S. Leandros and S. Kotoulas and M. Bitzani and K. A. K., "A deep learning method for predicting the COVID-19 ICU patient outcome fusing X-rays, respiratory sounds, and ICU parameters", Expert Systems with Applications, vol. 235, pp. 121089-121089, 2024
2023
D. Pessoa and B. M. M. Rocha and P. Georgios and K. Vassilis and R. P. Paiva and P. d. Carvalho and C. Strodthoff and G. Maria and G. Rodrigues and G. Cheimariotis and E. Kaimakamis and N. Maglaveras and A. Marques and I. Frerichs, "BRACETS: Bimodal repository of auscultation coupled with electrical impedance thoracic signals", Computer Methods and Programs in Biomedicine, in Computer Methods and Programs in Biomedicine, vol. 240, pp. 107720, pp. 107720-107720, 2023
D. Pessoa and G. Petmezas and B. M. M. Rocha and S. Leandros and K. Vassilis and N. Maglaveras and I. Frerichs and P. d. Carvalho and R. P. Paiva, "Pediatric Respiratory Sound Classification Using a Dual Input Deep Learning Architecture", in IEEE Biomedical Circuits and Systems Conference 2023, 2023
2022
R. P. Paiva and P. d. Carvalho and V. Kilintzis, "Wearable Sensing and Intelligent Data Analysis for Respiratory Management", Academic Press (Elsevier), 2022
2021
B. M. M. Rocha and D. Pessoa and A. Marques and P. d. Carvalho and R. P. Paiva, "Automatic Classification of Adventitious Respiratory Sounds: A (Un)Solved Problem?", Sensors, vol. 21, pp. 57-na, 2021
B. Vogt and D. Pessoa and B. M. M. Rocha and R. P. Paiva and P. d. Carvalho and N. Maglaveras and I. Frerichs and K. Haris and C. Strodthoff and G. Cheimariotis and G. Petmezas and N. Weiler, "Identification and analysis of stable breathing periods in electrical impedance tomography recordings", Physiological Measurement, vol. 42, no. 064003, 2021
D. Pessoa and P. d. Carvalho and R. P. Paiva and B. M. M. Rocha and G. Cheimariotis and E. Kaimakamis and S. Kotoulas and M. Tzimou and N. Maglaveras and A. Marques, "Detection of squawks in respiratory sounds of mechanically ventilated COVID-19 patients", 2021
2020
G. Yilmaz and M. Rapin and D. Pessoa and B. M. M. Rocha and A. M. d. Sousa and R. Rusconi and P. d. Carvalho and J. Wacker and R. P. Paiva and O. Chételat, "A Wearable Stethoscope for Long-Term Ambulatory Respiratory Health Monitoring", Sensors, vol. 20, no. 18, pp. 5124-5124, 2020
B. M. M. Rocha and D. Pessoa and A. Marques and P. d. Carvalho and R. P. Paiva, "Influence of Event Duration on Automatic Wheeze Classification", in 2020 25th International Conference on Pattern Recognition (ICPR), 2020
D. Pessoa and A. Marques and P. d. Carvalho and B. M. M. Rocha and R. P. Paiva, "Personalized Detection of Explosive Cough Events in Patients With Pulmonary Disease", 2020
2019
R. P. Paiva and B. M. M. Rocha and C. Teixeira and J. Henriques and P. d. Carvalho, "Feature Engineering for the Detection and Classification of Respiratory Sounds", in XV Mediterranean Conference on Medical and Biological Engineering and Computing – MEDICON 2019, 2019