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Medisinsk teknologi
Trådløs biomedisinsk sensornettverk
Forskningsgruppen arbeider med å utvikle trådløse sensorsystemer for diagnostikk, behandling og fjern monitorering av pasienter.
Kontaktinformasjon
Gruppeleder Ilangko Balasingham, professor, seksjonsleder, dr. ing.
Mobil: 93 45 90 22.
E-post: ilangkob@ntnu.no og ibalasin@ous-hf.no.
Kontaktinformasjon til gruppens medlemmer finnes lengre ned på siden.
Besøksadresse og postadresse
Intervensjonssenteret Rikshospitalet Oslo universitetssykehus Sognsvannsveien 20 0372 Oslo
Institutt for elektroniske systemer NTNU 7491 Trondheim
Beskrivelse av forskningsprofil
Forskningsgruppen arbeider med å utvikle trådløse sensorsystemer for diagnostikk, behandling og fjern monitorering av pasienter. Vi forsker på tråløse sensorsystemer som bruker ekstremt lav energi og er pålitelige og utvikler nye elektroniske designprinsipper og algoritmer som kan brukes både på sensorer (chipnivå) og store datamaskiner for å analysere flerdimensjonale medisinske data ved hjelp av statistisk signalbehandling og maskinlæringsmetoder.
Vi kombinerer metoder fra syntetisk biologi, nanoteknologi og IKT til å designe og utvikle neste generasjons trådløse sensorsystemer (bio-nanoelektroniske systemer) som kan overføre data med og fjernstyre celler direkte fra eksterne systemer som internett med tanke på persontilpasset diagnostikk og behandling av kroniske hjerte sykdommer (pacemaker), nerve sykdommer (Parkinson, Alzheimer) og kreft (tykktarmskreft).
Langsiktig mål
Our vision is to incorporate a remote communication and control module to engineered cells that can monitor and direct therapy for unmet human medicine applications.
develop new medical sensors based on bio-nano technologies (biological nanoelectronics)
develop communication and computing systems based on biological organisms, such as molecules, cells and organs that can communicate with the Internet and cloud services for storing and processing large amounts of data
develop new algorithms for processing and understanding of complex, large amounts of data from sensors, germplasm, medical records, test results, images, etc. in conjunction with high precision diagnosis, treatment and follow-up
perform research and development of basic research in the form of new theories, mathematical modeling, computer-aided simulations and prototype development to preclinical testing and validation - "from bench two bedside"
Project Manager/Principle Investigator of Wireless In-body Sensor and Actuator Networks (WINNOW), (Funded by the Research Council of Norway, IKTpluss program, 01.06.2017 – 31.05.2021, budsjett 16 millioner norske kroner)
This project aims to develop a communication theoretic framework combining heart cells (cardiomyocytes) and nanoscale electronic components for intra-body sensor communications for heart applications.
Coordinator/Principle Investigator of
Wireless In-Body Environment (WiBEC), (Funded by the European Commission, H2020- MARIE Skodowska-CURIE ACTIONS (MSCA-ITN-2015), 01.01.2016-31.12.2019, budget €3.957 million)
This project aims to design and develop the next generation in-body sensor networks targeting two specific applications like multi-site leadless pacemakers and robotic wireless capsule endoscope.
Project Manager of Medical Sensing, Localization, and Communication using Ultra Wideband Technology (MELODY II), (Funded by the
Research Council of Norway,
VERDIKT program, 01.01.2013 - 31.07.2017, budget NOK 14.7 million)
This is a phase II part of the MELODY project which is the large scale ICT project running since 2009 and aims to study using electromagnetic signals in the range of several GHz to design and develop novel remote sensors for vital sign estimation and body area sensor networks connection on-body sensors to off-body devices.
Co-Principle Investigator of NORBAS, (Funded by the Ministry of Foreign Affairs under the HERD/ICT for Balkan, 01.01.2012 - 31.07.2017, budget NOK 6.25 million)
Our part of the project studies a theoretical communication framework using neuronal nanonetworks for deep brain stimulation and communications for applications in diseases like Parkinson and Alzheimer.
Principle Investigator for two industry PhD projects in collaboration with OmniVision Technologies AS (Funded by the Research Council of Norway and OmniVision, 01.08.2015 – 31.07.2020, budget NOK 7 million)
We are developing a new video sensor and video processing algorithms using machine learning to detect anomalies in the gastrointestinal track.
Co-Principle Investigator
Organ on a chip and nano devices (CHIP) (Funded by the Life Science:UiO –convergence environment. 01.01.2018 – 31.12.2021, budget NOK 14.9 million)
We aim to develop a wireless communication solution to monitor islets in pancreas using an organoid.
Innovation projects
Principle Investigator of Medical Cloud and Colon Diagnostic App - an innovation project (Funded by Health South East of Norway 01.01.2015 – 30.11.2018. Budget NOK 3 million)
We are developing an algorithm using video to detect blood/capillary pressure and oxygen level in tissues.
Principle Investigator of Batteryless wireless sensor - an innovation project (Funded by Health South East of Norway 01.01.2016 – 31.06.2017. Budget NOK 1.2 million)
We are developing an implantable batteryless sensor device.
Norway:
Prof. Lars Aabakken, Gastro Lab, Oslo University Hospital
Prof. Håvard Attramadal, Heart Failure Center, Oslo University Hospital
Prof. Stefan Krauss, Norwegian Center of Excellence - Organ on Chip, University of Oslo
Abroad:
Prof. Ian Akyildiz, Georgia Institute of Technology, USA
Prof. Christopher Contag, Michigan State University, USA
Prof. Jianqing Wang, Nagoya Institute of Technology, Japan
Prof. Narcis Cardona, Universitat Politècnica de València, Spain
Prof. Ram Narayanan, Penn State University, USA
Prof. Wout Joseph, Ghent University, Belgium
Prof. Dirk Plettemeier, Technical University of Dresden, Germany
Youssef Chahibi, Ian F. Akyildiz, and Ilangko Balasingham. Propagation Modeling and Analysis of Molecular Motors in Molecular Communication. IEEE Transactions on NanoBioscience, 2016;15(8):917--927.
Mladen Veletic, Pål Anders Floor, Youssef Chahibi, and Ilangko Balasingham. On the Upper Bound of the Information Capacity in Neuronal Synapses. IEEE Transactions on Communications, 2016;64(12):5025--5036.
Igor Sevo, Aleksej Avramovic, Ilangko Balasingham, Ole Jakob Elle, Jacob Bergsland, and Lars Aabakken. Edge density based automatic detection of inflammation in colonoscopy videos. J. Computers in Biology and Medicine, 2016;72:138–150.
Mladen Veletic, Pål Anders Floor, Zdenka Babic, and Ilangko Balasingham. Peer-to-Peer Communication in Neuronal Nano-Network. IEEE Transactions on Communications, 2016;64(3):1153-1164.
Fabio Mesiti, Mladen Veletic, Pål Anders Floor, and Ilangko Balasingham. The Astrocyte Modulation of the Neuronal Activity as a Cascade of Equivalent Circuits. J. Nano Communication Networks, 2015;6(4):183-197.
Fabio Mesiti, Pål Anders Floor, and Ilangko Balasingham. Astrocyte to Neuron Communication Channels with Applications. IEEE Transactions on Molecular, Biological and Multi-Scale Communications, 2015;1(2):164-175.
Pål Anders Floor, Raul Chávez-Santiago, Sverre Brovoll, Øyvind Aardal, Jacob Bergsland, Ole-Johannes H. N. Grymyr, Per Steinar Halvorsen, Rafael Palomar, Dirk Plettemeier, Svein-Erik Hamran, Tor A. Ramstad, and Ilangko Balasingham. In-Body to On-Body Ultra Wideband Propagation Model Derived from Measurements in Living Animals. IEEE J. of Biomedical and Health Informatics, 2015:19(3):938-948.
Pål Anders Floor, Aanna N. Kim, Tor A. Ramstad, Ilangko Balasingham, Niklas Wernersson, and Michael Skoglund. On Joint Source-Channel Coding for a Multivariate Gaussian on a Gaussian MAC. In the IEEE Trans. of Communications, 2015;63(5):1824--1836.
Luis M. Borges, Raul Chavez-Santiago, Norberto Barroca, Fernando J. Velez, and Ilangko Balasingham. Radiofrequency Energy Harvesting for Wearable Sensors. IET Healthcare Technology Letters, 2015:2(1):22-27.
Lars Erik Solberg, Øyvind Aardal, Tor Berger, Ilangko Balasingham, Erik Fosse, and Svein-Erik Hamran. Experimental investigation into radar-based central blood pressure estimation. IET Radar, Sonar and Navigation, 2015;9(2):145-153.
