Jie Hou

• Hou, Jie; Strand-Amundsen, Runar James & Martinsen, Ørjan Grøttem (2023). Detection of physiological concentrations of GABA using dielectric spectroscopy - A pilot study. Journal of Electrical Bioimpedance. ISSN 1891-5469. 14(1), s. 47–52. doi: 10.2478/joeb-2023-0006. Fulltekst i vitenarkiv
• Dapsance, Florian; Hou, Jie; Dufour, Damien; Boccara, Charlotte; Briand, Nolwenn & Martinsen, Ørjan Grøttem (2023). Adipose Tissue Characterization With Electrical Impedance Spectroscopy and Machine Learning. IEEE Sensors Letters. ISSN 2475-1472. 7(10). doi: 10.1109/LSENS.2023.3317921. Fulltekst i vitenarkiv
• Hou, Jie; Ness, Siri Schøne; Tschudi, Jon; O'Farrell, Marion; Veddegjerde, Rune & Martinsen, Ørjan Grøttem [Vis alle 8 forfattere av denne artikkelen] (2022). Assessment of Intestinal Ischemia–Reperfusion Injury Using Diffuse Reflectance VIS-NIR Spectroscopy and Histology. Sensors. ISSN 1424-8220. 22(23). doi: 10.3390/s22239111. Fulltekst i vitenarkiv
• Bordvik, David Andreas; Hou, Jie; Noori, Farzan Majeed; Uddin, Md Zia & Tørresen, Jim (2022). Monitoring In-Home Emergency Situation and Preserve Privacy using Multi-modal Sensing and Deep Learning, 2022 International Conference on Electronics, Information, and Communication (ICEIC 2022) . IEEE (Institute of Electrical and Electronics Engineers). ISSN 9781665409353. doi: 10.1109/ICEIC54506.2022.9748829. Fulltekst i vitenarkiv Vis sammendrag

  Videos and images are commonly used in home monitoring systems. However, detecting emergencies in-home while preserving privacy is a challenging task concerning Human Activity Recognition (HAR). In recent years, HAR combined with deep learning has drawn much attention from the general public. Besides that, relying entirely on a single sensor modal-ity is not promising. In this paper, depth images and radar presence data were used to investigate if such sensor data can tackle the challenge of a system's ability to detect abnormal and normal situations while preserving privacy. The recurrence plots and wavelet transformations were used to make a two-dimensional representation of the presence radar data. Moreover, we fused data from both sensors using data-level, feature-level, and decision-level fusions. The decision-level fusion showed its superiority over the other two techniques. For the decision-level fusion, a combination of the depth images and presence data recurrence plots trained first on convolutional neural networks (CNN). The output was fed into support vector machines, which yielded the best accuracy of 99.98%.

• Hou, Jie; Liavåg, Olav Magnus Ivar; Færden, Ida Høy; Martinsen, Ørjan Grøttem; Tønnessen, Tor Inge & Line, Pål Dag [Vis alle 10 forfattere av denne artikkelen] (2022). Utilization of dielectric properties for assessment of liver ischemia-reperfusion injury in vivo and during machine perfusion. Scientific Reports. ISSN 2045-2322. 12(1). doi: 10.1038/s41598-022-14817-3. Fulltekst i vitenarkiv
• Hou, Jie; Strand-Amundsen, Runar James; Tronstad, Christian; Tønnessen, Tor Inge; Høgetveit, Jan Olav & Martinsen, Ørjan Grøttem (2022). Small intestinal viability assessment using dielectric relaxation spectroscopy and deep learning. Scientific Reports. ISSN 2045-2322. 12(1). doi: 10.1038/s41598-022-07140-4. Fulltekst i vitenarkiv
• Singstad, Bjørn Jostein; Azulay, Naomi; Bjurstedt, Andreas; Bjørndal, Simen Chill; Flø Drageseth, Magnus & Austdal, Lars Peter Engeset [Vis alle 21 forfattere av denne artikkelen] (2021). Estimation of heart rate variability from finger photoplethysmography during rest, mild exercise and mild mental stress. Journal of Electrical Bioimpedance. ISSN 1891-5469. 12(1), s. 89–102. doi: 10.2478/joeb-2021-0012. Fulltekst i vitenarkiv
• Hou, Jie; Strand-Amundsen, Runar James; Hødnebø, Stina; Tønnessen, Tor Inge & Høgetveit, Jan Olav (2021). Assessing ischemic injury in human intestine ex vivo with electrical impedance spectroscopy. Journal of Electrical Bioimpedance. ISSN 1891-5469. 12(1), s. 82–88. doi: 10.2478/joeb-2021-0011. Fulltekst i vitenarkiv
• Hou, Jie; Strand-Amundsen, Runar James; Tronstad, Christian; Høgetveit, Jan Olav; Martinsen, Ørjan Grøttem & Tønnessen, Tor Inge (2021). Automatic prediction of ischemia-reperfusion injury of small intestine using convolutional neural networks: A pilot study. Sensors. ISSN 1424-8220. 21(19). doi: 10.3390/s21196691. Fulltekst i vitenarkiv
• Hou, Jie; Abie, Sisay Mebre; Strand-Amundsen, Runar James; Galperin, Yuri; Bergli, Joakim & Schuelke, Christin [Vis alle 8 forfattere av denne artikkelen] (2021). Temperature dependence of the microwave dielectric properties of γ -aminobutyric acid. Scientific Reports. ISSN 2045-2322. 11(1). doi: 10.1038/s41598-021-97178-7. Fulltekst i vitenarkiv
• Abie, Sisay Mebre; Martinsen, Ørjan Grøttem; Egelandsdal, Bjørg; Hou, Jie; Bjerke, Frøydis & Mason, Alex [Vis alle 7 forfattere av denne artikkelen] (2021). Feasibility of using electrical impedance spectroscopy for assessing biological cell damage during freezing and thawing. Sensors. ISSN 1424-8220. 21(12). doi: 10.3390/s21124129. Fulltekst i vitenarkiv
• Cunha, Andrè Bastos da; Hou, Jie & Schuelke, Christin (2019). Machine learning for stem cell differentiation and proliferation classification on electrical impedance spectroscopy. Journal of Electrical Bioimpedance. ISSN 1891-5469. 10(1), s. 124–132. doi: 10.2478/joeb-2019-0018. Fulltekst i vitenarkiv Vis sammendrag

  Electrical impedance spectroscopy (EIS) measurements on cells is a proven method to assess stem cell proliferation and differentiation. Cell regenerative medicine (CRM) is an emerging field where the need to develop and deploy stem cell assessment techniques is paramount as experimental treatments reach pre-clinical and clinical stages. However, EIS measurements on cells is a method requiring extensive post-processing and analysis. As a contribution to address this concern, we developed three machine learning models for three different stem cell lines able to classify the measured data as proliferation or differentiation laying the stone for future studies on using machine learning to profile EIS measurements on stem cells spectra.

Se alle arbeider i Cristin

• Hou, Jie; Nesaragi, Naimahmed & Tronstad, Christian (2024). Electrical bioimpedance in the era of artificial intelligence. Journal of Electrical Bioimpedance. ISSN 1891-5469. 15(1), s. 1–3. doi: 10.2478/joeb-2024-0001.

Se alle arbeider i Cristin