• Advanced Institute of Engineering and Technology (AVITECH)

  • Seminars

    September 17, 2019: Mr. Yuki Iwata (Univ. Electro-Communications, Japan), Vital Sign Acquisition using CW Doppler Radar under Random Body Movement rejected by PCA Algorithm

    Vital sign measurement using a continuous wave (CW) – Doppler radar technique is widely applied where non-contact detection and privacy protection is required, such as infection screening in quarantine stations and sleep monitoring systems in home healthcare. However, CW-Doppler radar measures the velocity of chest surface movement consisting of cardiac and breathing signals with random body movement noise. Therefore, extracting cardiopulmonary information from the superimposed signal is a remaining challenge. Our objective is to remove the signal caused by the movement of the body and breathing, moreover, extract the heartbeat signal from the superimposed signal without relying on simultaneous measurements with other sensors. We proposed a novel adaptive algorithm based on a matched filter using a principal component analysis (PCA) to estimate the heartbeat signal measured under the breathing and random body movements. The proposed algorithm was experimentally evaluated on 6 actual measurement data obtained by healthy subjects. In the experiments, the chest perturbation was recorded while subjects keep their natural breathing for 10 minutes using CW – Doppler radar, and the ECG signal was recorded simultaneously as a grand truth. As a result, the average error of heartbeat per minute of 1.36 bpm and the average root mean square error of R-R intervals of 0.24 sec was obtained. The proposed adaptive algorithm based on PCA showed good performance on extracting heartbeat signals from the CW-Doppler radar for vital sign measurement.

    Speaker: Mr. Yuki Iwata, Univ. Electro-Communications

    Time: 15:30, Tuesday, September 17, 2019

    Venue: G2-315, 144 Xuan Thuy, Cau Giay, Hanoi


    Yuki Iwata received A.Sc. and B.Sc. in Tokyo Metropolitan College of Industrial Technology in 2017 and 2019 respectively. He is now a graduate student at the University of Electro-Communications. His research interests include biomedical signal processing, feature extraction, doppler radar architecture, infection screening system.


    February 2, 2024: Dr. Khoa D. Doan (Vin Univeristy) Toward Reliable and Practical Machine Learning Applications

    While Machine Learning (ML) has rapidly transformed several domains and applications with incredible successes, there are also important areas where the progress is significantly slower. Specifically, there exists a widened complexity gap between the methods currently investigated in research and those used in practice in these areas. One reason is that many algorithms, despite achieving […]

    February 2, 2024: Prof. Heng Ji (University of Illinois at Urbana-Champaign), Combating with Misinformation and Cancer: A Unified Multimodal AI Approach to Healthy and Happy Life

    A research overview of ongoing research projects, especially focusing on two that are most related to the VinUni-UIUC Smart Health Center: (1) Misinformation Detection and Trustworthy Large Language Models; (2) Joint Natural Language and Molecule Learning for Drug Discovery. Unsurprisingly these two seemingly different research problems can be tackled with a unified approach based on […]

    January 11, 2024: Dr. Le Duc Trong (FIT-UET) Resilient Multimodal Learning for Multimodal Emotion Recognition in the Presence of Incomplete Modalities

    Multimodal Emotion Recognition in Conversation (Multimodal ERC) is a critical area of research for interpreting human communication in diverse applications. Nevertheless, the persistent issue of uncertain missing modalities poses a major hurdle, hampering the development of robust Multimodal ERC models. Existing approaches face limitations in effectively leveraging a fusion of diverse data modalities encompassing audio, […]