[image 03789] 講演会のお知らせ: Prof. Thomas Plageman at University of Oslo

[Shin'ichi Satoh]

image-mlの皆様、

国立情報学研究所の佐藤真一です。オスロ大学のThomas Plageman教授による
以下の講演会のお知らせをお送りいたします。Springerのジャーナルの
Multimedia Systemsの編集委員長も務めておられ、マルチメディア分野の重鎮
です。トークはIoTや機械学習を用いた睡眠時無呼吸症候群に対する取り組み
の話であり、実際われわれも無関係ではないかもしれません。

参加無料、参加登録も不要です。どうぞご参加下さい。

-- Shin'ichi

日時: 2019年12月16日(月) 17:00-18:00
場所: 国立情報学研究所 15階 1512会議室
http://www.nii.ac.jp/access/

Title: Towards Sleep Apnea Detection with Consumer Electronics and Machine Learning

Speaker: Prof. Thomas Plageman, University of Oslo

Abstract:

Obstructive sleep apnea (OSA) is a common, but severely
under-diagnosed sleep disorder that affects the natural breathing
cycle during sleep with the periods of reduced respiration or no
airflow at all. It is the long-term goal of the Cesar project (RCN,
FriPro) to increase the percentage of diagnosed OSA cases, reduce the
time to diagnosis, and support long term monitoring of patients with
user friendly and cost-efficient tools for sleep analysis at
home. Core elements are mobile computing platforms (e.g.,
smartphones), consumer electronics sensors, and machine learning (ML)
for OSA detection.

In this presentation, we will give some background on OSA and discuss
some of the studies we have performed in the project. Using public
data sets from physionet.org<http://physionet.org> we could show that 
“simple” ML techniques could achieve rather high classification
performance even for only one signal using a high-quality data
set. Under lab conditions we could show that some of the available
low-cost breathing sensors produce good data – compared to the gold
standard for unattended sleep monitoring at home. Due to the
collaboration with the ongoing A3 study at the Oslo University
Hospital we could use one of these low-cost sensors for sleep
monitoring of 50 patients at home. The resulting data is in its raw
format of low quality and required thorough
preprocessing. Furthermore, we discuss how data augmentation with
Generative Adversarial Networks can be used to increase, re-balance
and personalize data sets. We will conclude the presentation with a
discussion about the future technical challenges as well as some
challenges that need to be addressed by law and ethics.


Short Bio: 

Thomas Plageman received the Dr. Sc. degree in computer science from
the Swiss Federal Institute of Technology (ETH), Zurich, Switzerland,
in 1994, with the Medal of ETH Zurich in 1995. He has been a Professor
with the University of Oslo, Oslo, Norway, since 1996. He currently
leads the Research Group in Distributed Multimedia Systems, Department
of Informatics, University of Oslo. He has published over 200 papers
in peer-reviewed journals, conferences, and workshops in his
field. His research interests include protocol architectures and
middleware solutions for multimedia communication and mobile systems,
future Internet, and multimodal sensor systems, complex event
processing, and machine learning with physiological time-series
data. He is a member of the Association for Computing Machinery
(ACM). He serves as Associate Editor for the ACM Transactions on
Multimedia Computing, Communication, and Applications and
Editor-in-Chief for Multimedia Systems (Springer).