Program

Presentation time:
HASCA oral presentation, 20 min (approx. 15-min talk + 5-min Q&A)

09:00-09:10 Opening (Chair: Kazuya Murao)
09:10-10:30 Session 1 [20min x4] (Chair: Kazuya Murao)
  • Towards LLMs for Sensor Data: Multi-Task Self-Supervised Learning
    Tsuyoshi Okita(Kyushu Institute of Technology), Kosuke Ukita(Kyushu Institute of Technology), Koki Matsuishi(Kyushu Institute of Technology), Masaharu Kagiyama(Kyushu Institute of Technology), Kodai Hirata(Kyushu Institute of Technology), Asahi Miyazaki(Kyushu Institute of Technology)
  • Predicting and Analyzing Emotion of Elderly People in Care Facilities
    Xinyi Min(Kyushu Institute of Technology), Haru Kaneko(Kyushu Institute of Technology), Sozo Inoue(Kyushu Institute of Technology
  • Personalized federated human activity recognition through semi-supervised learning and enhanced representation
    Lulu Gao(Kyushu University), Shin'ichi Konomi(Kyushu University)
  • Investigating the Effect of Orientation Variability in Deep Learning-based Human Activity Recognition
    Azhar Ali Khaked(Concordia University), Nobuyuki Oishi(University of Sussex), Daniel Roggen(University of Sussex), Paula Lago(Concordia University)
10:30-11:00 Coffee Break
11:00-12:20 Session 2 [20min x4] (Chair: Paula Lago)
  • Cardiac massage practice application using barometer in a smart phone and sealed bag
    Soto Mizukusa(Aichi Institute of Technology), Katsuhiko Kaji(Aichi Institute of Technology)
  • Eye movement differences in Japanese text reading between cognitively healthy older and younger adults
    Jumpei Kobayashi(Dai Nippon Printing Co., Ltd.), Hiroyuki Suzuki(Tokyo Metropolitan Institute for Geriatrics and Gerontology), Kenichiro Sato(Tokyo Metropolitan Institute for Geriatrics and Gerontology), Susumu Ogawa(Tokyo Metropolitan Institute for Geriatrics and Gerontology), Hiroko Matsunaga(Tokyo Metropolitan Institute for Geriatrics and Gerontology), Toshio Kawashima( Future University Hakodate)
  • A Data-Driven Study on the Hawthorne Effect in Sensor-Based Human Activity Recognition
    Alexander Hoelzemann(University of Siegen), Marius Bock(University of Siegen), Ericka Andrea Valladares Bastias(University of Siegen), Salma El Ouazzani Touhami(University of Siegen), Kenza Nassiri(University of Siegen), Kristof Van Laerhoven(University of Siegen)
  • Eco-Friendly Sensing for Human Activity Recognition
    Kaede Shintani(Osaka University), Hamada Rizk(Osaka University), Hirozumi Yamaguchi(Osaka University)
12:30-14:00 Lunch Break
14:00-15:30 Session 3 [SHL session]
  • SHL intro [4 min]
  • SHL summary paper [15 min]
  • SHL top 3 papers [36 min]
  • SHL award ceremony [5 min]
  • SHL posters session[18 min]
15:30-16:00 Coffee Break with SHL poster (cont'd)
16:00-17:00 Session 4 [20min x3] (Chair: Yu Enokibori)
  • Where Are the Best Positions of IMU Sensors for HAR? - Approach by a Garment Device with Fine-Grained Grid IMUs -
    Akihisa Tsukamoto(Nagoya University), Naoto Yoshida(Kogakuin University), Tomoko Yonezawa(Kansai University), Kenji Mase(Nagoya University), Yu Enokibori(Nagoya University)
  • Toward Pioneering Sensors and Features Using Large Language Models in Human Activity Recognition
    Haru Kaneko(Kyushu Institute of Technology), Sozo Inoue(Kyushu Institute of Technology)
  • Human activity recognition for packing processes using CNN-biLSTM
    Alberto Angulo(Sonora Institute of Technology), Jessica Beltran(Universidad Autonoma de Coahuila), Luis A. Castro(Sonora Institute of Technology)
17:00-17:10 Closing