Program

Best paper award was presented to
ActivityGAN: Generative Adversarial Networks for Data Augmentation in
Sensor-Based Human Activity Recognition

Xi'ang Li (Huazhong University of Science and Technology, Wuhan, China)
Jinqi Luo (Nanyang Technological University, Singapore, Singapore)
Rabih Younes (Duke University, Durham, North Carolina, United States)

Proceedings
The accepted papers in HASCA workshop have been published on ACM DL.

Time is UTC(Coordinated Universal Time) on September 12, 2020.
Presentation time:
HASCA oral presentation, 12 min (10-min talk + 2-min Q&A)
SHL oral presentation, 12 min (10-min talk + 2-min Q&A)
SHL video, 1 min
Nurse oral presentation, 9 min
Nurse video, 1 min










1000-1130
-Opening remarks

-Nurse Challenge summary [15 min]
-Nurse Challenge winner presentation [9 min]

Nurse Care activity Recognition Based on Machine Learning Techniques Using Accelerometer Data.
Mohammad Sabik Irbaz, Abir Azad, Tanjila Alam Sathi, Lutfun Nahar Lota
[Video]


-Nurse Challenge ceremony [5 min]

-SHL Challenge Introduction [2 min]
-SHL Challenge Summary [15 min]

Summary of the sussex-huawei locomotion-transportation recognition challenge 2020
Lin Wang, Hristijan Gjoreski, Mathias Ciliberto, Paula Lago, Kazuya Murao, Tsuyoshi Okita, Daniel Roggen


-SHL Challenge videos broadcast [12 min]

Combining LSTM and CNN for mode of transportation classification from smartphone sensors.
Björn Friedrich, Carolin Lübbe.
[Poster][Video]


Activity recognition for locomotion and transportation dataset using deep learning.
Chan Naseeb, Bilal Al Saeedi.
[Poster][Video]


Where are you? Human activity recognition with smartphone sensor data.
Gulustan Dogan, Iremnaz Cay, Sinem Sena Ertas, Şeref Recep Keskin, Nouran Alotaibi, Elif Sahin.
[Poster][Video]


Human activity recognition using multi-input CNN model with FFT spectrograms.
Kei Yaguchi, Chihiro Ito, Wataru Miyazaki, Kazukiyo Ikarigawa, Yuki Morikawa, Ryo Kawasaki, Yusuke Kyokawa, Eisaku Maeda, Masaki Shuzo.
[Poster][Video]


Smartphone location identification and transport mode recognition using an ensemble of generative adversarial networks.
Lukas Gunthermann.
[Poster][Video]


A multi-view architecture for the SHL challenge.
Massinissa Hamidi, Aomar Osmani, Pegah Alizadeh.


UPIC: user and position independent classical approach for locomotion and transportation modes recognition.
Md. Sadman Siraj, Omar Shahid, Md. Ahasan Atick Faisal, Farhan Fuad Abir, Md. Atiqur Rahman Ahad, Sozo Inoue, Tahera Hossain.
[Poster][Video]


Tackling the SHL recognition challenge with phone position detection and nearest neighbour smoothing.
Peter Widhalm, Philipp Merz, Liviu Coconu, Norbert Brändle.
[Poster][Video]


Ensemble learning for human activity recognition.
Sekiguchi Ryoichi, Abe Kenji, Yokoyama Takumi, Kumano Masayasu.
[Poster][Video]


Ensemble approach for sensor-based human activity recognition.
Sunidhi Brajesh, Anjan Ragh Kotagal Shivaprakash, Aswathy Mohan, Indraneel Ray.
[Poster][Video]


Hierarchical Classification Using ML/DL for Sussex-Huawei Locomotion-Transportation (SHL) Recognition Challenge.
Yi-Ting Tseng, Yi-Hao Lin, Hsien-Ting Lin, Fong-Man Ho, Chia-Hung Lin.
[Poster][Video]


-SHL team 1 presentation [12 min]

IndRNN based long-term temporal recognition in the spatial and frequency domain.
Shuai Li, Beidi Zhao, Yanbo Gao.
[Video]


-SHL team 2 presentation [12 min]

Tackling the SHL Challenge 2020 with person-specific classifiers and semi-supervised learning.
Stefan Kalabakov, Simon Stankoski, Nina Reščič, Andrejaana Andova, Ivana Kiprijanovska, Vito Janko, Martin Gjoreski, Mitja Luštrek.


-SHL team 3 presentation [12 min]

DenseNetX and GRU for the Sussex-Huawei locomotion-transportation recognition challenge.
Yida Zhu, Runze Chen and Haiyong Luo.
[Video]


-SHL ceremony (5 min)
1130-1200Break [30 min]
1200-1330
Session Chair: Mathias Ciliberto (University of Sussex)

-[HASCA] Using iOS for Inconspicuous Data Collection: A Real-World Assessment
Yuuki Nishiyama, Denzil Ferreira, Wataru Sasaki, Tadashi Okoshi, Jin Nakazawa, Anind K Dey, Kaoru Sezaki

-[HASCA] ActivityGANs: Generative Adversarial Networks for Data Augmentation in Sensor-Based Human Activity Recognition
Xi'ang Li, Jinqi Luo, Rabih Younes

-[HASCA] Improving Activity Data Collection with On-DevicePersonalization Using Fine-tuning
Nattaya Mairittha, Tittaya Mairittha, Sozo Inoue

-[HASCA] Social Distancing Warning System at Public Transportation by Analyzing Wi-Fi Signal from Mobile Devices
Thongtat Oransirikul, Hideyuki Takada

-[HASCA] Perception of Interaction between Hand and Object
Yuki Toyosaka, Tsuyoshi Okita

-[HASCA] MCoMat: A New Performance Metric for Imbalanced Multi-layer Activity Recognition Dataset
Sayeda Shamma Alia, Paula Lago, Sozo Inoue

-Nurse Challenge videos broadcast [7 min]

Feature Based Random Forest Nurse Care Activity Recognition Using Accelerometer Data.
Carolin Lübbe, Björn Friedrich, Sebastian Fudickar, Sandra Hellmers, Andreas Hein.
[Poster][Video]


A Pragmatic Signal Processing Approach for Nurse Care Activity Recognition Using Classical Machine Learning.
Md Ahasan Atick Faisal, Md Sadman Siraj, Md Tahmeed Abdullah, Omar Shahid, Farhan Fuad Abir, M.A.R. Ahad.
[Poster][Video]


Complex Nurse Care Activity Recognition Using Statistical Features.
Promit Basak, Shahamat Mustavi Tasin, Malisha Islam Tapotee, Md. Mamun
Sheikh, A.H.M. Nazmus Sakib, Sriman Bidhan Baray, M.A.R. Ahad.
[Poster][Video]


Nurse Care Activity Recognition Based on Convolution Neural Network for Accelerometer Data.
Md. Golam Rasul, Mashrur Hossain Khan, Lutfun Nahar Lota.
[Poster][Video]


A Window-Based Sequence-to-One Approach with Dynamic Voting
for Nurse Care Activity Recognition Using Acceleration-Based Wearable
Sensor.

Yiwen Dong, Jingxiao Liu, Yitao Gao, Sulagna Sarkar, Zhizhang Hu,
Jonathon Fagert, Shijia Pan, Pei Zhang, Hae Young Noh, Mostafa Mirshekari.
[Video]


Nurse Care activity Recognition Challenge: A Comparative Verification of Multiple Preprocessing Approaches.
Hitoshi Matsuyama, Takuto Yoshida, Nozomi Hayashida, Yuto Fukushima, Takuro Yonezawa, Nobuo Kawaguchi.
[Poster][Video]


Nurse Care Activity Recognition: Using Random Forest to Handle Imbalanced Class Problem.
Arafat Rahman, Nazmun Nahid, Iqbal Hassan, M.A.R. Ahad.
[Poster][Video]



1330-1500Break [90 min]
1500-1630
Session Chair: Paula Lago (Kyusyu Inst. of Tech.)

-[HASCA] Action Recognition Using Spatially Distributed Radar Setup Through Microdoppler Signature
Smriti Rani, Arijit Chowdhury, Andrew Gigie, Tapas Chakravarty, Arpan Pal

-[HASCA]ARM Cortex M4-based Extensible Multimodal Wearable Platform for Sensor Research and Context Sensing from Motion & Sound
Daniel Roggen

-[HASCA] CausalBatch: Solving Complexity/Performance Tradeoffs for Deep Convolutional and LSTM Networks for Wearable Activity Recognition
Lloyd Pellatt, Daniel Roggen

-[HASCA] Mental stress classification during motor tasks in older adults using an Artificial Neural Network
Apostolos Kalatzis, Laura Stanley, Ranjana Mehta, Rohith Karthikeyan

-[HASCA] Identifying Label Noise in Time-Series Datasets
Gentry Atkinson, Metsis Vangelis

-Closing