1st Edition
Human Activity and Behavior Analysis Advances in Computer Vision and Sensors: Volume 1
Human Activity and Behavior Analysis relates to the field of vision and sensor-based human action or activity and behavior analysis and recognition. The book includes a series of methodologies, surveys, relevant datasets, challenging applications, ideas, and future prospects.
The book discusses topics such as action recognition, action understanding, gait analysis, gesture recognition, behavior analysis, emotion and affective computing, and related areas. This volume focuses on relevant activities in three main subject areas: Healthcare and Emotion, Mental Health, and Nurse Care Records.
The editors are experts in these arenas and the contributing authors are drawn from high-impact research groups around the world. This book will be of great interest to academics, students, and professionals working and researching in the field of human activity and behavior analysis.
Healthcare and Emotion
1. Forecasting Parkinson's Disease Patients' Wearing-Off Using Wrist-Worn Fitness Tracker and Smartphone Dataset
John Noel Victorino, Yuko Shibata, Inoue Sozo, and Tomohiro Shibata
2. Toward Human Thermal Comfort Sensing: New Dataset and Analysis of Heart Rate Variability (HRV) Under Different Activities
Tahera Hossain, Yusuke Kawasaki, Kazuki Honda, Kizito Nkurikiyeyezu, and Guillaume Lopez
3. Reducing the Number of Wearable Sensors and Placement Optimization by Missing Data Imputation on Nursery Teacher Activity Recognition
Akira Omi, Kensi Fujiwara, Ren Ohmura, and Naoko Ishibashi
4. Optimal EEG Electrode Set for Emotion Recognition from Brain Signals: An Empirical Quest
Rumman Ahmed Prodhan, Sumya Akter, Md. Akhtaruzzaman Adnan, and Tanmoy Sarkar Pias
5. Translation-Delay-Aware Emotional Avatar System for Online Communication Support
Tomoya Suzuki, Akihito Taya, Yoshito Tobe, and Guillaume Lopez
6. Touching with Eye Contact and Vocal Greetings Increases the Sense of Security
Miyuki Iwamoto and Atsushi Nakazawa
7. Challenges and Opportunities of Activity Recognition in Clinical Pathways
Christina Garcia and Sozo Inoue
Mental Health
8. Anxolotl, an Anxiety Companion App - Stress Detection
Nuno Gomes, Matilde Pato, Pedro Santos, André Lourenço¸ and Lourenço Rodrigues
9. Detection of Self-Reported Stress Level from Wearable Sensor Data Using Machine Learning and Leep Learning-Based Classifiers: Is It Feasible?
Atzeni Michele, Cossu Luca, Cappon Giacomo, and Vettoretti Martina
10. A Multi-Sensor Fusion Method for Stress Recognition
Leonardo Alchieri, Nouran Abdalazim, Lidia Alecci, Silvia Santini, and Shkurta Gashi
11. Classification of Stress via Ambulatory ECG and GSR Data
Zachary Dair, Muhammad Saad, Urja Pawar, Samantha Dockray, and Ruairi O’Reilly
12. Detection and Classification of Acute Psychological Stress in Free-Living: Challenges and Achievements
M. Sevil, M. Rashid, R. Askari, L. Sharp, L. Quinn, and A. Cinar
13. IEEE EMBC 2022 Workshop and Challenge on Detection of Stress and Mental Health Using Wearable Sensors
Huiyuan Yang, Han Yu, Alicia Choto Segovia, Maryam Khalid, Thomas Vaessen, and Akane Sano
14. Understanding Mental Health Using Ubiquitous Sensors and Machine Learning: Challenges Ahead
Tahia Tazin, Tahera Hossain, Shahera Hossain, and Sozo Inoue
Nurse Care Records
15. Improving Complex Nurse Care Activity Recognition Using Barometric Pressure Sensors
Muhammad Fikry, Christina Garcia, Vu Nguyen Phuong Quynh, Sozo Inoue, Shintaro Oyama, Keiko Yamashita, Yuji Sakamoto, and Yoshinori Ideno
16. Analysis of Care Records for Predicting Urination Times
Masato Uchimura, Sozo Inoue, and Haru Kaneko
17. Predicting User-Specific Future Activities Using LSTM-Based Multi-Label Classification
Mohammad Sabik Irbaz, Lutfun Nahar Lota, and Fardin Ahsan Sakib
18. Nurse Activity Recognition Based on Temporal Frequency Features
Md. Sohanur Rahman, Hasib Ryan Rahman, Abrar Zarif, Yeasin Arafat Pritom, and Md Atiqur Rahman Ahad
19. Ensemble Classifier for Nurse Care Activity Prediction Based on Care Records
Björn Friedrich and Andreas Hein
20. Addressing the Inconsistent and Missing Time Stamps in Nurse Care Activity Recognition Care Record Dataset
Rashid Kamal, Chris Nugent, Ian Cleland, and Paul McCullagh
21. A Sequential-Based Analytical Approach for Nurse Care Activity Forecasting
Md. Mamun Sheikh, Shahera Hossain, and Md. Atiqur Rahman Ahad
22. Predicting Nursing Care with K-Nearest Neighbors and Random Forest Algorithms
Jonathan Sturdivant, John Hendricks, and Gulustan Dogan
23. Future Prediction for Nurse Care Activities Using Deep Learning Based Multi-Label Classification
Md. Golam Rasul, Wasim Akram, Sayeda Fatema Tuj Zohura, Tanjila Alam Sathi, and Lutfun Nahar Lota
24. A Classification Technique Based on Exploratory Data Analysis for Activity Recognition
Riku Shinohara, Huakun Liu, Monica Perusquía-Hernández, Naoya Isoyama, Hideaki Uchiyama, and Kiyoshi Kiyokawa
25. Time Series Analysis of Care Records Data for Nurse Activity Recognition in the Wild
Md. Kabiruzzaman, Mohammad Shidujaman, Shadril Hassan Shifat, Pritom Debnath, and Shahera Hossain
26. Summary of the Fourth Nurse Care Activity Recognition Challenge – Predicting Future Activities
Defry Hamdhana, Christina Garcia, Nazmun Nahid, Haru Kaneko, Sayeda Shamma Alia, Tahera Hossain, and Sozo Inoue
Biography
Md Atiqur Rahman Ahad, PhD, is Associate Professor at the University of East London, UK.
Sozo Inoue, PhD, is Professor at the Kyushu Institute of Technology, Japan.
Guillaume Lopez, PhD, is Professor at Aoyama Gakuin University, Japan.
Tahera Hossain, PhD, is Assistant Professor (Project) at Aoyama Gakuin University, Japan.
