Ubiquitous and Personal Computing Lab
Faculty of Engineering, Kyoto University of Advanced Science (KUAS), Japan
#Quantified-Self #consumerWearables #softwareCentered #digitalHealth #digitalEducation #predictiveModelling #signalProcessing #dataMining #humanComputerInteraction
Computing for Anyone, at Anytime, Anywhere
We research, develop and validate novel computing technologies to improve health, productivity, and well-being of individuals.
Devoted to creating computing technologies that can be used anytime, anywhere, by anyone, we envision a world where everyone is able to design and conduct self-experiments to test their personal hypothesis, to gain a better understanding into the-self, and to maximize their potential.
This research track focuses on developing novel software sensors with consumer wearble hardware for measuring psychological and physiological states in free-living environments.
#sleepTracking #eyeTracking #glucoseSensing #depressionDetection #fNIRS #brainImaging #signalProcessing #machineLearning
This research track focuses on developing novel analytical and predictive modelling methods for gaining insights into the quantified-self data collected using off-the-shelf consumer wearables.
Subtrack 2-2: Large-Scale Longitudinal Collection of QS Data
#personalInformatics #consumerInformatics #dataVisualization #dataMining #machineLearning #timeSeriesAnalysis
This research track focuses on designing and developing software applications (mobile apps, smartwatch apps, web apps) to engineer people's behavior towards better health, productivity and wellbeing.
Subtrack 3-2: mLearning App Development
Subtrack 3-3: Human-Computer Interaction in mHealth & mLearning
#appDevelopment #gamification #behaviorChangeTheory #mHealth #digitalHealth #HCI #soundTherapy #mobileLearning #nudge
Our following paper was published in the Proceedings of the 19th International Conference on Web Information Systems and Technologies (WEBIST 2023), indexed by Scopus. Yapa H. P. P. P., Liang Z, Piumarta I. (2023) Who Says What (WSW): A Novel Model for Utterance-Aware Speaker Identification in Text-Based Multi-Party Conversations. This paper received a Best Paper Award [15 Nov 2023].
Our following submissions were accepted to present at the 4th Sleep Congress of Asian Society of Sleep (ASSM 2023). [10 Dec 2023]
Liang Z, Yahya KN, Setiawan EN, Kasan JA, Firdauzi MO. (2023) FunAlarm: Gamification-Based Smartphone Alarm Application for Reducing Wakeup Delay.
Hoang HN, Liang Z. (2023) Shallow and Deep Learning Models for Detecting Apnea Events in Stroke Patients.
Khotchasing K, Liang Z. (2023) A Pilot Study into the Feasibility of Utilizing Contagious Yawning to improve Sleep Quality.
Our following paper was published in the Proceedings of the 31st International Conference on Computers in Education (ICCE 2023), indexed by Scopus. Liang Z. (2023) Enhancing Learning Experience in University Engineering Classes with Kahoot! Quiz Games. [6 Dec 2023]
Our following paper was published in the Proceedings of the14th International Conference on Mobile Computing and Ubiquitous Networking (ICMU 2023), indexed by Scopus. Liang Z. (2023) Effect of Decision Boundary for Logistic Regression Classifiers on Sleep Apnea Screening Accuracy with Wearable SpO2 Data. [30 Nov 2023]
Our following paper was published in the Proceedings of the 2023 International Conference on Teaching, Assessment and Learning for Engineering (TALE 2023), indexed by Web of Science and Scopus. Liang Z. (2023) Comparing Attitudes Towards Mobile App Development between International Students and Domestic Japanese Students. [30 Nov 2023]
We organized a co-design workshop Gamified Smartwatch for Sleep Health Workshop, which was facilitated by Prof. Edward Melcer and was attended by 47 students. This workshop was a follow-up of the three co-design workshops that we had during the summer and fall of 2023 and aimed to further explore the interdisciplinary research field at the intersection of gamification, digital health, and human-computer interaction. Instagram / Facebook [22 Nov 2023]
We following submissions were published in the Proceedings of the 10th International Electronic Conference on Sensors and Applications (ECSA2023). [15 Nov 2023]
Liang Z. (2023) Developing and Validating Ensemble Classifiers for At-Home Sleep Apnea Screening.
Sirithummarak P, Liang Z. (2023) Developing a Cross-Platform Application for Integrating Real-time Time-series Data from Multiple Wearable Sensors
Our following paper will be published in Digital Health, indexed by Web of Science, Scopus, and PubMed. Liang Z. (2023) Novel method combining multiscale attention entropy of overnight blood oxygen level and machine learning for easy sleep apnea screening. [16 Oct 2023]
Our following paper will be published in the Proceedings of the 12th Global Conference on Consumer Electronics (GCCE 2023) [10 Oct 2023]
Liang Z. (2023) Developing Sleep Apnea Screening Models Compatible With Low-Resolution SpO2 Data
Jayen H, Lukovnikova A, Nhung HH, Liang Z. (2023) Mining Contrast Rules in a Sleep Apnea Dataset
Our following submissions were presented at the 48th Annual Meeting of Japanese Society of Sleep Research. [15 Sep 2023]
Nhung HH, Jayen H, Lukovnikova A, Liang Z. (2023) Beyond Statistical Analysis: Identifying Meaningful Patterns in Sleep Apnea Dataset using Contrast Set Mining.
Khotchasing K, Nhung HH, Liang Z. (2023) Design and Development of Gamification mHealth Application for Sleep Hygiene Intervention.
Liang Z. (2023) Machine Learning based Sleep Apnea Screening with Overnight SpO2 Recordings.
〒615-8577 京都市右京区山ノ内五反田町18番地 南館工学部5階研究室508
South Building F5-508, Faculty of Engineering
Kyoto University of Advanced Science (KUAS)
18 Yamanouchi Gotanda-cho, Ukyo-ku, Kyoto 615-8577, Japan