Liang Z. (2022). Context-aware sleep health recommender systems (CASHRS): a narrative review. Electronics 2022, 11(20), 3384. Doi: 10.3390/electronics1120338 (Impact factor: 2.69, Q2) [SCI/Scopus]
Liang Z. (2022). Mining associations between glycemic variability in awake-time and in-sleep among non-diabetic adults. Frontiers in Medical Technology (Section: Medtech Data Analytics). [PubMed]
Liang Z. (2021) What does sleeping brain tell about stress? A pilot fNIRS study into stress-related cortical hemodynamic features during sleep. Frontiers in Computer Science (Section: Mobile and Ubiquitous Computing) 3:774949. Doi: 10.3389/fcomp.2021.774949. [SCI /Scopus]
Liang Z, Chapa-Martell MA. (2021) A multi-level classification approach for sleep stage prediction with processed data derived from consumer wearable activity trackers. Frontiers in Digital Health (Section: Health Informatics) 3:665946. Doi: 10.3389/fdgth.2021.665946. (Impact factor: 2.20, Q2) [PubMed /Scopus]
Bertrand L, Cleyet-Marrel N, Liang Z. (2021) Recognizing eating activities in free-living environment using consumer wearable devices. Engineering Proceedings 6(1): 58. Doi:10.3390/I3S2021Dresden-10141. 【First authors are visiting master students】
Liang Z, Ploderer B. (2020) “How does Fitbit measure brainwaves”: a qualitative study into the credibility of sleep-tracking technologies. PACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT) 4(1):Article 17. (Impact factor: 4.16, Q1) [SCI/Scopus]
Liang Z, Chapa-Martell MA. (2019) Accuracy of Fitbit wristbands in measuring sleep stage transitions and the effect of user-specific factors. JMIR mHealth and uHealth 7(6):e13384, DOI:10.2196/13384. (Impact Factor: 5.65, Q1) [PubMed/SCI/Scopus] # Featured in Techheading
Liang Z, Chapa-Martell MA. (2019) Not all errors are created equal: influence of user characteristics on measuring errors of consumer wearable devices for sleep tracking. EAI Endorsed Transactions on Pervasive Health and Technology 18(15):e4. (Impact Factor: 1.68, Q3) [SCI/Scopus]
Liang Z, Yoshida Y, Iino N, Nishimura T, Chapa-Martell MA, Nishimura S.(2019) A pervasive sensing approach to automatic assessment of trunk coordination using mobile devices. EAI Endorsed Transactions on Pervasive Health and Technology 18(15):e5. (Impact Factor: 1.68, Q3) [SCI/Scopus]
Liang Z, Chapa-Martell MA. (2019) Measurement accuracy of consumer sleep tracking wristbands is associated to users’ age and sleep efficiency. The Journal of Physical Fitness and Sports Medicine 8(6):394.
Liang Z, Chapa-Martell MA. (2018) Validity of consumer activity wristbands and wearable EEG for measuring overall sleep parameters and sleep structure in free-living conditions. Journal of Healthcare Informatics Research 2 (1-2): 152-178. (Impact Factor: 3.28, Q1) [PubMed/SCI/Scopus] #Cited by UK Parliamentary Office of Sciences & Technology # Featured in Gizmodo
Yoshida Y, Liang Z, Nishimura S, Konosu H, Nagao T, Nishimura T. (2018) Quality evaluation for sports coaching service: evaluate trunk torsion by mobile terminal. Transaction of Information Processing Society of Japan 59(2): 591-601.
Liang Z, Ploderer B, Liu W, Nagata Y, Bailey J, Kulik L, Li Y. (2016). SleepExplorer: A visualization tool to make sense of correlations between personal sleep data and contextual factors. Personal and Ubiquitous Computing 20(6): 985-1000. (Impact factor: 3.06, Q1) [SCI/Scopus]