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Detection of Artifacts in Ambulatory Electrodermal Activity Data.

, , , , , , and . Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 4 (2): 44:1-44:31 (2020)

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Detection of Artifacts in Ambulatory Electrodermal Activity Data., , , , , , and . Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 4 (2): 44:1-44:31 (2020)Federated Learning for Privacy-Aware Human Mobility Modeling., , and . Frontiers Artif. Intell., (2022)Cognitive Load Monitoring With Wearables-Lessons Learned From a Machine Learning Challenge., , , , , , , , and . IEEE Access, (2021)Exploring LAUREATE - the Longitudinal multimodAl stUdent expeRience datasEt for AffecT and mEmory research., , , and . UbiComp/ISWC Adjunct, page 494-499. ACM, (2022)A New Frontier for Activity Recognition: The Sussex-Huawei Locomotion Challenge., , , , , , , , , and . UbiComp/ISWC Adjunct, page 1511-1520. ACM, (2018)Non-Invasive Blood Pressure Estimation from ECG Using Machine Learning Techniques., , , and . Sensors, 18 (4): 1160 (2018)BAG-DSM: A Method for Generating Alternatives for Hierarchical Multi-Attribute Decision Models Using Bayesian Optimization., , and . Algorithms, 15 (6): 197 (2022)Recognizing Activities of Daily Living using Multi-sensor Smart Glasses., , , , , , , , , and . MIPRO, page 397-402. IEEE, (2023)Cross-location transfer learning for the sussex-huawei locomotion recognition challenge., , , , , and . UbiComp/ISWC Adjunct, page 730-735. ACM, (2019)Learning comprehensible and accurate hybrid trees., , , , and . Expert Syst. Appl., (2021)