Human digital twin, the development and impact on design

Y Song - … of Computing and Information Science in …, 2023 - asmedigitalcollection.asme.org
In the past decade, human digital twins (HDTs) attracted attention in both digital twin (DT)
applications and beyond. In this paper, we discuss the concept and the development of …

Selfhar: Improving human activity recognition through self-training with unlabeled data

CI Tang, I Perez-Pozuelo, D Spathis, S Brage… - Proceedings of the …, 2021 - dl.acm.org
Machine learning and deep learning have shown great promise in mobile sensing
applications, including Human Activity Recognition. However, the performance of such …

Beyond accuracy: a critical review of fairness in machine learning for mobile and wearable computing

S Yfantidou, M Constantinides, D Spathis… - arXiv preprint arXiv …, 2023 - arxiv.org
The field of mobile and wearable computing is undergoing a revolutionary integration of
machine learning. Devices can now diagnose diseases, predict heart irregularities, and …

Deep PPG: Large-scale heart rate estimation with convolutional neural networks

A Reiss, I Indlekofer, P Schmidt, K Van Laerhoven - Sensors, 2019 - mdpi.com
Photoplethysmography (PPG)-based continuous heart rate monitoring is essential in a
number of domains, eg, for healthcare or fitness applications. Recently, methods based on …

Where would i go next? large language models as human mobility predictors

X Wang, M Fang, Z Zeng, T Cheng - arXiv preprint arXiv:2308.15197, 2023 - arxiv.org
Accurate human mobility prediction underpins many important applications across a variety
of domains, including epidemic modelling, transport planning, and emergency responses …

Joint prediction of next location and travel time from urban vehicle trajectories using long short-term memory neural networks

J Sun, J Kim - Transportation Research Part C: Emerging …, 2021 - Elsevier
This paper aims to incorporate travel time prediction in the next location prediction problem
to enable the prediction of the city-wide movement trajectory of an individual vehicle by …

Classical and deep learning methods for recognizing human activities and modes of transportation with smartphone sensors

M Gjoreski, V Janko, G Slapničar, M Mlakar, N Reščič… - Information …, 2020 - Elsevier
Abstract The Sussex-Huawei Locomotion-Transportation Recognition Challenge presented
a unique opportunity to the activity-recognition community to test their approaches on a …

A hierarchical temporal attention-based LSTM encoder-decoder model for individual mobility prediction

F Li, Z Gui, Z Zhang, D Peng, S Tian, K Yuan, Y Sun… - Neurocomputing, 2020 - Elsevier
Prediction of individual mobility is crucial in human mobility related applications. Whereas,
existing research on individual mobility prediction mainly focuses on next location prediction …

Recurrent neural network for human activity recognition in embedded systems using ppg and accelerometer data

M Alessandrini, G Biagetti, P Crippa, L Falaschetti… - Electronics, 2021 - mdpi.com
Photoplethysmography (PPG) is a common and practical technique to detect human activity
and other physiological parameters and is commonly implemented in wearable devices …

A structured and scalable mechanism for test access to embedded reusable cores

EJ Marinissen, R Arendsen, G Bos… - … 1998 (IEEE Cat. No …, 1998 - ieeexplore.ieee.org
The main objective of core-based IC design is improvement of design efficiency and time-to-
market. In order to prevent test development from becoming the bottleneck in the entire …