Deep learning in human activity recognition with wearable sensors: A review on advances

S Zhang, Y Li, S Zhang, F Shahabi, S **a, Y Deng… - Sensors, 2022 - mdpi.com
Mobile and wearable devices have enabled numerous applications, including activity
tracking, wellness monitoring, and human–computer interaction, that measure and improve …

FaceBit: Smart face masks platform

A Curtiss, B Rothrock, A Bakar, N Arora… - Proceedings of the …, 2021 - dl.acm.org
The COVID-19 pandemic has dramatically increased the use of face masks across the
world. Aside from physical distancing, they are among the most effective protection for …

IDIoT: Multimodal framework for ubiquitous identification and assignment of human-carried wearable devices

A Bannis, S Pan, C Ruiz, J Shen, HY Noh… - ACM Transactions on …, 2023 - dl.acm.org
IoT (Internet of Things) devices, such as network-enabled wearables, are carried by
increasingly more people throughout daily life. Information from multiple devices can be …

Deep generative cross-modal on-body accelerometer data synthesis from videos

S Zhang, N Alshurafa - Adjunct Proceedings of the 2020 ACM …, 2020 - dl.acm.org
Human activity recognition (HAR) based on wearable sensors has brought tremendous
benefit to several industries ranging from healthcare to entertainment. However, to build …

BMAR: barometric and motion-based alignment and refinement for offline signal synchronization across devices

M Meier, C Holz - Proceedings of the ACM on Interactive, Mobile …, 2023 - dl.acm.org
A requirement of cross-modal signal processing is accurate signal alignment. Though
simple on a single device, accurate signal synchronization becomes challenging as soon as …

Evaluating Large Language Models as Virtual Annotators for Time-series Physical Sensing Data

A Hota, S Chatterjee, S Chakraborty - arxiv preprint arxiv:2403.01133, 2024 - arxiv.org
Traditional human-in-the-loop-based annotation for time-series data like inertial data often
requires access to alternate modalities like video or audio from the environment. These …

Association of number of bites and eating speed with energy intake: Wearable technology results under free-living conditions

N Alshurafa, S Zhang, C Romano, H Zhang… - Appetite, 2021 - Elsevier
Personalized weight management strategies are gaining interest. However, knowledge is
limited regarding eating habits and association with energy intake, and current technologies …

Time synchronization algorithm for the skiing monitoring system

Y Yang, R Cheng, J He, C Li, X Qiao… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
A skiing monitoring system composed of multiple sensors can feedback videos, kinematic,
and physiological parameters synchronously. Also, it is a significant technology for …

HiRA-Pro: High resolution alignment of multimodal spatio-temporal data: a process physics driven approach

A Hanchate, H Balhara, VS Chindepalli… - arxiv preprint arxiv …, 2024 - arxiv.org
We present HiRA-Pro, a novel procedure to align, at high spatio-temporal resolutions,
multimodal signals from real-world processes and systems that exhibit diverse transient …

LiDAR and camera data for smart urban traffic monitoring: Challenges of automated data capturing and synchronization

G Vitols, N Bumanis, I Arhipova, I Meirane - International Conference on …, 2021 - Springer
Availability and range of sensors and other type of smart hardware are growing.
Implementation of such solutions is becoming a crucial part of development strategies for …