Attend and discriminate: Beyond the state-of-the-art for human activity recognition using wearable sensors
Wearables are fundamental to improving our understanding of human activities, especially
for an increasing number of healthcare applications from rehabilitation to fine-grained gait …
for an increasing number of healthcare applications from rehabilitation to fine-grained gait …
Impact of sampling rate on wearable-based fall detection systems based on machine learning models
Falls are a leading health risk for the elderly. Various wearable-based fall detection systems
based on machine learning models have been developed to provide emergency alarms and …
based on machine learning models have been developed to provide emergency alarms and …
Deep auto-set: A deep auto-encoder-set network for activity recognition using wearables
AA Varamin, E Abbasnejad, Q Shi… - Proceedings of the 15th …, 2018 - dl.acm.org
Automatic recognition of human activities from time-series sensor data (referred to as HAR)
is a growing area of research in ubiquitous computing. Most recent research in the field …
is a growing area of research in ubiquitous computing. Most recent research in the field …
Modular integration of a passive RFID sensor with wearable textile antennas for patient monitoring
An integration and modularization solution for a passive computational radio frequency
identification (RFID) module is proposed for wireless patient monitoring. In the proposed …
identification (RFID) module is proposed for wireless patient monitoring. In the proposed …
Visig: Automatic interpretation of visual body signals using on-body sensors
Visual body signals are designated body poses that deliver an application-specific
message. Such signals are widely used for fast message communication in sports (signaling …
message. Such signals are widely used for fast message communication in sports (signaling …
Detuning effects of wearable patch antennas
The variations in the resonance frequency of a wearable 5.3 GHz textile patch antenna due
to bending, human body proximity and moisture absorption are investigated. Noteworthy are …
to bending, human body proximity and moisture absorption are investigated. Noteworthy are …
Double-layer conditional random fields model for human action recognition
The conditional random fields (CRFs) model, as one of the most successful discriminative
approaches, has received renewed attention recently for human action recognition …
approaches, has received renewed attention recently for human action recognition …
[PDF][PDF] Bed exit detection network (BED Net) for patients bed-exit monitoring based on color camera images
Among hospitalized patients, getting up from bed can lead to fall injuries, 20% of which are
severe cases such as broken bones or head injuries. To monitor patients' bed-side status …
severe cases such as broken bones or head injuries. To monitor patients' bed-side status …
Bed-exit prediction based on 3d convolutional neural network
TX Chen, RS Hsiao, CH Kao, DB Lin… - 2018 IEEE SmartWorld …, 2018 - ieeexplore.ieee.org
This paper presents a vision-assisted human motion analysis method that can be used to
recognize in-bed preparatory motions for bed-exit. In this work, a 3D convolutional neural …
recognize in-bed preparatory motions for bed-exit. In this work, a 3D convolutional neural …
Unobstructive human activity recognition: Probabilistic feature extraction with optimized convolutional neural network for classification
K Sivakumar, T Perumal, R Yaakob… - AIP Conference …, 2024 - pubs.aip.org
Human activity detection is a set of techniques that can be used in a wide range of
applications, including smart homes, smart cities, medical health care, and many more …
applications, including smart homes, smart cities, medical health care, and many more …