Search Results for author:
Found 6 papers, 2 papers with code
The Potential of Wearable Sensors for Assessing Patient Acuity in Intensive Care Unit (ICU)
In this study, we evaluated the impact of integrating mobility data collected from wrist-worn accelerometers with clinical data obtained from EHR for developing an AI-driven acuity assessment score.
Transformers in Healthcare: A Survey
With Artificial Intelligence (AI) increasingly permeating various aspects of society, including healthcare, the adoption of the Transformers neural network architecture is rapidly changing many applications.
Predicting risk of delirium from ambient noise and light information in the ICU
This study shows that ambient light and noise intensities are strong predictors of long-term delirium incidence in the ICU.
SkeleMotion: A New Representation of Skeleton Joint Sequences Based on Motion Information for 3D Action Recognition
Due to the availability of large-scale skeleton datasets, 3D human action recognition has recently called the attention of computer vision community.
Ranked #16 on
Action Recognition
on NTU RGB+D 120
Human Activity Recognition Based on Wearable Sensor Data: A Standardization of the State-of-the-Art
Inspired by this, we conduct an extensive set of experiments that analyze different sample generation processes and validation protocols to indicate the vulnerable points in human activity recognition based on wearable sensor data.
A Content-Based Late Fusion Approach Applied to Pedestrian Detection
We propose a novel method called Content-Based Spatial Consensus (CSBC), which, in addition to relying on spatial consensus, considers the content of the detection windows to learn a weighted-fusion of pedestrian detectors.
