AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Accidental Falls

Showing 71 to 80 of 189 articles

Clear Filters

Domain-Adaptive Fall Detection Using Deep Adversarial Training.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Fall detection (FD) systems are important assistive technologies for healthcare that can detect emergency fall events and alert caregivers. However, it is not easy to obtain large-scale annotated fall events with various specifications of sensors or ...

The Performance of Post-Fall Detection Using the Cross-Dataset: Feature Vectors, Classifiers and Processing Conditions.

Sensors (Basel, Switzerland)
In this study, algorithms to detect post-falls were evaluated using the cross-dataset according to feature vectors (time-series and discrete data), classifiers (ANN and SVM), and four different processing conditions (normalization, equalization, incr...

XGBoost based machine learning approach to predict the risk of fall in older adults using gait outcomes.

Scientific reports
This study aimed to identify the optimal features of gait parameters to predict the fall risk level in older adults. The study included 746 older adults (age: 63-89 years). Gait tests (20 m walkway) included speed modification (slower, preferred, and...

High Accuracy WiFi-Based Human Activity Classification System with Time-Frequency Diagram CNN Method for Different Places.

Sensors (Basel, Switzerland)
Older people are very likely to fall, which is a significant threat to the health. However, falls are preventable and are not necessarily an inevitable part of aging. Many different fall detection systems have been developed to help people avoid fall...

Revealing posturographic profile of patients with Parkinsonian syndromes through a novel hypothesis testing framework based on machine learning.

PloS one
Falling in Parkinsonian syndromes (PS) is associated with postural instability and consists a common cause of disability among PS patients. Current posturographic practices record the body's center-of-pressure displacement (statokinesigram) while the...

Comprehensive Review of Vision-Based Fall Detection Systems.

Sensors (Basel, Switzerland)
Vision-based fall detection systems have experienced fast development over the last years. To determine the course of its evolution and help new researchers, the main audience of this paper, a comprehensive revision of all published articles in the m...

A Machine Learning Multi-Class Approach for Fall Detection Systems Based on Wearable Sensors with a Study on Sampling Rates Selection.

Sensors (Basel, Switzerland)
Falls are dangerous for the elderly, often causing serious injuries especially when the fallen person stays on the ground for a long time without assistance. This paper extends our previous work on the development of a Fall Detection System (FDS) usi...

An eight-camera fall detection system using human fall pattern recognition via machine learning by a low-cost android box.

Scientific reports
Falls are a leading cause of unintentional injuries and can result in devastating disabilities and fatalities when left undetected and not treated in time. Current detection methods have one or more of the following problems: frequent battery replace...

Deep Convolutional and LSTM Networks on Multi-Channel Time Series Data for Gait Phase Recognition.

Sensors (Basel, Switzerland)
With an ageing society comes the increased prevalence of gait disorders. The restriction of mobility leads to a considerable reduction in the quality of life, because associated falls increase morbidity and mortality. Consideration of gait analysis d...

Hardware-Based Hopfield Neuromorphic Computing for Fall Detection.

Sensors (Basel, Switzerland)
With the popularity of smart wearable systems, sensor signal processing poses more challenges to machine learning in embedded scenarios. For example, traditional machine-learning methods for data classification, especially in real time, are computati...