Embedded machine learning using microcontrollers in wearable and ambulatory systems for health and care applications: A review
MS Diab, E Rodriguez-Villegas - IEEE Access, 2022 - ieeexplore.ieee.org
The use of machine learning in medical and assistive applications is receiving significant
attention thanks to the unique potential it offers to solve complex healthcare problems for …
attention thanks to the unique potential it offers to solve complex healthcare problems for …
A review of wearable sensors based fall-related recognition systems
J Liu, X Li, S Huang, R Chao, Z Cao, S Wang… - … Applications of Artificial …, 2023 - Elsevier
Falls are an important factor in significantly deteriorating quality of life of older adults,
consequently leading to both physical and psychological harm. A wearable-based fall …
consequently leading to both physical and psychological harm. A wearable-based fall …
A novel feature extraction method for preimpact fall detection system using deep learning and wearable sensors
Fall detection and prevention are crucial in elderly healthcare and humanoid robotic
research as they help mitigate the damaging after-effects of falls. In this work, we have …
research as they help mitigate the damaging after-effects of falls. In this work, we have …
Eeg-based alzheimer's disease recognition using robust-pca and lstm recurrent neural network
M Alessandrini, G Biagetti, P Crippa, L Falaschetti… - Sensors, 2022 - mdpi.com
The use of electroencephalography (EEG) has recently grown as a means to diagnose
neurodegenerative pathologies such as Alzheimer's disease (AD). AD recognition can …
neurodegenerative pathologies such as Alzheimer's disease (AD). AD recognition can …
A large-scale open motion dataset (KFall) and benchmark algorithms for detecting pre-impact fall of the elderly using wearable inertial sensors
Research on pre-impact fall detection with wearable inertial sensors (detecting fall accidents
prior to body-ground impacts) has grown rapidly in the past decade due to its great potential …
prior to body-ground impacts) has grown rapidly in the past decade due to its great potential …
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 …
and other physiological parameters and is commonly implemented in wearable devices …
A practical wearable fall detection system based on tiny convolutional neural networks
Falls are a major public health problem in a rapidly aging society due to their high
prevalence and severe consequences among the older population. Therefore, automatic fall …
prevalence and severe consequences among the older population. Therefore, automatic fall …
Design of inception with deep convolutional neural network based fall detection and classification model
K Durga Bhavani, M Ferni Ukrit - Multimedia Tools and Applications, 2024 - Springer
Falling is the most serious health problem for elderly population resulting in serious injuries,
if not treated quickly. As the world population gets increased, the number of serious falls and …
if not treated quickly. As the world population gets increased, the number of serious falls and …
Accelerometer-based fall detection using machine learning: Training and testing on real-world falls
Falling is a significant health problem. Fall detection, to alert for medical attention, has been
gaining increasing attention. Still, most of the existing studies use falls simulated in a …
gaining increasing attention. Still, most of the existing studies use falls simulated in a …
Effects of sliding window variation in the performance of acceleration-based human activity recognition using deep learning models
Deep learning (DL) models are very useful for human activity recognition (HAR); these
methods present better accuracy for HAR when compared to traditional, among other …
methods present better accuracy for HAR when compared to traditional, among other …