Deep learning algorithms for human activity recognition using mobile and wearable sensor networks: State of the art and research challenges
Human activity recognition systems are developed as part of a framework to enable
continuous monitoring of human behaviours in the area of ambient assisted living, sports …
continuous monitoring of human behaviours in the area of ambient assisted living, sports …
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 …
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 …
WiWeHAR: Multimodal human activity recognition using Wi-Fi and wearable sensing modalities
Robust and accurate human activity recognition (HAR) systems are essential to many
human-centric services within active assisted living and healthcare facilities. Traditional …
human-centric services within active assisted living and healthcare facilities. Traditional …
A robust deep learning approach for position-independent smartphone-based human activity recognition
B Almaslukh, AM Artoli, J Al-Muhtadi - Sensors, 2018 - mdpi.com
Recently, modern smartphones equipped with a variety of embedded-sensors, such as
accelerometers and gyroscopes, have been used as an alternative platform for human …
accelerometers and gyroscopes, have been used as an alternative platform for human …
A location-based orientation-aware recommender system using IoT smart devices and Social Networks
The rapid development of IoT sensors and data provided by Social Networks has
necessitated the fast development of recommender systems as they can be used as a tool to …
necessitated the fast development of recommender systems as they can be used as a tool to …
Analysis of machine learning-based assessment for elbow spasticity using inertial sensors
Spasticity is a frequently observed symptom in patients with neurological impairments.
Spastic movements of their upper and lower limbs are periodically measured to evaluate …
Spastic movements of their upper and lower limbs are periodically measured to evaluate …
Smartphone motion sensor-based complex human activity identification using deep stacked autoencoder algorithm for enhanced smart healthcare system
Human motion analysis using a smartphone-embedded accelerometer sensor provided
important context for the identification of static, dynamic, and complex sequence of activities …
important context for the identification of static, dynamic, and complex sequence of activities …
Data augmentation for inertial sensor-based gait deep neural network
L Tran, D Choi - IEEE Access, 2020 - ieeexplore.ieee.org
Inertial sensor-based gait has been discovered as an attractive method for user recognition.
Recently, with the approaching of deep learning techniques, new state-of-the-art researches …
Recently, with the approaching of deep learning techniques, new state-of-the-art researches …