A Shrestha, H Li, J Le Kernec… - IEEE Sensors …, 2020 - ieeexplore.ieee.org
Recognition of human movements with radar for ambient activity monitoring is a developed area of research that yet presents outstanding challenges to address. In real environments …
This paper presents a framework based on multilayer bi-LSTM network (bidirectional Long Short-Term Memory) for multimodal sensor fusion to sense and classify daily activities' …
This article covers radar signal processing for sensing in the context of assisted living (AL). This is presented through three example applications: human activity recognition (HAR) for …
Fall detection is a major challenge for researchers. Indeed, a fall can cause injuries such as femoral neck fracture, brain hemorrhage, or skin burns, leading to significant pain. However …
Indoor human activity recognition is actively studied as part of creating various intelligent systems with applications in smart home and office, smart health, internet of things, etc …
FJ Abdu, Y Zhang, Z Deng - IEEE Sensors Journal, 2022 - ieeexplore.ieee.org
Fall is a challenging task that poses a great danger to the elderly person's health as they carry out their daily routines and activities and could lead to serious injuries, long …
SOH Madgwick, S Wilson, R Turk… - IEEE/ASME …, 2020 - ieeexplore.ieee.org
Inertial sensing suites now permeate all forms of smart automation, yet a plateau exists in the real-world derivation of global orientation. Magnetic field fluctuations and inefficient …
This paper presents different information fusion approaches to classify human gait patterns and falls in a radar sensors network. The human gaits classified in this work are both …
W Ding, X Guo, G Wang - IEEE Transactions on Aerospace and …, 2021 - ieeexplore.ieee.org
This article concerns the issue of how to combine the multidomainradar information, including range–Doppler, time–Doppler, and time–range, for human activity recognition …