Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions
Activity detection and classification using different sensor modalities have emerged as
revolutionary technology for real-time and autonomous monitoring in behaviour analysis …
revolutionary technology for real-time and autonomous monitoring in behaviour analysis …
Technological innovations to assess and include the human dimension in the building-performance loop: A review
The human dimension plays an essential role in the energy performance of buildings and is
considered as significant as technological advances. Several studies highlighted the …
considered as significant as technological advances. Several studies highlighted the …
Multi-sensor fusion based on multiple classifier systems for human activity identification
Multimodal sensors in healthcare applications have been increasingly researched because
it facilitates automatic and comprehensive monitoring of human behaviors, high-intensity …
it facilitates automatic and comprehensive monitoring of human behaviors, high-intensity …
Towards resolving the co-existing impacts of multiple dynamic factors on the performance of EMG-pattern recognition based prostheses
Abstract Background and Objective Mobility of subject (MoS) and muscle contraction force
variation (MCFV) have been shown to individually degrade the performance of multiple …
variation (MCFV) have been shown to individually degrade the performance of multiple …
Toward explainable AI-empowered cognitive health assessment
AR Javed, HU Khan, MKB Alomari… - Frontiers in Public …, 2023 - frontiersin.org
Explainable artificial intelligence (XAI) is of paramount importance to various domains,
including healthcare, fitness, skill assessment, and personal assistants, to understand and …
including healthcare, fitness, skill assessment, and personal assistants, to understand and …
Fusing wearable and remote sensing data streams by fast incremental learning with swarm decision table for human activity recognition
Human activity recognition (HAR) by machine learning finds wide applications ranging from
posture monitoring for healthcare and rehabilitation to suspicious or dangerous actions …
posture monitoring for healthcare and rehabilitation to suspicious or dangerous actions …
Decoding movement intent patterns based on spatiotemporal and adaptive filtering method towards active motor training in stroke rehabilitation systems
Upper extremity (UE) neuromuscular dysfunction critically affects post-stroke patients from
performing activities of daily life. In this regard, various rehabilitation robotics have been …
performing activities of daily life. In this regard, various rehabilitation robotics have been …
Automated human activity recognition by colliding bodies optimization-based optimal feature selection with recurrent neural network
P Khatiwada, A Chatterjee, M Subedi - arXiv preprint arXiv:2010.03324, 2020 - arxiv.org
In smart healthcare, Human Activity Recognition (HAR) is considered to be an efficient
model in pervasive computation from sensor readings. The Ambient Assisted Living (AAL) in …
model in pervasive computation from sensor readings. The Ambient Assisted Living (AAL) in …
Single-stage underwater target detection based on feature anchor frame double optimization network
H Ge, Y Dai, Z Zhu, X Zang - Sensors, 2022 - mdpi.com
Objective: The shallow underwater environment is complex, with problems of color shift,
uneven illumination, blurring, and distortion in the imaging process. These scenes are very …
uneven illumination, blurring, and distortion in the imaging process. These scenes are very …
Classifying 3D objects in LiDAR point clouds with a back-propagation neural network
Due to object recognition accuracy limitations, unmanned ground vehicles (UGVs) must
perceive their environments for local path planning and object avoidance. To gather high …
perceive their environments for local path planning and object avoidance. To gather high …