AIMC Topic: Spatio-Temporal Analysis

Clear Filters Showing 111 to 120 of 144 articles

Multilevel Features for Sensor-Based Assessment of Motor Fluctuation in Parkinson's Disease Subjects.

IEEE journal of biomedical and health informatics
Motor fluctuations are a frequent complication in patients with Parkinson's disease (PD) where the response to medication fluctuates between ON states (medication working) and OFF states (medication has worn off). This paper describes a new data anal...

Spatial-temporal variation characteristics and evolution of the global industrial robot trade: A complex network analysis.

PloS one
Industrial robots are a strategic future technology and an important part of the development of artificial intelligence, and they are a necessary means for the intelligent transformation of manufacturing industry. Based on global industrial robot tra...

Spatiotemporal gait characteristic changes with gait training using the hybrid assistive limb for chronic stroke patients.

Gait & posture
BACKGROUND: Robotic rehabilitation has been attracting attention as a means to carry out "intensive", "repetitive", "task-specific", gait training. The newly developed robotic device, the Hybrid Assistive Limb (HAL), is thought to have the possibilit...

Making Sense of Spatio-Temporal Preserving Representations for EEG-Based Human Intention Recognition.

IEEE transactions on cybernetics
Brain-computer interface (BCI) is a system empowering humans to communicate with or control the outside world with exclusively brain intentions. Electroencephalography (EEG)-based BCI is one of the promising solutions due to its convenient and portab...

Real-time tracking of surgical instruments based on spatio-temporal context and deep learning.

Computer assisted surgery (Abingdon, England)
ABSTARCT Real-time tool tracking in minimally invasive-surgery (MIS) has numerous applications for computer-assisted interventions (CAIs). Visual tracking approaches are a promising solution to real-time surgical tool tracking, however, many approach...

Deep learning and process understanding for data-driven Earth system science.

Nature
Machine learning approaches are increasingly used to extract patterns and insights from the ever-increasing stream of geospatial data, but current approaches may not be optimal when system behaviour is dominated by spatial or temporal context. Here, ...

A Survey of the Techniques for The Identification and Classification of Human Actions from Visual Data.

Sensors (Basel, Switzerland)
Recognition of human actions form videos has been an active area of research because it has applications in various domains. The results of work in this field are used in video surveillance, automatic video labeling and human-computer interaction, am...

3-D Quantification of Filopodia in Motile Cancer Cells.

IEEE transactions on medical imaging
We present a 3D bioimage analysis workflow to quantitatively analyze single, actin-stained cells with filopodial protrusions of diverse structural and temporal attributes, such as number, length, thickness, level of branching, and lifetime, in time-l...

Learning of spatiotemporal patterns in a spiking neural network with resistive switching synapses.

Science advances
The human brain is a complex integrated spatiotemporal system, where space (which neuron fires) and time (when a neuron fires) both carry information to be processed by cognitive functions. To parallel the energy efficiency and computing functionalit...