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Posture

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A Blanket Accommodative Sleep Posture Classification System Using an Infrared Depth Camera: A Deep Learning Approach with Synthetic Augmentation of Blanket Conditions.

Sensors (Basel, Switzerland)
Surveillance of sleeping posture is essential for bed-ridden patients or individuals at-risk of falling out of bed. Existing sleep posture monitoring and classification systems may not be able to accommodate the covering of a blanket, which represent...

A mechatronics data collection, image processing, and deep learning platform for clinical posture analysis: a technical note.

Physical and engineering sciences in medicine
Static and dynamic posture analysis was a critical clinical examination in physiotherapy and rehabilitation. It was a time-consuming task for clinicians, so a semi-automatic method can facilitate this process as well as provide well-documented medica...

Can an android's posture and movement discriminate against the ambiguous emotion perceived from its facial expressions?

PloS one
Expressing emotions through various modalities is a crucial function not only for humans but also for robots. The mapping method from facial expressions to the basic emotions is widely used in research on robot emotional expressions. This method clai...

LiftPose3D, a deep learning-based approach for transforming two-dimensional to three-dimensional poses in laboratory animals.

Nature methods
Markerless three-dimensional (3D) pose estimation has become an indispensable tool for kinematic studies of laboratory animals. Most current methods recover 3D poses by multi-view triangulation of deep network-based two-dimensional (2D) pose estimate...

Visual Information Features and Machine Learning for Wushu Arts Tracking.

Journal of healthcare engineering
Martial arts tracking is an important research topic in computer vision and artificial intelligence. It has extensive and vital applications in video monitoring, interactive animation and 3D simulation, motion capture, and advanced human-computer int...

A Deep-Learning Based Posture Detection System for Preventing Telework-Related Musculoskeletal Disorders.

Sensors (Basel, Switzerland)
The change from face-to-face work to teleworking caused by the pandemic has induced multiple workers to spend more time than usual in front of a computer; in addition, the sudden installation of workstations in homes means that not all of them meet t...

Estimating Human Pose Efficiently by Parallel Pyramid Networks.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Good performance and high efficiency are both critical for estimating human pose in practice. Recent state-of-the-art methods have greatly boosted the pose detection accuracy through deep convolutional neural networks, however, the strong performance...

Deep neural network approach for estimating the three-dimensional human center of mass using joint angles.

Journal of biomechanics
Human body center of mass location plays an essential role in physical therapy, especially in investigating a subject's capability to maintain balance. However, its estimation can be a very complex, costly, and time-consuming process. To overcome the...

Exploring a Fuzzy Rule Inferred ConvLSTM for Discovering and Adjusting the Optimal Posture of Patients with a Smart Medical Bed.

International journal of environmental research and public health
Several countries nowadays are facing a tough social challenge caused by the aging population. This public health issue continues to impose strain on clinical healthcare, such as the need to prevent terminal patients' pressure ulcers. Provocative app...

Image-Guided Human Reconstruction via Multi-Scale Graph Transformation Networks.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
3D human reconstruction from a single image is a challenging problem. Existing methods have difficulties to infer 3D clothed human models with consistent topologies for various poses. In this paper, we propose an efficient and effective method using ...