AIMC Topic: Posture

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Application of structured support vector machine backpropagation to a convolutional neural network for human pose estimation.

Neural networks : the official journal of the International Neural Network Society
In this study, for the first time, we show how to formulate a structured support vector machine (SSVM) as two layers in a convolutional neural network, where the top layer is a loss augmented inference layer and the bottom layer is the normal convolu...

Understanding human intention by connecting perception and action learning in artificial agents.

Neural networks : the official journal of the International Neural Network Society
To develop an advanced human-robot interaction system, it is important to first understand how human beings learn to perceive, think, and act in an ever-changing world. In this paper, we propose an intention understanding system that uses an Object A...

In-lab versus at-home activity recognition in ambulatory subjects with incomplete spinal cord injury.

Journal of neuroengineering and rehabilitation
BACKGROUND: Although commercially available activity trackers can aid in tracking therapy and recovery of patients, most devices perform poorly for patients with irregular movement patterns. Standard machine learning techniques can be applied on reco...

Arbitrary Symmetric Running Gait Generation for an Underactuated Biped Model.

PloS one
This paper investigates generating symmetric trajectories for an underactuated biped during the stance phase of running. We use a point mass biped (PMB) model for gait analysis that consists of a prismatic force actuator on a massless leg. The signif...

Application of Machine Learning in Postural Control Kinematics for the Diagnosis of Alzheimer's Disease.

Computational intelligence and neuroscience
The use of wearable devices to study gait and postural control is a growing field on neurodegenerative disorders such as Alzheimer's disease (AD). In this paper, we investigate if machine-learning classifiers offer the discriminative power for the di...

Estimation of Full-Body Poses Using Only Five Inertial Sensors: An Eager or Lazy Learning Approach?

Sensors (Basel, Switzerland)
Human movement analysis has become easier with the wide availability of motion capture systems. Inertial sensing has made it possible to capture human motion without external infrastructure, therefore allowing measurements in any environment. As high...

Application of Machine Learning Approaches for Classifying Sitting Posture Based on Force and Acceleration Sensors.

BioMed research international
Occupational musculoskeletal disorders, particularly chronic low back pain (LBP), are ubiquitous due to prolonged static sitting or nonergonomic sitting positions. Therefore, the aim of this study was to develop an instrumented chair with force and a...

A new 3D center of mass control approach for FES-assisted standing: First experimental evaluation with a humanoid robot.

Medical engineering & physics
This paper proposes a new control framework to restore the coordination between upper (functional) and lower (paralyzed) limbs in the context of functional electrical stimulation in completely paraplegic individuals. A kinematic decoupling between th...

Artificial neural networks to predict 3D spinal posture in reaching and lifting activities; Applications in biomechanical models.

Journal of biomechanics
Spinal posture is a crucial input in biomechanical models and an essential factor in ergonomics investigations to evaluate risk of low back injury. In vivo measurement of spinal posture through the common motion capture techniques is limited to equip...

Robots Learn to Recognize Individuals from Imitative Encounters with People and Avatars.

Scientific reports
Prior to language, human infants are prolific imitators. Developmental science grounds infant imitation in the neural coding of actions, and highlights the use of imitation for learning from and about people. Here, we used computational modeling and ...