AIMC Topic: Movement

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Analysis of Motor Control and Learning in Human-Robot Interaction during Game Guided Movements.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Robotic devices can be used in upper limb rehabilitation in order to help the total or partial functional recovery. Robots can perform repetitive activities for a long period of time, which may be beneficial for rehabilitation processes. In this cont...

RCIT: A Robust Catadioptric-based Instrument 3D Tracking Method For Microsurgical Instruments In a Single-Camera System.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The field of robotic microsurgery and micro-manipulation has undergone a profound evolution in recent years, particularly with regard to the accuracy, precision, versatility, and dexterity. These advancements have the potential to revolutionize high-...

An Attention-based Bidirectional LSTM Model for Continuous Cross-Subject Estimation of Knee Joint Angle during Running from sEMG Signals.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Accurate and robust estimation of joint kinematics via surface electromyogram (sEMG) signals provides a human-machine interaction (HMI)-based method that can be used to adequately control rehabilitation robots while performing complex movements, such...

A Deep Learning Approach for Grading of Motor Impairment Severity in Parkinson's Disease.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Objective and quantitative monitoring of movement impairments is crucial for detecting progression in neurological conditions such as Parkinson's disease (PD). This study examined the ability of deep learning approaches to grade motor impairment seve...

Validation of the Human Arm Stiffness Estimation Method Developed for Overground Physical Interaction Experiments.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
To build a physically interactive robot for overground applications, it is crucial to first understand the biomechanics of humans underlying overground physical human-robot interaction (pHRI) tasks. Estimating human arm stiffness during overground in...

Deep-Learning Markerless Tracking of Infant General Movements using Standard Video Recordings.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Monitoring spontaneous General Movements (GM) of infants 6-20 weeks post-term age is a reliable tool to assess the quality of neurodevelopment in early infancy. Abnormal or absent GMs are reliable prognostic indicators of whether an infant is at risk...

Natural Grasp Intention Recognition Based on Gaze in Human-Robot Interaction.

IEEE journal of biomedical and health informatics
OBJECTIVE: While neuroscience research has established a link between vision and intention, studies on gaze data features for intention recognition are absent. The majority of existing gaze-based intention recognition approaches are based on delibera...

A low-frequency acceleration sensor inspired by saccule in human vestibule.

The Review of scientific instruments
A human vestibular system is a group of devices in the inner ear that govern the balancing movement of the head, in which the saccule is responsible for sensing gravity accelerations. Imitating the sensing principle and structure of the Sensory Hair ...

Upper Limb Movement Decoding Scheme Based on Surface Electromyography Using Attention-Based Kalman Filter Scheme.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Convolutional neural network (CNN)-based models are widely used in human movement decoding based on surface electromyography. However, they capture only the spatial information of the surface electromyography and lack prior knowledge of the system, r...

Classification of EEG signals related to real and imagery knee movements using deep learning for brain computer interfaces.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Non-invasive Brain-Computer Interface (BCI) uses an electroencephalogram (EEG) to obtain information on brain neural activity. Because EEG can be contaminated by various artifacts during the collection process, it has primarily evolved in...