AIMC Topic: Movement

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Unsupervised Phase Learning and Extraction from Repetitive Movements.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Phase extraction from repetitive movements is one crucial part in various applications such as interactive robotics, physical rehabilitation, or gait analysis. However, pre-existing automatic phase extraction techniques are specific to a target movem...

Human activity recognition from inertial sensor time-series using batch normalized deep LSTM recurrent networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In recent years machine learning methods for human activity recognition have been found very effective. These classify discriminative features generated from raw input sequences acquired from body-worn inertial sensors. However, it involves an explic...

Gated Recurrent Neural Networks for EMG-Based Hand Gesture Classification. A Comparative Study.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Electromyographic activities (EMG) generated during contraction of upper limb muscles can be mapped to distinct hand gestures and movements, posing them as a promising modality for prosthetic and cybernetic applications. This paper presents a compara...

Reduced Effort Does Not Imply Slacking: Responsiveness to Error Increases With Robotic Assistance.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
In both neurorehabilitation and functional augmentation, the patient or the user's muscular effort diminishes when the movement of their limb is supported by a robot. Is this relaxation a result of "slacking" by letting the robot take-over the moveme...

Fast social-like learning of complex behaviors based on motor motifs.

Physical review. E
Social learning is widely observed in many species. Less experienced agents copy successful behaviors exhibited by more experienced individuals. Nevertheless, the dynamical mechanisms behind this process remain largely unknown. Here we assume that a ...

Superior arm-movement decoding from cortex with a new, unsupervised-learning algorithm.

Journal of neural engineering
OBJECTIVE: The aim of this work is to improve the state of the art for motor-control with a brain-machine interface (BMI). BMIs use neurological recording devices and decoding algorithms to transform brain activity directly into real-time control of ...

Effects of integrating rhythmic arm swing into robot-assisted walking in patients with subacute stroke: a randomized controlled pilot study.

International journal of rehabilitation research. Internationale Zeitschrift fur Rehabilitationsforschung. Revue internationale de recherches de readaptation
This study aimed to identify the effects of rhythmic arm swing during robot-assisted walking training on balance, gait, motor function, and activities of daily living among patients with subacute stroke. Twenty patients with subacute stroke were recr...

Error-augmented bimanual therapy for stroke survivors.

NeuroRehabilitation
BACKGROUND: Stroke recovery studies have shown the efficacy of bimanual training on upper limb functional recovery and others have shown the efficacy of feedback technology that augments error.