AIMC Topic: Signal Processing, Computer-Assisted

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Materials science. Materials that couple sensing, actuation, computation, and communication.

Science (New York, N.Y.)
Tightly integrating sensing, actuation, and computation into composites could enable a new generation of truly smart material systems that can change their appearance and shape autonomously. Applications for such materials include airfoils that chang...

Multistep prediction of physiological tremor based on machine learning for robotics assisted microsurgery.

IEEE transactions on cybernetics
For effective tremor compensation in robotics assisted hand-held device, accurate filtering of tremulous motion is necessary. The time-varying unknown phase delay that arises due to both software (filtering) and hardware (sensors) in these robotics i...

Automatic Wheezing Detection Based on Signal Processing of Spectrogram and Back-Propagation Neural Network.

Journal of healthcare engineering
Wheezing is a common clinical symptom in patients with obstructive pulmonary diseases such as asthma. Automatic wheezing detection offers an objective and accurate means for identifying wheezing lung sounds, helping physicians in the diagnosis, long-...

Shifting the balance of human standing: Inter-limb coordination for the control of a robotic balance simulation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Learning to maintain standing balance in the presence of a paretic limb is an important recovery process for many stroke survivors. In this study, we used a robotic balance simulator to investigate whether manipulating medial-lateral or anterior-post...

Seizure detection using regression tree based feature selection and polynomial SVM classification.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This paper presents a novel patient-specific algorithm for detection of seizures in epileptic patients with low hardware complexity and low power consumption. In the proposed approach, we first compute the spectrogram of the input fragmented EEG sign...

On the use of convolutional neural networks and augmented CSP features for multi-class motor imagery of EEG signals classification.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Learning the deep structures and unknown correlations is important for the detection of motor imagery of EEG signals (MI-EEG). This study investigates the use of convolutional neural networks (CNNs) for the classification of multi-class MI-EEG signal...

Automatic identification of artifacts in electrodermal activity data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Recently, wearable devices have allowed for long term, ambulatory measurement of electrodermal activity (EDA). Despite the fact that ambulatory recording can be noisy, and recording artifacts can easily be mistaken for a physiological response during...

Novel images extraction model using improved delay vector variance feature extraction and multi-kernel neural network for EEG detection and prediction.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Advanced intelligent methodologies could help detect and predict diseases from the EEG signals in cases the manual analysis is inefficient available, for instance, the epileptic seizures detection and prediction. This is because the diver...

Sampling from Determinantal Point Processes for Scalable Manifold Learning.

Information processing in medical imaging : proceedings of the ... conference
High computational costs of manifold learning prohibit its application for large datasets. A common strategy to overcome this problem is to perform dimensionality reduction on selected landmarks and to successively embed the entire dataset with the N...

Modulation of grasping force in prosthetic hands using neural network-based predictive control.

Methods in molecular biology (Clifton, N.J.)
This chapter describes the implementation of a neural network-based predictive control system for driving a prosthetic hand. Nonlinearities associated with the electromechanical aspects of prosthetic devices present great challenges for precise contr...