AIMC Topic: Signal Processing, Computer-Assisted

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Command Filter-Based Adaptive Neural Tracking Controller Design for Uncertain Switched Nonlinear Output-Constrained Systems.

IEEE transactions on cybernetics
In this paper, a new adaptive approximation-based tracking controller design approach is developed for a class of uncertain nonlinear switched lower-triangular systems with an output constraint using neural networks (NNs). By introducing a novel barr...

Adaptive Neural Synchronization Control for Bilateral Teleoperation Systems With Time Delay and Backlash-Like Hysteresis.

IEEE transactions on cybernetics
This paper considers the master and slave synchronization control for bilateral teleoperation systems with time delay and backlash-like hysteresis. Based on radial basis functions neural networks' approximation capabilities, two improved adaptive neu...

Unsupervised frequency-recognition method of SSVEPs using a filter bank implementation of binary subband CCA.

Journal of neural engineering
OBJECTIVE: Recently developed effective methods for detection commands of steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) that need calibration for visual stimuli, which cause more time and fatigue prior to the use, ...

Deep Learning and Insomnia: Assisting Clinicians With Their Diagnosis.

IEEE journal of biomedical and health informatics
Effective sleep analysis is hampered by the lack of automated tools catering to disordered sleep patterns and cumbersome monitoring hardware. In this paper, we apply deep learning on a set of 57 EEG features extracted from a maximum of two EEG channe...

A Deep Learning Approach to on-Node Sensor Data Analytics for Mobile or Wearable Devices.

IEEE journal of biomedical and health informatics
The increasing popularity of wearable devices in recent years means that a diverse range of physiological and functional data can now be captured continuously for applications in sports, wellbeing, and healthcare. This wealth of information requires ...

Equivalent Neural Network Optimal Coefficients Using Forgetting Factor with Sliding Modes.

Computational intelligence and neuroscience
The Artificial Neural Network (ANN) concept is familiar in methods whose task is, for example, the identification or approximation of the outputs of complex systems difficult to model. In general, the objective is to determine online the adequate par...

Sensor-Based Gait Parameter Extraction With Deep Convolutional Neural Networks.

IEEE journal of biomedical and health informatics
Measurement of stride-related, biomechanical parameters is the common rationale for objective gait impairment scoring. State-of-the-art double-integration approaches to extract these parameters from inertial sensor data are, however, limited in their...

A Model-Based Machine Learning Approach to Probing Autonomic Regulation From Nonstationary Vital-Sign Time Series.

IEEE journal of biomedical and health informatics
Physiological variables, such as heart rate (HR), blood pressure (BP) and respiration (RESP), are tightly regulated and coupled under healthy conditions, and a break-down in the coupling has been associated with aging and disease. We present an appro...

Fuzzy Computing Model of Activity Recognition on WSN Movement Data for Ubiquitous Healthcare Measurement.

Sensors (Basel, Switzerland)
Ubiquitous health care (UHC) is beneficial for patients to ensure they complete therapeutic exercises by self-management at home. We designed a fuzzy computing model that enables recognizing assigned movements in UHC with privacy. The movements are m...