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This paper presents a novel method for ECG baseline drift removal while preserving the integrity of the ST segment. Baseline estimation is achieved by tracking 3 isoelectric points within the ECG waveform as fiducial markers used in an interpolation filter. These points are determined relative to the QRS complex, which is extracted using a known method (Pan-Tompkins algorithm). The proposed algorithm...
This paper explores how noise can improve classification accuracy of motor imagery classification using an ensemble support vector machine (ESVM) classifier. We add white Gaussian noise to the EEG signals and use them with the original signal data set for the ESVM training process. The ESVM classifier uses coefficients of the discrete wavelet transform (DWT) and coefficients of the autoregressive...
This paper presents a computationally-efficient compressive sampling system for photoplethysmogram (PPG) signals. The approach relies on the exploration of the Discrete Cosine Transform (DCT) as sparsifying basis for reconstruction of randomly sampled signals, along with an overlapped window reconstruction algorithm which improves reconstruction accuracy of shorter windows, without sacrificing reconstruction...
This paper presents an efficient VLSI implementation of a singular value decomposition (SVD) processor of on-line recursive independent component analysis (ORICA) for use in a real-time electroencephalography (EEG) system. ICA is a well-known method for blind source separation (BBS), which helps to obtain clear EEG signals without artifacts. In general, computations of ORICA are complicated and the...
We propose an algorithm that uses pressure image data to detect a person's sleeping posture and identifies different body limbs. Our algorithm can be used in monitoring bed-bound patients and assessing the risk of pressure ulceration. We used a GMM-based clustering approach for concurrent posture classification and limb identification. Our proposed technique, applied on 9 healthy subjects instructed...
This paper presents the design and implementation of a real-time epilepsy detection filter that is suitable for closed-loop seizure suppression. The design aims to minimize the detection delay, while a reasonable average detection rate is obtained. The filter is based on a complex Morlet wavelet and uses an adaptive thresholding strategy for the seizure discrimination. This relatively simple configuration...
This paper presents an event-driven categorization system which processes the address events from a Dynamic Vision Sensor. Using neuromorphic processing, cortex-like spike-based features are extracted by an event-driven MAX-like convolutional network. The extracted spike patterns are then classified by an Online Sequential Extreme Learning Machine with Auto Encoder. Using a Lookup Table, we achieve...
Real-time visual identification and tracking of objects is a computationally intensive task, particularly in cluttered environments which contain many visual distracters. In this paper we describe a real-time bio-inspired system for object tracking and identification which combines an event-based vision sensor with a convolutional neural network running on FPGA for recognition. The event-based vision...
Onset detection is one of the main issues towards self-paced BCIs that can be used outside research settings. For this reason, this paper suggests a potential solution for onset detection problem by discriminating between speech related events. In this study, overt, inhibited overt and covert states were tested to classify from idle state in an off-line setting. Autoregressive model coefficients were...
A wearable microsystem for low-latency automatic sleep stage classification and REM sleep detection in rodents is presented. The detection algorithm is implemented digitally to achieve low latency and is optimized for low complexity and power consumption. The algorithm uses both EEG and EMG signals as inputs. Experimental results using off-line signals from nine mice show REM detection sensitivity...
Sensory information, such as the tactile or proprioceptive signals, helps motor brain-machine interface (mBMI) work more naturally. Before applying sensory feedback, we need to explore if the neural activities are discriminative to different stimuli during a BMI task. Previous studies on the cortical discrimination are mainly focused on the rat whisker system. In this paper, we design a BMI task,...
This paper presents an error-resilient wavelet-based ECG processor under voltage overscaling (VOS). A novel predictor based on weighted-average bilateral estimation (WBE) is proposed and used for algorithmic noise tolerance (ANT) that compensates the VOS-incurred errors. A two-stage ANT mechanism using heterogeneous error-detection techniques is developed, which enhances the robustness of ANT. This...
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