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Neural-machine interface (NMI) decoding errors challenge the clinical value of neural control of powered artificial legs, because these errors can dangerously disturb the user's walking balance, cause stumbles or falls, and thus threaten the user's confidence and safety in prosthesis use. Although extensive research efforts have been made to minimize the NMI decoding error rate, none of the current...
Diagnosis and monitoring of Parkinson's disease has a number of challenges as there is no definitive biomarker despite the broad range of symptoms. Research is ongoing to produce objective measures that can either diagnose Parkinson's or act as an objective decision support tool. Recent research on speech based measures have demonstrated promising results. This study aims to investigate the characteristics...
Valve-sparing aortic root reconstruction is an up- and-coming approach for patients suffering from aortic valve insufficiencies which promises to significantly reduce complications. However, the success of the treatment strongly depends on the challenging task of choosing the correct size of the prosthesis, for which, up to now, surgeons solely have to rely on their experience. Here, we present a...
We consider the detection of the control or idle state in an asynchronous Steady-state visually evoked potential (SSVEP)-based brain computer interface system. We propose a likelihood ratio test using Canonical Correlation Analysis (CCA) scores calculated from the EEG measurements. The test exploits the state-specific distributions of CCA scores. The algorithm was tested on offline measurements from...
High-density electrocorticography (ECoG) arrays are promising interfaces for high-resolution neural recording from the cortical surface. Commercial options for high-density arrays are limited, and historically tradeoffs must be made between spatial coverage and electrode density. However, thin-film technology is a promising alternative for generating electrode arrays capable of large area coverage...
The ability to perform postural transitions such as sit-to-stand is an accepted metric for functional independence. The number of transitions performed in real-life situations provides clinically useful information for individuals recovering from lower extremity injury or surgery. Performance deficits during these transitions are well correlated to negative outcomes in numerous populations. Thus,...
Study of genetic variants in the context of molecular networks has recently gained much attention. However, many of these studies suffer from the lack of functional information about the network rewiring effect of genetic variants. After large-scale homology modeling, plus extracting native structure from PDB database, we performed structure-based prediction about the rewiring effect using our SNP-IN...
Fully automatic localization of lumbar vertebrae from clinical X-ray images is very challenging due to the variation of X-ray quality, scale, contrast, number of visible vertebrae, etc. To overcome these challenges, we present a novel framework, where we accelerate a scale-invariant object detection method using Support Vector Machines (SVM) trained on Histogram of Oriented Gradients (HOG) features...
We propose an automatic spike sorting approach for the data recorded from a microelectrode array during visual stimulation of wild type retinas with tiled spot stimuli. The approach first detects individual spikes per electrode by their signature local minima. With the mixture probability distribution of the local minima estimated afterwards, it applies a minimum-squared-error clustering algorithm...
The performance of the myoelectric pattern recognition system sharply decreases when working in various limb positions. The issue can be solved by cumbersome training procedure that can anticipate all possible future situations. However, this procedure will sacrifice the comfort of the user. In addition, many unpredictable scenarios may be met in the future. This paper proposed a new adaptive myoelectric...
The use of abstract chemical reaction networks (CRNs) as a modelling and design framework for the implementation of computing and control circuits using enzyme-free, entropy driven DNA strand displacement (DSD) reactions is starting to garner widespread attention in the area of synthetic biology. Previous work in this area has demonstrated the theoretical plausibility of using this approach to design...
Monitoring the spontaneous kicking patterns of infants can give insight into their development. A computer vision based method for estimating the pose of an infant's leg from range images is presented in this paper. After some manual inputs for initialization, the range data associated with the infant is extracted. The method uses Robust Point Set Registration (RPSR) to fit an articulated model to...
The minimum variance (MV) beamformer is a method that has the potential to enhance the resolution and contrast of ultrasound images. However, it suffers from sensitivity to speed of sound errors and aberration. Although there have been several studies on the application of phase aberration correction (PAC) methods to conventional delay-and-sum (DAS) beamforming, the benefits of PAC methods in mitigating...
This paper presents a novel automatic quantitative measurement method for assessment of the performance of image registration algorithms designed for registering retina fundus images. To achieve automatic quantitative measurement, we propose the use of edges and edge dissimilarity measure for determining the performance of retina image registration algorithms. Our input is the registered pair of retina...
This paper deals with a blind hybrid digital watermarking algorithm for the copyright protection and authentication of magnetic resonance tomography images. Medical image watermarking requires extreme care when embedding watermark information in the medical images, to protect the image quality from being violated and to avoid the wrong diagnosis that might occur. The proposed algorithm contains robust...
In this paper we apply techniques for numerical estimation of system resolution from imaging, to the regression problem of relating biological data to phenotypes. Our approach can be viewed as an extension of Backus-Gilbert theory, which attempts to find the most concentrated estimator that may be reliably computed in an inverse problem. Applied to a regression model, we estimate a minimal combination...
Accurate timing of interventions during the gait cycle are critical for optimal efficacy of assistive devices, e.g., to reduce the metabolic cost of walking. However, timing control generally relies on methods that can neither account for changes in the stride duration over time due to different walking speeds, nor reject isolated abnormal strides, which could be caused by stumbling or obstacle avoidance...
It is known that signs of (early) auditory selective attention are reflected in the N1-wave of auditory late potentials. In recent years, we have analyzed this N1-effect using multiscale neurofunctional modeling and (instantaneous) phase synchronization measures of Hardy space mapped data. To acquire the electroencephalographic data in dichotic listening, we repeated the seminal experiment of Hillyard...
The fundamental objective in non-invasive myoelectric prosthesis control is to determine the user's intended movements from corresponding skin-surface recorded electromyographic (sEMG) activation signals as quickly and accurately as possible. Linear Discriminant Analysis (LDA) has emerged as the de facto standard for real-time movement classification due to its ease of use, calculation speed, and...
Frailty is an increasingly common geriatric condition that results in an increased risk of adverse health outcomes such as falls. The most widely-used means of detecting frailty is the Fried phenotype, which includes several objective measures such as grip strength and gait velocity. One method of screening for falls is to measure balance, which can be done by a range of techniques including the assessment...
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