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Computer-aided decision support systems enable physicians to make more accurate clinical decisions and can significantly improve the quality of care provided to patients. However, prediction of classification confidence as the degree of reliability on the resulting predictions is a much needed step in clinical decision making. A recently developed technique called conformal prediction utilizes the...
In recent years, there has been a rapid growth in patient monitoring and medical data analysis using decision support systems, smart alarm monitoring, expert systems and many other computer aided protocols. The main goal of this study was to enhance the developed diagnostic alarm system for detecting critical events during anaesthesia. The proposed diagnostic alarm system is called Fuzzy logic monitoring...
Recent advances in body-worn sensor technology have increased the scope for harnessing quantitative information from the timed-up-and-go test (TUG), well beyond simply the time taken to perform the test. Previous research has shown that the quantitative TUG method can differentiate fallers from non-fallers with greater success than the manually timed TUG or the Berg Balance Test. In order to advance...
Identifying whether or not a retinal implant has malfunctioned after implantation is crucial for safety and efficacy testing in preclinical animal studies and clinical testing in human volunteers. Technical failure can lead to charge injection to areas other than the retina leading to a misjudgment of safety considerations or psychophysical results. This study assessed the feasibility of using standard...
Micro-air vehicles (MAVs) have attracted attention for their potential application to military applications, environmental sensing, and search and rescue missions. While progress is being made toward fabrication of a completely human-engineered MAV, another promising approach seeks to interface to, and take control of, an insect's nervous system. Cyborg insects take advantage of their innate exquisite...
A framework for online dynamic channel weighting is developed for the task of EEG-based neonatal seizure detection. The channel weights are computed on-the-fly by combining the up-to-now patient-specific history and the clinically-derived prior channel importance. These estimated time-varying weights are introduced within a Bayesian probabilistic framework to provide a channel-specific and thus patient-adaptive...
Current rehabilitation technology and techniques have proven effective at modifying and correcting gait abnormalities. They are however limited to laboratory and clinical settings, under the supervision of a specialist. Conventional techniques for quantifying gait asymmetries can be combined with sensory feedback methods to provide an intuitive and inexpensive feedback system for extra-clinical rehabilitation...
Falling in the home is one of the major challenges to independent living among older adults. The associated costs, coupled with a rapidly growing elderly population, are placing a burden on healthcare systems worldwide that will swiftly become unbearable. To facilitate expeditious emergency care, we have developed an artificially intelligent camera-based system that automatically detects if a person...
Machine-learning techniques have found widespread applications in bioinformatics. Such techniques provide invaluable insight on understanding the complex biomedical mechanisms and predicting the optimal individualized intervention for patients. In our case, we are particularly interested in developing an individualized clinical guideline on wheelchair tilt and recline usage for people with spinal...
This paper introduces WiiPD, an approach to home-based objective assessment of Parkinson's disease. WiiPD aims to make use of the many capabilities of the Nintendo Wii Remote in combination with a number of bespoke data gathering methods to provide a rich and engaging user experience that can capture a wide range of motor and non-motor metrics. In this paper we discuss the architecture of the approach,...
Multi-modal image registration is a momentous technology in medical image processing and analysis. In order to improve the robustness and accuracy of multi-modal rigid image registration, a novel learning-based dissimilarity function is proposed in this paper. This novel dissimilarity function is based on measuring the dissimilarity between the joint intensity distribution of the testing image pair...
Testing for nonlinearity is one of the most important preprocessing steps in nonlinear time series analysis. Typically, this is done by means of the linear surrogate data methods. But it is a known fact that the validity of the results heavily depends on the stationarity of the time series. Since most physiological signals are non-stationary, it is easy to falsely detect nonlinearity using the linear...
In this paper we present our investigations related to the optimization of hydrogels for the coating/packaging of biomedical devices. In order for hydrogels to be a viable interface/packaging material, a number of conditions must be met. We outline the tailoring of the mechanical properties of a HEMA based hydrogel by exploiting the influence of individual hydrogel components to achieve these requirements...
This paper presents a real-time implementation of an intent recognition system on one transfemoral (TF) amputee. Surface Electromyographic (EMG) signals recorded from residual thigh muscles and the ground reaction forces/moments collected from the prosthetic pylon were fused to identify three locomotion modes (level-ground walking, stair ascent, and stair descent) and tasks such as sitting and standing...
The Mobile Instrument for Motion Instruction and Correction (MIMIC) enables an expert (i.e., physical therapist) to map his/her movements to a trainee (i.e., patient) in a hands-free fashion. MIMIC comprises an Expert Module (EM) and a Trainee Module (TM); both modules include six-degree-of-freedom inertial measurement units, microcontrollers, and batteries. The TM also includes actuators that provide...
We describe a novel approach for screening retinal imagery to detect evidence of abnormalities. In this paper, we focus our efforts on age-related macular degeneration (AMD), a pathology that may often go undetected in the early or intermediate stages, and can lead to a neovascular form often resulting in blindness, if untreated. Our strategy for retinal anomaly detection is to employ a single class...
One of the primary challenges in noninvasive brain-computer interface (BCI) control is low information transfer rate (ITR). An approach that employs a power-based sequential hypothesis testing (SHT) technique is presented for real-time detection of motor commands. Electroencephalogram (EEG) recordings obtained during a BCI task were first analyzed with a hypothesis testing (HT) method. Using serial...
A previously developed neural-machine interface (NMI) based on neuromuscular-mechanical fusion has showed promise for recognizing user locomotion modes; however, errors of NMI during mode transitions were observed, which may challenge its real application. This study aimed to investigate whether or not the prior knowledge of walking environment could further improve the NMI performance. Linear Discriminant...
Comprehensive testing and evaluation of cardiovascular device function and performance is required prior to clinical implementation. Initial proof of concept investigations are conducted within in-vitro mock circulation loops, before proof of principle is demonstrated via in-vivo animal testing. To facilitate the rapid transition of cardiovascular devices through this development period, a testing...
Brain-computer interfaces (BCIs) exploring the auditory communication channel might be preferable for amyotrophic lateral sclerosis (ALS) patients with poor sight or with the visual system being occupied for other uses. Spatial attention was proven to be able to modulate the event-related potentials (ERPs); yet up to now, there is no auditory BCI based on virtual sound field. In this study, auditory...
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