Computer Vision-Based Carbohydrate Estimation for Type 1 Diabetic Patients Using Smartphones

Background: Individuals with type 1 diabetes (T1D) have to count the carbohydrates (CHOs) of their meal to estimate the prandial insulin dose needed to compensate for the meal’s effect on blood glucose levels. CHO counting is very challenging but also crucial, since an error of 20 grams can substantially impair postprandial control. Method: The GoCARB system is a smartphone application designed to support T1D patients with CHO counting of nonpacked foods. In a typical scenario, the user places a reference card next to the dish and acquires 2 images with his/her smartphone. From these images, the plate is detected and the different food items on the plate are automatically segmented and recognized, while their 3D shape is reconstructed. Finally, the food volumes are calculated and the CHO content is estimated by combining the previous results and using the USDA nutritional database. Results: To evaluate the proposed system, a set of 24 multi-food dishes was used. For each dish, 3 pairs of images were taken and for each pair, the system was applied 4 times. The mean absolute percentage error in CHO estimation was 10 ± 12%, which led to a mean absolute error of 6 ± 8 CHO grams for normal-sized dishes. Conclusion: The laboratory experiments demonstrated the feasibility of the GoCARB prototype system since the error was below the initial goal of 20 grams. However, further improvements and evaluation are needed prior launching a system able to meet the inter- and intracultural eating habits.

Vision-based Proximity Detection in Retinal Surgery

In retinal surgery, surgeons face difficulties such as indirect visualization of surgical targets, physiological tremor, and lack of tactile feedback, which increase the risk of retinal damage caused by incorrect surgical gestures. In this context, intraocular proximity sensing has the potential to overcome current technical limitations and increase surgical safety. In this paper, we present a system for detecting unintentional collisions between surgical tools and the retina using the visual feedback provided by the opthalmic stereo microscope. Using stereo images, proximity between surgical tools and the retinal surface can be detected when their relative stereo disparity is small. For this purpose, we developed a system comprised of two modules. The first is a module for tracking the surgical tool position on both stereo images. The second is a disparity tracking module for estimating a stereo disparity map of the retinal surface. Both modules were specially tailored for coping with the challenging visualization conditions in retinal surgery. The potential clinical value of the proposed method is demonstrated by extensive testing using a silicon phantom eye and recorded rabbit in vivo data.

A Food Recognition System for Diabetic Patients based on an Optimized Bag of Features Model

Computer vision-based food recognition could be used to estimate a meal's carbohydrate content for diabetic patients. This study proposes a methodology for automatic food recognition, based on the Bag of Features (BoF) model. An extensive technical investigation was conducted for the identification and optimization of the best performing components involved in the BoF architecture, as well as the estimation of the corresponding parameters. For the design and evaluation of the prototype system, a visual dataset with nearly 5,000 food images was created and organized into 11 classes. The optimized system computes dense local features, using the scale-invariant feature transform on the HSV color space, builds a visual dictionary of 10,000 visual words by using the hierarchical k-means clustering and finally classifies the food images with a linear support vector machine classifier. The system achieved classification accuracy of the order of 78%, thus proving the feasibility of the proposed approach in a very challenging image dataset.

Control of muscle relaxation during anesthesia: a novel approach for clinical routine

During general anesthesia drugs are administered to provide hypnosis, ensure analgesia, and skeletal muscle relaxation. In this paper, the main components of a newly developed controller for skeletal muscle relaxation are described. Muscle relaxation is controlled by administration of neuromuscular blocking agents. The degree of relaxation is assessed by supramaximal train-of-four stimulation of the ulnar nerve and measuring the electromyogram response of the adductor pollicis muscle. For closed-loop control purposes, a physiologically based pharmacokinetic and pharmacodynamic model of the neuromuscular blocking agent mivacurium is derived. The model is used to design an observer-based state feedback controller. Contrary to similar automatic systems described in the literature this controller makes use of two different measures obtained in the train-of-four measurement to maintain the desired level of relaxation. The controller is validated in a clinical study comparing the performance of the controller to the performance of the anesthesiologist. As presented, the controller was able to maintain a preselected degree of muscle relaxation with excellent precision while minimizing drug administration. The controller performed at least equally well as the anesthesiologist.

Reading on LCD vs e-Ink displays: effects on fatigue and visual strain

Purpose:  Most recently light and mobile reading devices with high display resolutions have become popular and they may open new possibilities for reading applications in education, business and the private sector. The ability to adapt font size may also open new reading opportunities for people with impaired or low vision. Based on their display technology two major groups of reading devices can be distinguished. One type, predominantly found in dedicated e-book readers, uses electronic paper also known as e-Ink. Other devices, mostly multifunction tablet-PCs, are equipped with backlit LCD displays. While it has long been accepted that reading on electronic displays is slow and associated with visual fatigue, this new generation is explicitly promoted for reading. Since research has shown that, compared to reading on electronic displays, reading on paper is faster and requires fewer fixations per line, one would expect differential effects when comparing reading behaviour on e-Ink and LCD. In the present study we therefore compared experimentally how these two display types are suited for reading over an extended period of time. Methods:  Participants read for several hours on either e-Ink or LCD, and different measures of reading behaviour and visual strain were regularly recorded. These dependent measures included subjective (visual) fatigue, a letter search task, reading speed, oculomotor behaviour and the pupillary light reflex. Results:  Results suggested that reading on the two display types is very similar in terms of both subjective and objective measures. Conclusions:  It is not the technology itself, but rather the image quality that seems crucial for reading. Compared to the visual display units used in the previous few decades, these more recent electronic displays allow for good and comfortable reading, even for extended periods of time.

Noxious stimulation response index: a novel anesthetic state index based on hypnotic-opioid interaction

The noxious stimulation response index (NSRI) is a novel anesthetic depth index ranging between 100 and 0, computed from hypnotic and opioid effect-site concentrations using a hierarchical interaction model. The authors validated the NSRI on previously published data.

Morphological and biochemical T2 evaluation of cartilage repair tissue based on a hybrid double echo at steady state (DESS-T2d) approach

To use a new approach which provides, based on the widely used three-dimensional double-echo steady-state (DESS) sequence, in addition to the morphological information, the generation of biochemical T2 maps in one hybrid sequence.

Time course based artifact identification for independent components of resting-state FMRI

In functional magnetic resonance imaging (fMRI) coherent oscillations of the blood oxygen level-dependent (BOLD) signal can be detected. These arise when brain regions respond to external stimuli or are activated by tasks. The same networks have been characterized during wakeful rest when functional connectivity of the human brain is organized in generic resting-state networks (RSN). Alterations of RSN emerge as neurobiological markers of pathological conditions such as altered mental state. In single-subject fMRI data the coherent components can be identified by blind source separation of the pre-processed BOLD data using spatial independent component analysis (ICA) and related approaches. The resulting maps may represent physiological RSNs or may be due to various artifacts. In this methodological study, we propose a conceptually simple and fully automatic time course based filtering procedure to detect obvious artifacts in the ICA output for resting-state fMRI. The filter is trained on six and tested on 29 healthy subjects, yielding mean filter accuracy, sensitivity and specificity of 0.80, 0.82, and 0.75 in out-of-sample tests. To estimate the impact of clearly artifactual single-subject components on group resting-state studies we analyze unfiltered and filtered output with a second level ICA procedure. Although the automated filter does not reach performance values of visual analysis by human raters, we propose that resting-state compatible analysis of ICA time courses could be very useful to complement the existing map or task/event oriented artifact classification algorithms.

Implementation of Evidence-Based Practices for Treatment of Alcohol and Drug Disorders: The Role of the State Authority

The current climate of increasing performance expectations and diminishing resources, along with innovations in evidence-based practices (EBPs), creates new dilemmas for substance abuse treatment providers, policymakers, funders, and the service delivery system. This paper describes findings from baseline interviews with representatives from 49 state substance abuse authorities (SSAs). Interviews assessed efforts aimed at facilitating EBP adoption in each state and the District of Columbia. Results suggested that SSAs are concentrating more effort on EBP implementation strategies such as education, training, and infrastructure development, and less effort on financial mechanisms, regulations, and accreditation. The majority of SSAs use EBPs as a criterion in their contracts with providers, and just over half reported that EBP use is tied to state funding. To date, Oregon remains the only state with legislation that mandates treatment expenditures for EBPs; North Carolina follows suit with legislation that requires EBP promotion within current resources.

Rapid estimation of cartilage T2 based on double echo at steady state (DESS) with 3 Tesla

The double-echo-steady-state (DESS) sequence generates two signal echoes that are characterized by a different contrast behavior. Based on these two contrasts, the underlying T2 can be calculated. For a flip-angle of 90 degrees , the calculated T2 becomes independent of T1, but with very low signal-to-noise ratio. In the present study, the estimation of cartilage T2, based on DESS with a reduced flip-angle, was investigated, with the goal of optimizing SNR, and simultaneously minimizing the error in T2. This approach was validated in phantoms and on volunteers. T2 estimations based on DESS at different flip-angles were compared with standard multiecho, spin-echo T2. Furthermore, DESS-T2 estimations were used in a volunteer and in an initial study on patients after cartilage repair of the knee. A flip-angle of 33 degrees was the best compromise for the combination of DESS-T2 mapping and morphological imaging. For this flip angle, the Pearson correlation was 0.993 in the phantom study (approximately 20% relative difference between SE-T2 and DESS-T2); and varied between 0.429 and 0.514 in the volunteer study. Measurements in patients showed comparable results for both techniques with regard to zonal assessment. This DESS-T2 approach represents an opportunity to combine morphological and quantitative cartilage MRI in a rapid one-step examination.

Informative State-Based Video Communication

We study state-based video communication where a client simultaneously informs the server about the presence status of various packets in its buffer. In sender-driven transmission, the client periodically sends to the server a single acknowledgement packet that provides information about all packets that have arrived at the client by the time the acknowledgment is sent. In receiver-driven streaming, the client periodically sends to the server a single request packet that comprises a transmission schedule for sending missing data to the client over a horizon of time. We develop a comprehensive optimization framework that enables computing packet transmission decisions that maximize the end-to-end video quality for the given bandwidth resources, in both prospective scenarios. The core step of the optimization comprises computing the probability that a single packet will be communicated in error as a function of the expected transmission redundancy (or cost) used to communicate the packet. Through comprehensive simulation experiments, we carefully examine the performance advances that our framework enables relative to state-of-the-art scheduling systems that employ regular acknowledgement or request packets. Consistent gains in video quality of up to 2B are demonstrated across a variety of content types. We show that there is a direct analogy between the error-cost efficiency of streaming a single packet and the overall rate-distortion performance of streaming the whole content. In the case of sender-driven transmission, we develop an effective modeling approach that accurately characterizes the end-to-end performance as a function of the packet loss rate on the backward channel and the source encoding characteristics.