Error Concealment for 5/3 Motion Compensated Temporal Filtering with Lifting

5/3 Motion Compensated Temporal Filtering (MCTF) is a tool for highly scalable video coding which has been recently studied by many researchers. This thesis presents several error concealment algorithms for 5/3 MCTF with lifting, which can be used to improve the quality of compressed video damaged by packet losses. In MCTF video, the low frequency subband frame, abbreviated as L-frame, contains most of the signal energy in any given Group-of-Pictures (GOP). We assume that one of these L-frames is lost. The proposed error concealment algorithms use the available data to reconstruct the missing L-frame. The simplest error concealment method considered in the thesis is Zero Motion Error Concealment. This method simply assumes zero motion through the damaged GOP, and averages the neighboring L-frames to reconstruct the missing L-frame. Another method called Motion Concatenation finds temporal pathways through the damaged GOP by connecting motion vectors available at the decoder, and copies the corresponding pixel values from the neighboring L-frames to the missing L-frame. Finally, Motion Re-estimation uses motion estimator at the decoder to find a motion vectors between two neighboring L-frames of the missing L-frame, and synthesizes the missing L-frame halfway between its neighboring L-frames. The overall error concealment system combines these three methods to maximize visual performance, as well as the Peak Signal-to-Noise-Ratio (PSNR)

Effectiveness of a Serious Game for Cognitive Training in Chronic Stroke Survivors with Mild-to-Moderate Cognitive Impairment: A Pilot Randomized Controlled Trial

Previous cognitive training games for stroke survivors required the close supervision of therapists. We aim to demonstrate the preliminary therapeutic effectiveness of Neuro-World, serious mobile games for cognitive training, in chronic stroke survivors with mild-to-moderate cognitive impairment without therapist supervision. For that, we conducted a randomized, controlled clinical trial at a single long-term care rehabilitation center with 50 stroke survivors in the chronic stage with mild-to-moderate cognitive impairment. Participants were randomized to standard medical care (n = 25) or standard medical care plus administration of Neuro-World (n = 25) over 12 weeks. A two-way mixed model ANOVA and Tukey’s post hoc tests identified significant differences in outcomes between the experimental and the control groups at post-intervention but not at baseline. Within the experimental group, there were statistically significant improvements in all the outcomes except for the language category of the Mini-Mental State Examination and Digit Forward Span. The improvements were clinically significant for the total Mini-Mental State Examination, Digit Forward Span, and Digit Backward Span. Within the control group, there were no improvements in any of the outcomes. The practice of Neuro-World led to significant improvements in cognitive function and marginal mitigation of depressive symptoms in chronic stroke survivors with mild-to-moderate cognitive impairment

LungTrack: towards contactless and zero dead-zone respiration monitoring with commodity RFIDs

International audienceRespiration rate sensing plays a critical role in elderly care and patient monitoring. The latest research has explored the possibility of employing Wi-Fi signals for respiration sensing without attaching a device to the target. A critical issue with these solutions includes that good monitoring performance could only be achieved at certain locations within the sensing range, while the performance could be quite poor at other "dead zones." In addition, due to the contactless nature, it is challenging to monitor multiple targets simultaneously as the reflected signals are often mixed together. In this work, we present our system, named LungTrack, hosted on commodity RFID devices for respiration monitoring. Our system retrieves subtle signal fluctuations at the receiver caused by chest displacement during respiration without need for attaching any devices to the target. It addresses the dead-zone issue and enables simultaneous monitoring of two human targets by employing one RFID reader and carefully positioned multiple RFID tags, using an optimization technique. Comprehensive experiments demonstrate that LungTrack can achieve a respiration monitoring accuracy of greater than 98% for a single target at all sensing locations (within 1 st − 5 th Fresnel zones) using just one RFID reader and five tags, when the target's orientation is known a priori. For the challenging scenario involve two human targets, LungTrack is able to achieve greater than 93% accuracy when the targets are separated by at least 10 cm

An Overview of Smart Shoes in the Internet of Health Things: Gait and Mobility Assessment in Health Promotion and Disease Monitoring

New smart technologies and the internet of things increasingly play a key role in healthcare and wellness, contributing to the development of novel healthcare concepts. These technologies enable a comprehensive view of an individual’s movement and mobility, potentially supporting healthy living as well as complementing medical diagnostics and the monitoring of therapeutic outcomes. This overview article specifically addresses smart shoes, which are becoming one such smart technology within the future internet of health things, since the ability to walk defines large aspects of quality of life in a wide range of health and disease conditions. Smart shoes offer the possibility to support prevention, diagnostic work-up, therapeutic decisions, and individual disease monitoring with a continuous assessment of gait and mobility. This overview article provides the technological as well as medical aspects of smart shoes within this rising area of digital health applications, and is designed especially for the novel reader in this specific field. It also stresses the need for closer interdisciplinary interactions between technological and medical experts to bridge the gap between research and practice. Smart shoes can be envisioned to serve as pervasive wearable computing systems that enable innovative solutions and services for the promotion of healthy living and the transformation of health care

The Motion Capture System

The objective of the Motion Capture System is to capture and simulate the movement of a dancer. Currently, at Simon Fraser University three departments of Computing, Music, and Engineering are intrigued by the project which focuses on studying dance movements and composing or conducting music inspired from these movements. Particularly, these departments are interested in our project since it has the potential to become the initial step of the bigger project involving the three departments. Our goal is to design a real time system which captures the 2D movement of an object (a small doll) and can be utilized as an analysis tool to study the movements of a dancer. The data obtained from the analysis tool can be fed to composition software to create composition data or directed to synthesizer software to generate the corresponding audio sounds

Decomposition of Reaching Movements Enables Detection and Measurement of Ataxia

Technologies that enable frequent, objective, and precise measurement of ataxia severity would benefit clinical trials by lowering participation barriers and improving the ability to measure disease state and change. We hypothesized that analyzing characteristics of sub-second movement profiles obtained during a reaching task would be useful for objectively quantifying motor characteristics of ataxia. Participants with ataxia (N=88), participants with parkinsonism (N=44), and healthy controls (N=34) performed a computer tablet version of the finger-to-nose test while wearing inertial sensors on their wrists. Data features designed to capture signs of ataxia were extracted from participants’ decomposed wrist velocity time-series. A machine learning regression model was trained to estimate overall ataxia severity, as measured by the Brief Ataxia Rating Scale (BARS). Classification models were trained to distinguish between ataxia participants and controls and between ataxia and parkinsonism phenotypes. Movement decomposition revealed expected and novel characteristics of the ataxia phenotype. The distance, speed, duration, morphology, and temporal relationships of decomposed movements exhibited strong relationships with disease severity. The regression model estimated BARS with a root mean square error of 3.6 points, r2 = 0.69, and moderate-to-excellent reliability. Classification models distinguished between ataxia participants and controls and ataxia and parkinsonism phenotypes with areas under the receiver-operating curve of 0.96 and 0.89, respectively. Movement decomposition captures core features of ataxia and may be useful for objective, precise, and frequent assessment of ataxia in home and clinic environments

ExerLink: Enabling Pervasive Social Exergames with Heterogeneous Exercise Devices

We envision that diverse social exercising games, or exergames, will emerge, featuring much richer interactivity with immersive game play experiences. Further, the recent advances of mobile devices and wireless networking will make such social engagement more pervasive - people carry portable exergame devices (e.g., jump ropes) and interact with remote users anytime, anywhere. Towards this goal, we explore the potential of using heterogeneous exercise devices as game controllers for a multi-player social exergame; e.g., playing a boat paddling game with two remote exercisers (one with a jump rope, and the other with a treadmill). In this paper, we propose a novel platform called ExerLink that converts exercise intensity to game inputs and intelligently balances intensity/delay variations for fair game play experiences. We report the design considerations and guidelines obtained from the design and development processes of game controllers. We validate the efficacy of game controllers and demonstrate the feasibility of social exergames with heterogeneous exercise devices via extensive human subject studies.

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

Correction to: Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

The original version of this article unfortunately contained a mistake