Development of augmented reality rehabilitation games integrated with biofeedback for upper limb

Stroke is one of the leading causes of disability in all over the world. This disability greatly impacts the stroke patients' daily life activities. Thus, rehabilitation exercises are essential for post stroke patients to restore their lost functions gradually for daily life activities. Traditional rehabilitation exercises do not motivate the post stroke patients as they are normally humdrum and required expensive equipments. Therefore, this paper presents the development of low -cost motivating webcam colour based visual tracking augmented reality (AR) system with biofeedback for upper-limb post stroke rehabilitation therapy. Augmented Reality is a novel form of human-computer interface which overlay the computer-generated information on the real world environment rather than replaces it. In the developed AR system, two games; Ping Pong Rehab (PPR) and Balloon Collection Rehab (BCR) are created based on game design principle. PPR game trains shoulder and arm muscles during rehabilitation therapy whilst BCR game trains shoulder, arm and forearm muscles. Both games have been built and integrated with Biograph Infiniti software to monitor the muscles' performance. The integrated system will obtain the biofeedback EMG signals from patients that will be utilised for future developments. It allows the patients to monitor their arms and muscles movements in real time on the display screen via low-cost webcam. The system aims for home based rehabilitation system and friendly used by patients themselves. The developed integrated system has tested with able subject and it worked perfectly during the test

Real time biosignal-Driven illusion system for upper limb rehabilitation

This paper presents design and development of real time biosignal-driven illusion system: Augmented Reality based Illusion System (ARIS) for upper limb motor rehabilitation. ARIS is a hospital / home based self-motivated whole arm rehabilitation system that aims to improve and restore the lost upper limb functions due to Cerebrovascular Accident (CVA) or stroke. Taking the advantage of human brain plasticity nature, the system incorporates with number of technologies to provide fast recovery by re-establishing the neural pathways and synapses that able to control the mobility. These technologies include Augmented Reality (AR) where illusion environment is developed, computer vision technology to track multiple colors in real time, EMG acquisition system to detect the user intention in real time and 3D modelling library to develop Virtual Arm (VA) model where human biomechanics are applied to mimic the movement of real arm. The system operates according to the user intention via surface electromyography (sEMG) threshold level. In the case of real arm cannot reach to the desired position, VA will take over the job of real arm to complete the exercise. The effectiveness of the developed ARIS has evaluated via questionnaire, graphical and analytical measurements which provided with positive results

Estimation of Upper Limb Joint Angle Using Surface EMG Signal

In the development of robot-assisted rehabilitation systems for upper limb rehabilitation therapy, human electromyogram (EMG) is widely used due to its ability to detect the user intended motion. EMG is one kind of biological signal that can be recorded to evaluate the performance of skeletal muscles by means of a sensor electrode. Based on recorded EMG signals, user intended motion could be extracted via estimation of joint torque, force or angle. Therefore, this estimation becomes one of the most important factors to achieve accurate user intended motion. In this paper, an upper limb joint angle estimation methodology is proposed. A back propagation neural network (BPNN) is developed to estimate the shoulder and elbow joint angles from the recorded EMG signals. A Virtual Human Model (VHM) is also developed and integrated with BPNN to perform the simulation of the estimated angle. The relationships between sEMG signals and upper limb movements are observed in this paper. The effectiveness of our developments is evaluated with four healthy subjects and a VHM simulation. The results show that the methodology can be used in the estimation of joint angles based on EMG

Augmented Reality based Illusion System with biofeedback

This paper presents the Augmented Reality based Illusion System (ARIS) with biofeedback for upper limb rehabilitation. It aims for fast recovery of motor deficit with motivational approach over traditional upper limb rehabilitation methods. The system incorporates with Augmented Reality (AR) technology to develop upper limb rehabilitation exercise and computer vision with color recognition technique to create 'Fool-the-Brain' concept for fast recovery of neural impairment due to various motor injuries. The rehabilitation exercise in ARIS is aiming to increase the shoulder joint range of motions by performing reaching movements and to strengthen the associated muscles. 'Fool-the-Brain' concept is introduced during performing rehabilitation exercise to perceive artificial visual feedback where user's real impaired arm is covered by Virtual Arm (VA). When the real arm cannot perform the required task, VA will take over the job of real one and will make the user perceives the sense that is still be able to accomplish the task with own effort. Evaluation has performed and results indicate that ARIS with biofeedback is a potential upper limb rehabilitation system for people with upper limb motor deficit. © 2014 IEEE

Scaled conjugate gradient based decision support system for automated diagnosis of skin cancer

Melanoma is the most deathful form of skin cancer but early diagnosis can ensure a high rate of survival. Early diagnosis is one of the greatest challenges due to lack of experience of general practitioners (GPs). This paper presents a clinical decision support system designed for the use of general practitioners, aiming to save time and resources in the diagnostic process. Segmentation, pattern recognition, and lesion detection are the important steps in the proposed decision support system. The system analyses the images to extract the affected area using a novel proposed segmentation method. It determinates the underlying features which indicate the difference between melanoma and benign images and makes a decision. Considering the efficiency of neural networks in classification of complex data, scaled conjugate gradient based neural network is used for classification. The presented work also considers analyzed performance of other efficient neural network training algorithms on the specific skin lesion diagnostic problem and discussed the corresponding findings. The best diagnostic rates obtainedthrough the proposed decision support system are around 92%

A binary level set method based on k-Means for contour tracking on skin cancer images

A great challenge of research and development activities have recently highlighted in segmenting of the skin cancer images. This paper presents a novel algorithm to improve the segmentation results of level set algorithm with skin cancer images. The major contribution of presented algorithm is to simplify skin cancer images for the computer aided object analysis without loss of significant information and to decrease the required computational cost. The presented algorithm uses k-means clustering technique and explores primitive segmentation to get initial label estimation for level set algorithm. The proposed segmentation method provides better segmentation results as compared to standard level set segmentation technique and modified fuzzy cmeans clustering technique

Promoter polymorphisms of DNMT3B and the risk of colorectal cancer in Chinese: a case-control study

<p>Abstract</p> <p>Background</p> <p>DNA-methyltransferase-3B (DNMT3B), which plays a role in DNA methylation, is usually aberrant expression involved in carcinogenesis. Polymorphisms of the DNMT3B gene may influence DNMT3B activity on DNA methylation in several cancers, thereby modulating the susceptibility to cancer.</p> <p>Methods</p> <p>DNMT3B -579G>T genotypes and -149C>T were determined by PCR-RFLP and sequencing in 137 colorectal cancer patients and 308 controls matched for age and sex, who did not receive radiotherapy or chemotherapy for newly diagnosed and histopathologically confirmed colorectal cancer. The association between two SNPs of the <it>DNMT3B </it>promoter and the risk of the development of colorectal cancer was analyzed in a population of Chinese.</p> <p>Results</p> <p>The allele frequency of -149C >T among patients and controls was 0.73% versus 0.65%, respectively. The allele frequency of -597G>T for patients and controls was 6.57% versus 11.53%, respectively. Individuals with at least one -149C>T allele were no at a significantly increase risk of colorectal cancer compared with those having a -149TT genotype. However, Individuals with at least one 579G>T allele were decreased risk of colorectal cancer compared with those having a -579TT genotype.</p> <p>Conclusion</p> <p>The relative distribution of -149C>T <it>DNMT3B </it>SNPs among a Chinese population can not be used as a stratification marker to predict an individual's susceptibility to colorectal cancer. However, the DNMT3B -579G>T polymorphism may contribute to the genetic susceptibility to colorectal cancer.</p

The evidence base for circulating tumour DNA blood-based biomarkers for the early detection of cancer: a systematic mapping review

Background: The presence of circulating cell-free DNA from tumours in blood (ctDNA) is of major importance to those interested in early cancer detection, as well as to those wishing to monitor tumour progression or diagnose the presence of activating mutations to guide treatment. In 2014, the UK Early Cancer Detection Consortium undertook a systematic mapping review of the literature to identify blood-based biomarkers with potential for the development of a non-invasive blood test for cancer screening, and which identified this as a major area of interest. This review builds on the mapping review to expand the ctDNA dataset to examine the best options for the detection of multiple cancer types. Methods: The original mapping review was based on comprehensive searches of the electronic databases Medline, Embase, CINAHL, the Cochrane library, and Biosis to obtain relevant literature on blood-based biomarkers for cancer detection in humans (PROSPERO no. CRD42014010827). The abstracts for each paper were reviewed to determine whether validation data were reported, and then examined in full. Publications concentrating on monitoring of disease burden or mutations were excluded. Results: The search identified 94 ctDNA studies meeting the criteria for review. All but 5 studies examined one cancer type, with breast, colorectal and lung cancers representing 60% of studies. The size and design of the studies varied widely. Controls were included in 77% of publications. The largest study included 640 patients, but the median study size was 65 cases and 35 controls, and the bulk of studies (71%) included less than 100 patients. Studies either estimated cfDNA levels non-specifically or tested for cancer-specific mutations or methylation changes (the majority using PCR-based methods). Conclusion: We have systematically reviewed ctDNA blood biomarkers for the early detection of cancer. Pre-analytical, analytical, and post-analytical considerations were identified which need to be addressed before such biomarkers enter clinical practice. The value of small studies with no comparison between methods, or even the inclusion of controls is highly questionable, and larger validation studies will be required before such methods can be considered for early cancer detection

Alum Adjuvant Enhances Protection against Respiratory Syncytial Virus but Exacerbates Pulmonary Inflammation by Modulating Multiple Innate and Adaptive Immune Cells

Respiratory syncytial virus (RSV) is well-known for inducing vaccine-enhanced respiratory disease after vaccination of young children with formalin-inactivated RSV (FI-RSV) in alum formulation. Here, we investigated alum adjuvant effects on protection and disease after FIRSV immunization with or without alum in comparison with live RSV reinfections. Despite viral clearance, live RSV reinfections caused weight loss and substantial pulmonary inflammation probably due to high levels of RSV specific IFN-γ+IL4-, IFN-γ-TNF-α+, IFN-γ+ TNF-α- effector CD4 and CD8 T cells. Alum adjuvant significantly improved protection as evidenced by effective viral clearance compared to unadjuvanted FI-RSV. However, in contrast to unadjuvanted FI-RSV, alum-adjuvanted FI-RSV (FI-RSV-A) induced severe vaccine- enhanced RSV disease including weight loss, eosinophilia, and lung histopathology. Alum adjuvant in the FI-RSV-A was found to be mainly responsible for inducing high levels of RSV-specific IFN-γ-IL4+, IFN-γ-TNF-α+ CD4+ T cells, and proinflammatory cytokines IL-6 and IL-4 as well as B220+ plasmacytoid and CD4+ dendritic cells, and inhibiting the induction of IFN-γ+CD8 T cells. This study suggests that alum adjuvant in FI-RSV vaccines increases immunogenicity and viral clearance but also induces atypical T helper CD4+ T cells and multiple inflammatory dendritic cell subsets responsible for vaccine-enhanced severe RSV disease

Intraperitoneal drain placement and outcomes after elective colorectal surgery: international matched, prospective, cohort study

Despite current guidelines, intraperitoneal drain placement after elective colorectal surgery remains widespread. Drains were not associated with earlier detection of intraperitoneal collections, but were associated with prolonged hospital stay and increased risk of surgical-site infections.Background Many surgeons routinely place intraperitoneal drains after elective colorectal surgery. However, enhanced recovery after surgery guidelines recommend against their routine use owing to a lack of clear clinical benefit. This study aimed to describe international variation in intraperitoneal drain placement and the safety of this practice. Methods COMPASS (COMPlicAted intra-abdominal collectionS after colorectal Surgery) was a prospective, international, cohort study which enrolled consecutive adults undergoing elective colorectal surgery (February to March 2020). The primary outcome was the rate of intraperitoneal drain placement. Secondary outcomes included: rate and time to diagnosis of postoperative intraperitoneal collections; rate of surgical site infections (SSIs); time to discharge; and 30-day major postoperative complications (Clavien-Dindo grade at least III). After propensity score matching, multivariable logistic regression and Cox proportional hazards regression were used to estimate the independent association of the secondary outcomes with drain placement. Results Overall, 1805 patients from 22 countries were included (798 women, 44.2 per cent; median age 67.0 years). The drain insertion rate was 51.9 per cent (937 patients). After matching, drains were not associated with reduced rates (odds ratio (OR) 1.33, 95 per cent c.i. 0.79 to 2.23; P = 0.287) or earlier detection (hazard ratio (HR) 0.87, 0.33 to 2.31; P = 0.780) of collections. Although not associated with worse major postoperative complications (OR 1.09, 0.68 to 1.75; P = 0.709), drains were associated with delayed hospital discharge (HR 0.58, 0.52 to 0.66; P &lt; 0.001) and an increased risk of SSIs (OR 2.47, 1.50 to 4.05; P &lt; 0.001). Conclusion Intraperitoneal drain placement after elective colorectal surgery is not associated with earlier detection of postoperative collections, but prolongs hospital stay and increases SSI risk