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The latest advancements in the field of deep learning and biomedical engineering have allowed for the development of myoelectric interfaces based on deep neural networks. A longstanding problem of these interfaces is that the models cannot easily be applied to new users due to the high variability and stochastic nature of the electromyography signals. Further training a new model for every new subject requires the collection of large volumes of data. Therefore, this work proposes a transfer learning (TL) scheme which allows reusing the knowledge of a pre-existing model for a new user. Firstly, a convolutional neural network (CNN) is trained on an initial dataset using the data of multiple subjects. Then, the weights of this model are fine-tuned for a new target subject. The approach is evaluated on the Ninapro datasets DB2 and DB7. The experimentation included three different CNN models and eight preprocessing alternatives. The results showed that the success of the TL method depends on how the data are preprocessed. Specifically, the biggest accuracy improvement (+5.14%) is achieved when only the first 20% of the signal duration is used.

Cerebral palsy (CP) is the most common cause of permanent neurological disabilities in children. Many children require long-term daily physiotherapy (PT), and videogaming is a promising tool to increase motivation in rehabilitation. The short- and medium-term effects of an intervention with rehabilitation specific videogames were evaluated on individually defined therapy goals, gross motor function, and motivation. Thirty-two children with bilateral spastic CP, Gross Motor Function Classification level III-IV, and 6-15 years were randomized into an intervention group (regular PT and gaming) or a control group (regular PT), followed by a crossover. The effects of both training periods (each 12 weeks) were compared using the Goal Attainment Scale (GAS), Trunk Control Measurement Scale (TCMS), Pediatric Balance Scale (PBS), Gross Motor Function Measure-88 (GMFM-88), and Dimensions of Mastery Motivation Questionnaire (DMQ). After 3 months follow-up, children were retested using the GMFM, TCMS, and PBS. The GAS change scores were significantly higher after the intervention compared to the control period (8.5 and 2.4

We propose a neuroevolutionary speciation mechanism that is applied on NeuroEvolution of Augmenting Topologies (NEAT) that solely evolves neural networks’ topology and weights and its extension HA-NEAT that also evolves activation functions. The new speciation mechanism is defined based on the behavior of the individuals rather than their topological similarity. Focusing on classification tasks we build artificial datasets of high complexity. Performance is described by (i) median classification accuracy, (ii) computational efficiency (number of generations) and (iii) network complexity (number of nodes and connections). The performance metrics are compared using Kruskal-Wallis hypothesis tests with Bonferroni correction. It is found that the proposed behavioral speciation mechanism outperforms the original speciation solving problems that were not solvable before or improving the accuracy and reducing the network complexity.

Objective : The aim of this study was to determine if serious games especially customized for physical rehabilitation could be used in daily clinics with patients that are not familiar with informatics and/or new technologies. Materials and methods : 21 patients participated in this study. Experiments were performed in the physical rehabilitation of a hospital in Morocco. Patients were asked to perform physical rehabilitation exercises with dedicated serious games after their conventional therapy session. A questionnaire was used to evaluate patients’ habits to rehabilitation exercises and satisfaction and expectation about the use of serious games for physical rehabilitation. This study aimed to determine if such clinical approach would be culturally acceptable within a North African population in order to plan further clinical distribution if the hypothesis appears to be positive. Results : The same problem of low adherence to at-home exercises was found in Morocco compared to Europe and the United-States of America: 60 (30) % of the exercises performed by the patients in Morocco, 48 (28) % in Europe and the Stats. Results of this study shown that serious games are well accepted by the patient (100%) and that it can help during the rehabilitation (90%). Most of the patient prefers the exercises with the games compared to conventional rehabilitation exercises. Conclusion: Even in a context of low education (participants in this study attended school until the age of 10 y.o.), and low access and knowledge about new technology and informatics, rehabilitation exercises within serious games seems to be an interesting option to motivate patient during the rehabilitation with the physiotherapist but also eventually placed at-home to facilitate rehabilitation.

The aim of this study was to determine if the results of activities performed using specially developed serious games for physical rehabilitation could be used as an indicator of the natural maturation and decline of motor control in healthy participants. Eighty-one participants (19 children (5–15 years old), 40 adults (18–65 years old) and 22 aged subjects (60–88 years old) participated in this study. Motions performed were recorded using the Kinect sensor. Three different exercises embedded in the games were used to assess upper limb, trunk and lower limb control. The trial duration and accuracy, measures of gross motor function and fine motor control, respectively, were computed for each participant. ANOVA tests shows statistically significant differences between the three groups for duration (53 ± 15, 27 ± 10 and 119 ± 30 s for children, adults and elderly subjects respectively) and accuracy (87 ± 5, 89 ± 10 and 70 ± 8% for children, adults and elderly subjects respectively). The slopes of the curves that approximated the evolution of the performance over various ages are coherent with previous studies about motor control development and physiological decline. The proposed solution, i.e. serious games rehabilitation exercises coupled to motion analysis, seems to be an interesting tool to assess global motor function. Further studies are needed to study the influence of pathologies on the studied parameters.

This study aimed to investigate: 1) the effect of optic flow speed manipulation on active participation during robot-assisted treadmill walking (RATW), 2) the influence of the type of virtual environment, and 3) the level of motion sickness and enjoyment. Twenty-eight healthy older adults were randomized in two groups: “stimulus rich” Park group (50% male, 61± 6 year) and “stimulus poor” Hallway group (43% male, 62± 5 year). Subjects walked in the Lokomat with immersive virtual reality (VR) with a matched, slow and fast optic flow speed, each lasting 7 minutes. Active participation was measured by continuously assessing the human-machine interaction torques at the hip and knee joints and muscle activity of the Vastus Medialis and Biceps Femoris. Motion sickness and enjoyment were assessed with the Simulator Sickness Questionnaire (SSQ) and Physical Activity Enjoyment Scale (PACES) respectively. In both groups optic flow speed manipulation in both directions led to a decrease in bilateral hip interaction torques towards flexion at the end of the stance phase compared to matched speed. In the Hallway group, walking with slow optic flow elicited 32% more muscle activity of the Vastus Medialis. There were no significant differences between both groups for the SSQ and PACES. Optic flow speed manipulation appears to have only a small effect on the active participation of healthy people during RATW. The type of virtual environment did not affect their activity, motion sickness or enjoyment. However, the addition of immersive VR during RATW was well tolerated and enjoyable. Further research with patients is necessary.

The use of hazardous chemicals is widely embedded throughout the life cycle of jeans. Recent literature on the use and discharge of hazardous chemicals in the denim and jeans industry reveals that in many of the production phases of a jeans, the use of such chemicals poses a health risk to cotton farmers, companies’ employees and neighboring communities, and that local eco-systems have or are becoming dysfunctional due to chemical pollution. This implies that those chemicals often negatively impact the planetary boundaries and the human right to a clean and healthy environment. This chapter first provides an analysis of the adverse impacts in each phase of the entire life-cycle of a pair of jeans (‘jeans’): (i) cotton farming and (ii) weaving & dyeing (Turkey); (iii) manufacturing (Vietnam); (iv) consumer use and (v) disposal (the Netherlands). Subsequently, the legal standards applicable to the use and discharge of (hazardous) chemicals in each of these five phases are discussed, covering international and EU law, soft law, domestic law and self-regulatory standards. In the final part, the legal standards are compared with industries’ best practices that emerged from the gathered information in a case study concerning a specific pair of jeans. This comparison provides an in-depth insight in the gap between legal theory and practice. Based on this understanding, further action can be initiated, and solutions can be developed by the denim and jeans industry and policymakers aimed at addressing the challenges revealed in this study.

In the Dutch capitalistic consumer society, things are not made to stand the test of time, but to be replaced by other things within the foreseeable future. They are made to be thrown away, and quite often as quickly as possible, because it is this characteristic that guarantees a new purchase. In this contribution the authors will focus on a white T-shirt. The main questions are: What is the current practice in the Netherlands regarding the disposal, separation, reusing, and recycling of this Dutch white trash and how does the legal framework regulate the matter of RMG waste?.

Summary Background To date, the accuracy of bio-impedance (BIA) to assess body composition & sarcopenia in persons aged 80 and over remains unclear. Objective We aimed to evaluate the agreement between dual energy X-ray absorptiometry (DXA) and BIA equations to determine lean mass, as well as their suitability to identify sarcopenia. Design 174 community dwelling well-functioning persons (83 women, 91 men) aged 80 and over were included. Appendicular lean mass (ALM) was predicted using BIA-based equations available in literature, and compared to DXA outcomes. Through cross-validation and stepwise multiple linear regression, a new ALM-formula was generated suitable for this population. Results Literature-based BIA equations systematically overestimated ALM. The new prediction formula that we propose for the 80+ is: ALM = 0,827+(0,19*Impedance Index)+(2,101*Sex)+(0,079*Weight); R2 = 0,888; SEE = 1,450 kg. Sarcopenia classification based on our new BIA equation for ALM showed better agreement with DXA (k ≥ 0,454) compared to literature-based BIA equations (k Conclusions Despite the high correlation between both methods, literature-based BIA equations consistently overestimate ALM compared to DXA in persons aged 80 and over. We proposed a new equation for ALM, reaching higher agreement with DXA and thus improving the accuracy of BIA for this specific age group.

Purpose To identify the different fatigue items in existing frailty scales. Methods PubMed, Web of Knowledge and PsycINFO were systematically screened for frailty scales. 133 articles were included, describing 158 frailty scales. Fatigue items were extracted and categorized in 4 fatigue constructs: “mood state related tiredness”, “general feeling of tiredness”, “activity based feeling of tiredness” and “resistance to physical tiredness”. Results 120 fatigue items were identified, of which 100 belonged to the construct “general feeling of tiredness” and only 9 to the construct “resistance to physical tiredness”. 49,4% of the frailty scales included at least 1 fatigue item, representing 15 ± 9,3% of all items in these scales. Fatigue items have a significantly higher weight in single domain (dominantly physical frailty scales) versus multi domain frailty scales (21 ± 3.2 versus 10.6 ± 9.8%, p= Conclusion Fatigue is prominently represented in frailty scales, covering a great diversity in fatigue constructs and underlying pathophysiological mechanisms by which fatigue relates to frailty. Although fatigue items were more prevalent and had a higher weight in physical frailty scales, the operationalization of fatigue leaned more towards psychological constructs. This review can be used as a reference for choosing a suitable frailty scale depending on the type of fatigue of interest.

Deep learning (DL) has transformed the field of data analysis by dramatically improving the state of the art in various classification and prediction tasks, especially in the area of computer vision. In biomedical engineering, a lot of new work is directed towards surface electromyography (sEMG) based gesture recognition, often addressed as an image classification problem using Convolutional Neural Networks (CNN). In this paper, we utilize the Hilbert space-filling curve for the generation of image representations of sEMG signals that are then classified by CNN. The proposed method is evaluated on different network architectures and yields a classification improvement of more than 3%.

In recent years, the successful application of Deep Learning methods to classification problems has had a huge impact in many domains. In biomedical engineering, the problem of gesture recognition based on electromyography is often addressed as an image classification problem using Convolutional Neural Networks. In this paper, we approach electromyography-based hand gesture recognition as a sequence classification problem using Temporal Convolutional Networks. The proposed network yields an improvement in gesture recognition of almost 5% to the state of the art reported in the literature, whereas the analysis helps in understanding the limitations of the model and exploring new ways to improve its performance.

Objective Although dual-task paradigm is commonly used in rehabilitation there is, currently, a lack of information about quantitative balance assessment performed in dual-task conditions. The aim of this study is to validate the use of the Nintendo Wii Balance Board (WBB) to assess balance modifications induced by dual-task activity in healthy subjects. Material and Methods Seventy-five healthy participants (37 ± 14 years old, 173± 8 cm, 73± 16 kg, 35 women) participated in this study. Balance was recorded in control situation (baseline) and under two different cognitive tasks (verbal fluency and calculation). Each trial lasted for 60 seconds and were performed with eyes open and closed. Nine parameters were extracted based on center of pressure displacement based on a previously-validated method. ANOVA tests were used to compare the different conditions followed by Bonferroni’s corrections. Protocol was repeated one week after to assess the reproducibility. Results Statistically significant differences were found comparing eyes open and closed situation. Concerning the influence of dual-tasks statistically significant decrease of the balance was observed for both eyes open and closed conditions (increase of the total sway and the speed of displacement). Concerning the reproducibility all parameters shows good to excellent ICC values for the different conditions. Conclusion In this study, we demonstrated the validity of the WBB to detect the effect of the dual-task on balance in healthy subjects. Further studies are needed to determine if such a kind of evaluation can be used in clinics with subjects at risk of falling.

Objective The aim of this work was to determine if scoring mechanisms embedded in cognitive mobile games (CMG) designed for cognitive training are sensitive enough to detect changes in cognitive function induced by various acute respiratory loads in healthy subjects. Material and methods Thirty healthy subjects participated in this study (25 ± 4 years old, 13 women). A set of three brief CMG was used to assess cognitive function (Rush Back, Must Sort, True Color) in control situation and at four different inspiratory loads (through a mouthpiece without resistance and with 10, 50 and 70% of the maximal inspiratory pressure). Results Statistically significant decreases in CMG scores were observed in Rush Back (p = 0.032) and True Color (p = 0.002) when the subjects breathed through the mouthpiece without resistance compared to the control condition. A statistical difference was observed for Must Sort (p = 0.003) between baseline and 10% of Inspiratory Threshold Load (ITL). Significant differences for the three games were observed between the baseline and 50% of ITL and between baseline and 70% of ITL. Conclusion CMG designed for cognitive training are sensitive in detecting transitional changes in cognitive function induced by low, medium and high acute respiratory loads in healthy subjects. This offers interesting new possibilities for the assessment and long-term follow-up of patients suffering from chronic respiratory disease, since this type of assessment could easily be completed independently by patients in their own homes, and could be combined with rehabilitation exercises as an evaluative measure.

The aim of this paper was to investigate the effect of commercial video games (VGs) in physical rehabilitation of motor functions. Several databases were screened (Medline, SAGE Journals Online, and ScienceDirect) using combinations of the following free-text terms: commercial games, video games, exergames, serious gaming, rehabilitation games, PlayStation, Nintendo, Wii, Wii Fit, Xbox, and Kinect. The search was limited to peer-reviewed English journals. The beginning of the search time frame was not restricted and the end of the search time frame was 31 December 2015. Only randomized controlled trial, cohort, and observational studies evaluating the effect of VGs on physical rehabilitation were included in the review. A total of 4728 abstracts were screened, 275 were fully reviewed, and 126 papers were eventually included. The following information was extracted from the selected studies: device type, number and type of patients, intervention, and main outcomes. The integration of VGs into physical rehabilitation has been tested for various pathological conditions, including stroke, cerebral palsy, Parkinson's disease, balance training, weight loss, and aging. There was large variability in the protocols used (e.g. number of sessions, intervention duration, outcome measures, and sample size). The results of this review show that in most cases, the introduction of VG training in physical rehabilitation offered similar results as conventional therapy. Therefore, VGs could be added as an adjunct treatment in rehabilitation for various pathologies to stimulate patient motivation. VGs could also be used at home to maintain rehabilitation benefits.

This paper contributes to the philosophical approach of business ethics by inserting the current state of business ethics, which is captured by semi-legal casuistry and frameworks, and Karan Barad's posthuman theory known as 'new materialism', into a proposal for the study of business ethics. The merging of business ethics and posthuman theory results in a so-called 'posthuman approach to critical business ethics'. My proposition is that these semi-legal frameworks weaken the field of business ethics, or even make it disappear. In addition to descriptive, empirical, social-scientific business ethics, there is also philosophical, normative, critical business ethics. This paper is written in the belief that these two branches of business ethics are navel-gazing toward legal or semi-legal frameworks - such as self-regulation and alternative dispute resolution (ADR) - creating a discourse of utility and regulation, rather than a discourse of ethics.

In recent years, Deep Learning methods have been successfully applied to a wide range of image and speech recognition problems highly impacting other research fields. As a result, new works in biomedical engineering are directed towards the application of these methods to electromyography-based gesture recognition. In this paper, we present a brief overview of Deep Learning methods for electromyography-based hand gesture recognition along with an analysis of a modified simple model based on Convolutional Neural Networks. The proposed network yields a 3% improvement on the classification accuracy of the basic model, whereas the analysis helps in understanding the limitations of the model and exploring new ways to improve the performance.

There is a link between breathing and balance and posture. When the inspiratory loads are increased by pathologies, there is a decrease of postural control. The increase of the inspiratory load on respiratory muscles is a common feature in various chronic pulmonary pathologies. Consequently, the balance of those patients is likely affected., SCOPUS: ar.j, info:eu-repo/semantics/published

BACKGROUND In the past few years numerous mobile games have been developed to train the brain. There is a lack of information about the relation between the scores obtained in these games and the cognitive abilities of the patients. OBJECTIVE The aim of this study was to determine whether or not mobile games can be used to assess cognitive abilities of elderly. METHODS Twenty healthy young adults, 29 old patients with cognitive impairments (Mini-Mental State Exam (MMSE) [20- 24]) and 27-aged controls participated in this study. Scores obtained in 7 mobile games were correlated with MMSE and the Addenbrooke's Cognitive Evaluation revised (ACE-R). RESULTS Statistically significant differences were found for all games between patients with cognitive impairments and the aged controls. Correlations between the average scores of the games and the MMSE and ACE-R are significant (R = 0.72 [p < 0.001] and R = 0.81 [p < 0.001], respectively). CONCLUSION Scores of cognitive mobile games could be used as an alternative to MMSE and ACE-R to evaluate cognitive function of aged people with and without cognitive impairment at least when MMSE is higher than 20/30.

The development of portable haematology analysers receives increased attention due to their deployability in resource-limited or emergency settings. Lens-free in-line holographic microscopy is one of the technologies that is being pushed forward in this regard as it eliminates complex and expensive optics, making miniaturisation and integration with microfluidics possible. On-chip flow cytometry enables high-speed capturing of individual cells in suspension, giving rise to high-throughput cell counting and classification. To perform a real-time analysis on this high-throughput content, we propose a fast and robust framework for the classification of leukocytes. The raw data consists of holographic acquisitions of leukocytes, captured with a high- speed camera as they are flowing through a microfluidic chip. Three different types of leukocytes are considered: granulocytes, monocytes and T-lymphocytes. The proposed method bypasses the reconstruction of the holographic data altogether by extracting Zernike moments directly from the frequency domain. By doing so, we introduce robustness to translations and rotations of cells, as well as to changes in distance of a cell with respect to the image sensor, achieving classification accuracies up to 96.8%. Furthermore, the reduced computational complexity of this approach, compared to traditional frameworks that involve the reconstruction of the holographic data, allows for very fast processing and classification, making it applicable in high-throughput flow cytometry setups.

Optoelectronic devices are the gold standard for 3D evaluation in clinics, but due to the complexity of this kind of hardware and the lack of access for patients, affordable, transportable, and easy-to-use systems must be developed to be largely used in daily clinics. The KinectTM sensor has various advantages compared to optoelectronic devices, such as its price and transportability. However, it also has some limitations: (in)accuracy of the skeleton detection and tracking as well as the limited amount of available points, which makes 3D evaluation impossible. To overcome these limitations, a novel method has been developed to perform 3D evaluation of the upper limbs. This system is coupled to rehabilitation exercises, allowing functional evaluation while performing physical rehabilitation. To validate this new approach, a two-step method was used. The first step was a laboratory validation where the results obtained with the KinectTM were compared with the results obtained with an optoelectronic device; 40 healthy young adults participated in this first part. The second step was to determine the clinical relevance of this kind of measurement. Results of the healthy subjects were compared with a group of 22 elderly adults and a group of 10 chronic stroke patients to determine if different patterns could be observed. The new methodology and the different steps of the validations are presented in this paper.

Purpose: Cerebral palsy (CP) leads to various clinical signs mainly induced by muscle spasticity and muscle weakness. Among these ones impaired balance and posture are very common. Traditional physical therapy exercise programs are focusing on this aspect, but it is difficult to motivate patients to regularly perform these exercises, especially at home without therapist supervision. Specially developed serious games (SG) could therefore be an interesting option to motivate children to perform specific exercise for balance improvement. Method: Ten CP children participated in this study. Patients received four sessions of SG included into conventional therapy (1 session of 30 min a week during 4 weeks). Trunk control and balance were assessed using Trunk Control Motor Scale (TCMS) before and after interventions. Results: Children presented a significant improvement in TCMS global score after interventions [37.6 (8.7) and 39.6 (9.5) before and after interventions, respectively, p = 0.04]. Conclusion: SG could therefore be an interesting option to integrate in the conventional treatment of CP children.Implication for RehabilitationCerebral palsy (CP) leads to balance issues.Rehabilitation exercises are not performed (enough) at home.Serious games (SG) could increase patients’ motivation.SG increase balance control of CP children. Cerebral palsy (CP) leads to balance issues. Rehabilitation exercises are not performed (enough) at home. Serious games (SG) could increase patients’ motivation. SG increase balance control of CP children.

info:eu-repo/semantics/published

Feature Selective Neuroevolution of Augmenting Topologies (FS-NEAT) and Feature Deselective Neuroevolution of Augmenting Topologies (FD-NEAT) are two popular methods for optimizing the topology and the weights of Artificial Neural Networks (ANNs) simultaneously with performing feature selection. However, no study exists that systematically investigates their performance on the exclusive-or (XOR) problem with increasing complexity. Moreover, it is unknown whether the choice of a different initial topology of the ANNs would influence the performance of the two algorithms. For this reasons, this paper investigates the performance of FD-NEAT and FS-NEAT in terms of accuracy, number of generations required for their convergence to the optimal solution and their ability of selecting the relevant features in artificial datasets with irrelevant features. The comparisons are performed based on hypothesis tests (Wilcoxon rank sum test, p

This editorial paper is an introduction to the special Yuridika edition about the ‘Sustainable Market Actors for Responsible Trade’ project (SMART). SMART identifies the areas in which companies and other market players can realise their unfulfilled potential to contribute in their own way to development friendly, environmentally friendly, and socially sustainable business, trade, and investment. SMART creates more awareness on how nondevelopment policies and regulations reinforce or undermine EU development policies. The research presented in this special Yuridika edition aims to find these legal means to reduce the gap between law and reality. In this Editorial, the various contributions to this special edition of the journal Yuridika will be introduced

Depuis longtemps, le jeu fait partie integrante de la societe et intervient dans divers processus d’apprentissage. D’abord extremement rudimentaires (exemple du jeu des osselets), les jeux se sont peu a peu complexifies. Avec l’avenement de la technologie a la fin des annees 1970, les jeux sont entres dans une nouvelle dimension, celle du jeu video (JV). Le but de cet article n’est pas de debattre des derives negatives que pourraient engendrer ces jeux (vio-lence, perte du contact social, etc.), mais d’identifier les nouvelles possibili-tes que ces derniers offrent aux patients et aux therapeutes.L’idee d’integrer des jeux video dans la prise en charge d’un patient n’est pas neuve, mais l’essor actuel des tech-niques de realites virtuelles s’explique par l’augmentation grandissante de la technologie et, surtout, par une demo-cratisation importante de l’equipement requis pour jouer.Avant d’explorer les differentes appli-cations possibles des jeux video en rea-daptation, il convient de preciser cer-tains termes. Les

Contains fulltext : 179531.pdf (Publisher’s version ) (Open Access) Automatic detection of pulmonary nodules in thoracic computed tomography (CT) scans has been an active area of research for the last two decades. However, there have only been few studies that provide a comparative performance evaluation of different systems on a common database. We have therefore set up the LUNA16 challenge, an objective evaluation framework for automatic nodule detection algorithms using the largest publicly available reference database of chest CT scans, the LIDC-IDRI data set. In LUNA16, participants develop their algorithm and upload their predictions on 888 CT scans in one of the two tracks: 1) the complete nodule detection track where a complete CAD system should be developed, or 2) the false positive reduction track where a provided set of nodule candidates should be classified. This paper describes the setup of LUNA16 and presents the results of the challenge so far. Moreover, the impact of combining individual systems on the detection performance was also investigated. It was observed that the leading solutions employed convolutional networks and used the provided set of nodule candidates. The combination of these solutions achieved an excellent sensitivity of over 95% at fewer than 1.0 false positives per scan. This highlights the potential of combining algorithms to improve the detection performance. Our observer study with four expert readers has shown that the best system detects nodules that were missed by expert readers who originally annotated the LIDC-IDRI data. We released this set of additional nodules for further development of CAD systems. 13 p.

In the last decade, technological advances in the gaming industry have allowed the marketing of hardware for motion and balance control that is based on technological concepts similar to scientific and clinical equipment. Such hardware is attractive to researchers and clinicians for specific applications. However, some questions concerning their scientific value and the range of future potential applications have yet to be answered. This article attempts to present an objective analysis about the pros and cons of using such hardware for scientific and clinical purposes and calls for a constructive discussion based on scientific facts and practical clinical requests that are emerging from application fields.

To date, the major dilemma concerning frailty is the lack of a standardized language regarding its operationalization. Considering the demographic challenge that the world is facing, standardization of frailty identification is indeed the first step in tackling the burdensome consequences of frailty. To demonstrate this diversity in frailty assessment, the available frailty instruments have been linked to the International Classification of Functioning, Disability, and Health (ICF): a standardized and hierarchically coded language developed by World Health Organization regarding health conditions and their positive (functioning) and negative (disability) consequences. A systematic review on frailty instruments was carried out in PubMed, Web of Knowledge, and PsycINFO. The items of the identified frailty instruments were then linked to the ICF codes. 79 original or adapted frailty instruments were identified and categorized into single (n = 25) and multidomain (n = 54) groups. Only 5 frailty instruments (indexes) were linked to all 5 ICF components. Whereas the ICF components Body Functions and Activities and Participation were frequently linked to the frailty instruments, Body Structures, Environmental and Personal factors were sparingly represented mainly in the multidomain frailty instruments. This review highlights the heterogeneity in frailty operationalization. Environmental and personal factors should be given more thought in future frailty assessments. Being unambiguous, structured, and neutral, the ICF language allows comparing observations made with different frailty instruments. In conclusion, this systematic overview and ICF translation can be a cornerstone for future standardization of frailty assessment.

Purpose: The paper presents a complete computer-aided detection (CAD) system for the detection of lung nodules in computed tomography images. A new mixed feature selection and classification methodology is applied for the first time on a difficult medical image analysis problem. Methods: The CAD system was trained and tested on images from the publicly available Lung Image Database Consortium (LIDC) on the National Cancer Institute website. The detection stage of the system consists of a nodule segmentation method based on nodule and vessel enhancement filters and a computed divergence feature to locate the centers of the nodule clusters. In the subsequent classification stage, invariant features, defined on a gauge coordinates system, are used to differentiate between real nodules and some forms of blood vessels that are easily generating false positive detections. The performance of the novel feature-selective classifier based on genetic algorithms and artificial neural networks (ANNs) is compared with that of two other established classifiers, namely, support vector machines (SVMs) and fixed-topology neural networks. A set of 235 randomly selected cases from the LIDC database was used to train the CAD system. The system has been tested on 125 independent cases from the LIDC database. Results: The overall performancemore » of the fixed-topology ANN classifier slightly exceeds that of the other classifiers, provided the number of internal ANN nodes is chosen well. Making educated guesses about the number of internal ANN nodes is not needed in the new feature-selective classifier, and therefore this classifier remains interesting due to its flexibility and adaptability to the complexity of the classification problem to be solved. Our fixed-topology ANN classifier with 11 hidden nodes reaches a detection sensitivity of 87.5% with an average of four false positives per scan, for nodules with diameter greater than or equal to 3 mm. Analysis of the false positive items reveals that a considerable proportion (18%) of them are smaller nodules, less than 3 mm in diameter. Conclusions: A complete CAD system incorporating novel features is presented, and its performance with three separate classifiers is compared and analyzed. The overall performance of our CAD system equipped with any of the three classifiers is well with respect to other methods described in literature.« less

Product-oriented policies gain more and more attention in environmental policies. In this framework, we studied cases (here presented only housing and computers and paper) in a life cycle perspective in order to determine their environmental impacts (in terms of GHG emissions, resource use and waste production) over the period 1990–2010. We also evaluated their potential for improvement up to 2010 by applying product-oriented strategies. We identified clear technical (theoretical) potential for improvement, especially for housing, packaging and computers and paper in offices. We then carried out a Delphi-based survey among stakeholders in order to investigate potential measures.

SummaryIntroduction: This article is part of the Focus Theme of Methods of Information in Medicine on “Methodologies, Models and Algorithms for Patients Rehabilitation”. Objectives: This paper presents a camera based method for identifying the patient and detecting interactions between the patient and the therapist during therapy. Detecting interactions helps to discriminate between active and passive motion of the patient as well as to estimate the accuracy of the skeletal data. Methods: Continuous face recognition is used to detect, recognize and track the patient with other people in the scene (e.g. the therapist, or a clinician). We use a method based on local binary patterns (LBP). After identifying users in the scene we identify interactions between the patient and other people. We use a depth map/point cloud for estimating the distance between two people. Our method uses the association of depth regions to user identities and computes the minimal distance between the regions. Results: Our results show state-of-the-art performance of real-time face recognition using low-resolution images that is sufficient to use in adaptive systems. Our proposed approach for detecting interactions shows 91.9% overall recognition accuracy what is sufficient for applications in the context of serious games. We also discuss limitations of the proposed method as well as general limitations of using depth cameras for serious games. Conclusions: We introduced a new method for frame-by-frame automated identification of the patient and labeling reliable sequences of the patient’s data recorded during rehabilitation (games). Our method improves automated rehabilitation systems by detecting the identity of the patient as well as of the therapist and by detecting the distance between both over time.

Due to the increase of life expectancy age-related cognitive decline and dementia are a major health issue. Regular evaluation and follow-up must be performed to assess cognitive functions. Regular training (lectures, memory exercises, calculation...) is the best way to preserve cognitive function. Since a few years plenty of video games have been developed to train the brain. Evidence started to emerge about the efficacy of such kind of intervention. However there is a lack of information about the relation between the scores obtained in the games and the cognitive function of the patients. Therefore the aim of this study was to determine if there are correlations between scores obtained from the games and cognitive function. Twenty 18-aged controls and 16 patients with cognitive impairments (MMSE >20) participated in this study. Scores obtained in 8 mini-games were correlated with MMSE and the revised version of the Addenbrooke's Cognitive Evaluation (ACER). Mean correlation between the 8 games and the MMSE is 0.62 and 0.65 for the ACE-R. Those results seems to indicate that cognitive video games could be used to follow evolution of cognitive function of aged people with and without cognitive impairment at least when MMSE is > 20/30.

Summary The present study shows the results and methodology applied to the study of the identification of priority product categories for Belgian product and environmental policy. The main goal of the study was to gather insight into the consumption of products in Belgium and their related life-cycle environmental impacts. The conclusions of this project on the product categories with major environmental contributions can be used to start up working groups involving stakeholders and initiate detailed product studies on the impact reduction potential that could be achieved by means of implementing product policy measures. Several ways of assessing product category environmental impacts and the effects of policy measures have been developed; ‘bottom-up’ or ‘market-life-cycle assessment’ is one of these, and we tried this approach for the situation in Belgium. Simplified life-cycle assessment (LCA) studies were conducted for representative average products within each function-based product category and the results were multiplied with market statistics. Using this approach, we found that building construction, building occupancy, and personal transport are among the major categories for Belgium. The major drawbacks of this approach are the system-level limitations and the existence of a broad spectrum of nonharmonized methods and datasets from which a sound preliminary selection had to be made. Consequently, the retrieval and selection of data was very time consuming and due to this we had to accept some major limitations in the study design. Nevertheless, the study has contributed to the development of a methodology for market-LCA and elements that can be picked up in currently ongoing and future work. The study concludes that to improve the feasibility and acceptance of this type of study there is a need for the development of a harmonized methodology on market-LCA, policy-relevant impact indicators as well as a harmonized and stakeholder-agreed-upon LCA databases.

Environmental effects of economic activities are ultimately driven by consumption, via impacts of the production, use, and waste management phases of products and services ultimately consumed. Integrated product policy (IPP) addressing the life-cycle impacts of products forms an innovative new generation of environmental policy. Yet this policy requires insight into the final consumption expenditures and related products that have the greatest life-cycle environmental impacts. This review article brings together the conclusions of 11 studies that analyze the life-cycle impacts of total societal consumption and the relative importance of different final consumption categories. This review addresses in general studies that were included in the project Environmental Impacts of Products (EIPRO) of the European Union (EU), which form the basis of this special issue. Unlike most studies done in the past 25 years on similar topics, the studies reviewed here covered a broad set of environmental impacts beyond just energy use or carbon dioxide (CO2) emissions. The studies differed greatly in basic approach (extrapolating LCA data to impacts of consumption categories versus approaches based on environmentally extended input-output (EEIO) tables), geographical region, disaggregation of final demand, data inventory used, and method of impact assessment. Nevertheless, across all studies a limited number of priorities emerged. The three main priorities, housing, transport, and food, are responsible for 70% of the environmental impacts in most categories, although covering only 55% of the final expenditure in the 25 countries that currently make up the EU. At a more detailed level, priorities are car and most probably air travel within transport, meat and dairy within food, and building structures, heating, and (electrical) energy-using products within housing. Expenditures on clothing, communication, health care, and education are considerably less important. Given the very different approaches followed in each of the sources reviewed, this result hence must be regarded as extremely robust. Recommendations are given to harmonize and improve the methodological approaches of such analyses, for instance, with regard to modeling of imports, inclusion of capital goods, and making an explicit distinction between household and government expenditure. © 2006 by the Massachusetts Institute of Technology and Yale University.

This paper presents a novel classification approach for microcalcifications extracted from core biopsy tissue samples digitized using micro-CT, a high-resolution 3D imaging modality. Microcalcifications are tiny spots of calcium that may occur in the female breast. Although they are common in healthy woman, they are often an early sign of breast cancer. In case of suspiciousness, a biopsy is conducted and the extracted tissue is pathologically analyzed for the presence of cancer cells. The calcifications themselves however are mostly not analyzed. As a result, there is a ground truth for the tissue samples but not for the individual calcifications. Therefore, this paper presents an approach where the calcifications are first classified according to shape-based clusters before predicting a label for the tissue samples.

The Kinect™ (Microsoft™, Redmond, WA) sensor, originally developed for gaming purposes, may have interesting possibilities for other fields such as posture and motion assessment. The ability of the Kinect sensor to perform biomechanical measurements has previously been studied and shows promising results. However, interday repeatability of the device is still not known.This study assessed the intra- and interday repeatability of the Kinect sensor compared with a standard stereophotogrammetric device during posture assessment for measuring segment lengths. Forty subjects took part in the study. Five motionless captures were performed in one session to assess posture. Data were simultaneously recorded with both devices.Similar intraclass correlations coefficient (ICC) values were found for intraday (ICC=0.94 for the Kinect device and 0.98 for the stereophotogrammetric device) and interday (ICC=0.88 and 0.87, respectively) repeatability.Results of this study suggest that a cost-effective, easy-to-use, and portable single markerless camera offers the same repeatability during posture assessment as an expensive, time-consuming, and nontransportable marker-based device.

The recent availability of the Kinect™ sensor, a low-cost Markerless Motion Capture (MMC) system, could give new and interesting insights into ergonomics (e.g. the creation of a morphological database). Extensive validation of this system is still missing. The aim of the study was to determine if the Kinect™ sensor can be used as an easy, cheap and fast tool to conduct morphology estimation. A total of 48 subjects were analysed using MMC. Results were compared with measurements obtained from a high-resolution stereophotogrammetric system, a marker-based system (MBS). Differences between MMC and MBS were found; however, these differences were systematically correlated and enabled regression equations to be obtained to correct MMC results. After correction, final results were in agreement with MBS data (p = 0.99). Results show that measurements were reproducible and precise after applying regression equations. Kinect™ sensors-based systems therefore seem to be suitable for use as fast and reliable tools to estimate morphology. Practitioner Summary: The Kinect™ sensor could eventually be used for fast morphology estimation as a body scanner. This paper presents an extensive validation of this device for anthropometric measurements in comparison to manual measurements and stereophotogrammetric devices. The accuracy is dependent on the segment studied but the reproducibility is excellent.

Iris recognition has gained a lot of popularity for the last decades. Mainly a method based on binary iris templates found its way to real world use due to its simplicity, stability and reliability. The principle is that the unique iris structure is encoded to the bit code templates that are sufficient for high accuracy recognition. Encoding is performed by filtering a preprocessed iris image and storing only the phase information of the response to the filters. For years researchers used the 2D Gabor filters or their modifications, because these filters proved to provide the most reliable features. Despite the high recognition accuracy, the use of 2D Gabor filters faces a problem of spoofing. Recent studies show that the encoding process can be reverted and a spoofed iris can be obtained only based on the iris code. In this paper, we propose an efficient feature extraction method for iris recognition based on convolution kernels, learned from a database of irises. We show that the proposed method reaches state-of-the-art performance and can prohibit attackers from generating spoofed irises if the optimized convolution kernel is safely stored.

The recent availability of the Kinect™ sensor, a cost-effective markerless motion capture system (MLS), offers interesting possibilities in clinical functional analysis and rehabilitation. However, neither validity nor reproducibility of this device is known yet. These two parameters were evaluated in this study. Forty-eight volunteers performed shoulder abduction, elbow flexion, hip abduction and knee flexion motions; the same protocol was repeated one week later to evaluate reproducibility. Movements were simultaneously recorded by the Kinect (with Microsoft Kinect SDK v.1.5) MLS and a traditional marker-based stereophotogrammetry system (MBS). Considering the MBS as reference, discrepancies between MLS and MBS were evaluated by comparing the range of motion (ROM) between both systems. MLS reproducibility was found to be statistically similar to MBS results for the four exercises. Measured ROMs however were found different between the systems.