Optimization of fuzzy rule sets using a bacterial evolutionary algorithm

In this paper we present a novel approach where we rst create a large set of (possibly) redundant rules using inductive rule learning and where we use a bacterial evolutionary algorithm to identify the best subset of rules in a subsequent step. This enables us to nd an optimal rule set with respect to a freely de nable global goal function, which gives us the possibility to integrate interpretability related quality criteria explicitly in the goal function and to consider the interplay of the overlapping fuzzy rulesPeer Reviewe

Extending the Medical Concept of Reference Intervals using Fuzzy Predicates

Abstract Expert systems for medical applications have to deal with medical concepts such as "normal range", "elevated", or "reduced". These concepts, although backed by a profound medical background based on reference intervals, are defined manually by physicians using interval-based representation. This approach is usually not feasible in largescale applications. In the present study we describe a method to generate fuzzy-logic-based predicates founded on historic medical data, using a combination of established statistical methods and cluster analyses to generate concepts that correspond to established laboratory standards and the physician's interpretation. We also describe visualization techniques which help the physician to analyze and adapt the results according to clinical needs. Finally, a case study using actual laboratory data from 562 hepatitis patients is presented

Validation of a method for the estimation of energy expenditure during physical activity using a mobile device accelerometer

The main goal of this paper consists on the adaption and validation of a method for the measurement of the energy expenditure during physical activities. Sensors available in a mobile device, e.g., a smartphone, a smartwatch, or others, allow the capture of several signals, which may be used to the estimation of the energy expenditure. The adaption consists in the comparison between the units of the data acquired by a tri-axial accelerometer and a mobile device accelerometer. The tests were performed by healthy people with ages between 12 and 50 years old that performed several activities, such as standing, gym (walking), climbing stairs, walking, jumping, running, playing tennis, and squatting, with a mobile device on the waist. The validation of the method showed that the energy expenditure is underestimated and super estimated in some cases, but with reliable results. The creation of a validated method for the measurement of energy expenditure during physical activities capable for the implementation in a mobile application is an important issue for increase the acceptance of the mobile applications in the market. As verified the results obtained are around 124.6 kcal/h, for walking activity, and 149.7 kcal/h, for running activity.This work was supported by FCT project PEst-OE/EEI/L A0008/2013 (Este trabalho foi suportado pelo projecto FCT PEst-OE/EEI/LA0008/2013). The authors would also like to acknowledge the contribution of the COST Action IC1303 – AAPELE – Architectures, Algorithms and Protocols for Enhanced Living Environments

ICT-based system to predict and prevent falls (iStoppFalls): study protocol for an international multicenter randomized controlled trial

[EN] Background: Falls are very common, especially in adults aged 65 years and older. Within the current international European Commission's Seventh Framework Program (FP7) project 'iStoppFalls' an Information and Communication Technology (ICT) based system has been developed to regularly assess a person's risk of falling in their own home and to deliver an individual and tailored home-based exercise and education program for fall prevention. The primary aims of iStoppFalls are to assess the feasibility and acceptability of the intervention program, and its effectiveness to improve balance, muscle strength and quality of life in older people. Methods/Design: This international, multicenter study is designed as a single-blinded, two-group randomized controlled trial. A total of 160 community-dwelling older people aged 65 years and older will be recruited in Germany (n = 60), Spain (n = 40), and Australia (n = 60) between November 2013 and May 2014. Participants in the intervention group will conduct a 16-week exercise program using the iStoppFalls system through their television set at home. Participants are encouraged to exercise for a total duration of 180 minutes per week. The training program consists of a variety of balance and strength exercises in the form of video games using exergame technology. Educational material about a healthy lifestyle will be provided to each participant. Final reassessments will be conducted after 16 weeks. The assessments include physical and cognitive tests as well as questionnaires assessing health, fear of falling, quality of life and psychosocial determinants. Falls will be followed up for six months by monthly falls calendars. Discussion: We hypothesize that the regular use of this newly developed ICT-based system for fall prevention at home is feasible for older people. By using the iStoppFalls sensor-based exercise program, older people are expected to improve in balance and strength outcomes. In addition, the exercise training may have a positive impact on quality of life by reducing the risk of falls. Taken together with expected cognitive improvements, the individual approach of the iStoppFalls program may provide an effective model for fall prevention in older people who prefer to exercise at home.The authors are members of the iStoppFalls project. This project has received funding from the European Union’s Seventh Framework Programme for research, technological development, and demonstration under grant agreement no [287361]. The Australian arm is funded by an Australian National Health and Medical Research Council (NHMRC) EU collaboration grant (#1038210). The content of the manuscript does not represent the opinion of the European Community or NHMRC. The funding sources have no role in any aspects of this study. Yves J. Gschwind has been financially supported by a research grant from the Margarete and Walter Lichtenstein Foundation, Basel, Switzerland. Stephen R. Lord is supported by NHMRC as a Senior Principal Research Fellow and Kim Delbaere as a NHMRC Career Development Fellow. All other authors are supported by the iStoppFalls project, European Community Grant Agreement 287361. On behalf the iStoppFalls consortium, we would like to thank all the participants who take part in the study.Gschwind, YJ.; Eichberg, S.; Marston, HR.; Ejupi, A.; De Rosario Martínez, H.; Kroll, M.; Drobics, M.... (2014). ICT-based system to predict and prevent falls (iStoppFalls): study protocol for an international multicenter randomized controlled trial. BMC Geriatrics. 14(91):1-13. https://doi.org/10.1186/1471-2318-14-91S1131491Berchicci M, Lucci G, Di Russo F: Benefits of physical exercise on the aging brain: the role of the prefrontal cortex. 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ICT-based system to predict and prevent falls (iStoppFalls): results from an international multicenter randomized controlled trial

Background: Falls and fall-related injuries are a serious public health issue. Exercise programs can effectively reduce fall risk in older people. The iStoppFalls project developed an Information and Communication Technology-based system to deliver an unsupervised exercise program in older people’s homes. The primary aims of the iStoppFalls randomized controlled trial were to assess the feasibility (exercise adherence, acceptability and safety) of the intervention program and its effectiveness on common fall risk factors. Methods: A total of 153 community-dwelling people aged 65+ years took part in this international, multicentre, randomized controlled trial. Intervention group participants conducted the exercise program for 16 weeks, with a recommended duration of 120 min/week for balance exergames and 60 min/week for strength exercises. All intervention and control participants received educational material including advice on a healthy lifestyle and fall prevention. Assessments included physical and cognitive tests, and questionnaires for health, fear of falling, number of falls, quality of life and psychosocial outcomes. Results: The median total exercise duration was 11.7 h (IQR = 22.0) over the 16-week intervention period. There were no adverse events. Physiological fall risk (Physiological Profile Assessment, PPA) reduced significantly more in the intervention group compared to the control group (F1,127 = 4.54, p = 0.035). There was a significant three-way interaction for fall risk assessed by the PPA between the high-adherence (>90 min/week; n = 18, 25.4 %), low-adherence (n = 53, 74.6 %) and control group (F2,125 = 3.12, n = 75, p = 0.044). Post hoc analysis revealed a significantly larger effect in favour of the high-adherence group compared to the control group for fall risk (p = 0.031), postural sway (p = 0.046), stepping reaction time (p = 0.041), executive functioning (p = 0.044), and quality of life (p for trend = 0.052). Conclusions: The iStoppFalls exercise program reduced physiological fall risk in the study sample. Additional subgroup analyses revealed that intervention participants with better adherence also improved in postural sway, stepping reaction, and executive function

Optimization of fuzzy rule sets using a bacterial evolutionary algorithm

In this paper we present a novel approach where we rst create a large set of (possibly) redundant rules using inductive rule learning and where we use a bacterial evolutionary algorithm to identify the best subset of rules in a subsequent step. This enables us to nd an optimal rule set with respect to a freely de nable global goal function, which gives us the possibility to integrate interpretability related quality criteria explicitly in the goal function and to consider the interplay of the overlapping fuzzy rulesPeer Reviewe

Game-based IT solutions for active and healthy ageing

Game-based approaches can be used to support traditional intervention schemes which enable older adults in staying active & healthy for a longer time. These techniques are especially useful as they improve the motivation of the users and thus help to improve the effectiveness of the intervention. TV-based games are often oriented along traditional video games. External sensors like video cameras can be incorporated to provide direct feedback on the activities of the user. This information can also be utilized to reassess the status of the user and monitor his/her training progress. Mobile devices and the large range of available body worn sensors offer the opportunity to design games around daily and outdoor activities. By adding a social level to the games, competition and group efforts can be initiated, giving further motivation to reach a certain goal. In this overview, we will present different approaches of game-based IT solutions to support active & healthy aging, including concrete examples from resent applications