Mobile monitoring application to support sustainable behavioural change towards healthy lifestyle

We describe the development of body area networks (BANs) incorporating sensors and other devices to provide intelligent mobile services in healthcare and well-being. The first BAN applications were designed to simply transmit biosignals and display them remotely. Further developments include analysis and interpretation of biosignals in the light of context data. By including feedback loops, BAN telemonitoring was also augmented with teletreatment services. Recent developments include incorporation of clinical decision support by applying techniques from artificial intelligence. These developments represent a movement towards smart healthcare, making health BAN applications more intelligent by incorporating feedback, context awareness, personalization, and decision support.\ud The element of decision support was first introduced into the BAN health and well-being applications in the Food Valley Eating Advisor (FOVEA) project. Obesity and overweight represent a growing threat to health and well-being in modern society. Physical inactivity has been shown to contribute significantly to morbidity and mortality rates, and this is now a global trend bringing huge costs in terms of human suffering and reduction in life expectancy as well as uncontrolled growth in demand on healthcare services. Part of the solution is to foster healthier lifestyle. A major challenge however is that exercise and dietary programs may work for the individual in the short term, but adherence in the medium and long term is difficult to sustain, making weight management a continuing struggle for individuals and a growing problem for society, governments, and health services. Using ICT to support sustainable behavioral change in relation to healthy exercise and diet is the goal of the FOVEA monitoring and feedback application. We strive to design and develop intelligent BAN-based applications that support motivation and adherence in the long term. We present this healthy lifestyle application and report results of an evaluation conducted by surveying professionals in related disciplines

Measuring Behavior in the Home Cage : Study Design, Applications, Challenges, and Perspectives

FUNDING This research was supported by NIH grants R00AG056662, P20GM125528, AG057424 to WS and SLPeer reviewedPublisher PD

Using implicit rather than explicit measures of emotions

Implicit and explicit measures are typically combined in laboratory food studies. Results of these laboratory studies often show little additional value of implicit compared to explicit measures. We argue that implicit measures of food experience should not be regarded as a more expensive and more complex equivalent of established explicit measures. Instead, each type of measure provides complementary information. Whereas explicit measures capture especially the sensory aspects of the food itself, implicit measures capture especially the total food experience from pre- to post- consumption, which not only relates to the food itself but also to factors such as the physical and social context in which foods are consumed in real life. This requires that implicit measures are applied outside the conventional laboratory habitat. Fortunately, this becomes increasingly possible with current technical developments.</p

Muscle Hyperalgesia Correlates With Motor Function in Complex Regional Pain Syndrome Type 1

At present it is unclear if disturbed sensory processing plays a role in the development of the commonly observed motor impairments in patients with complex regional pain syndrome (CRPS). This study aims to investigate the relation between sensory and motor functioning in CRPS patients with and without dystonia. Patients with CRPS of the arm and controls underwent comprehensive quantitative sensory testing and kinematic analysis of repetitive finger movements. Both CRPS groups showed thermal hypoesthesia to cold and warm stimuli and hyperalgesia to cold stimuli. A decreased pressure pain threshold reflecting muscle hyperalgesia emerged as the most prominent sensory abnormality in both patient groups and was most pronounced in CRPS patients with dystonia. Moreover, the decreased pressure pain threshold was the only nociceptive parameter that related to measures of motor function in both patients and controls. CRPS patients with dystonia had an increased 2-point discrimination as compared to controls and CRPS patients without dystonia. This finding was also reported in other types of dystonia and has been associated to cortical reorganization in response to impaired motor function. We hypothesize that increased sensitivity of the circuitry mediating muscle nociception may play a crucial role in impaired motor control in CRPS

Muscle Hyperalgesia Correlates With Motor Function in Complex Regional Pain Syndrome Type 1

At present it is unclear if disturbed sensory processing plays a role in the development of the commonly observed motor impairments in patients with complex regional pain syndrome (CRPS). This study aims to investigate the relation between sensory and motor functioning in CRPS patients with and without dystonia. Patients with CRPS of the arm and controls underwent comprehensive quantitative sensory testing and kinematic analysis of repetitive finger movements. Both CRPS groups showed thermal hypoesthesia to cold and warm stimuli and hyperalgesia to cold stimuli. A decreased pressure pain threshold reflecting muscle hyperalgesia emerged as the most prominent sensory abnormality in both patient groups and was most pronounced in CRPS patients with dystonia. Moreover, the decreased pressure pain threshold was the only nociceptive parameter that related to measures of motor function in both patients and controls. CRPS patients with dystonia had an increased 2-point discrimination as compared to controls and CRPS patients without dystonia. This finding was also reported in other types of dystonia and has been associated to cortical reorganization in response to impaired motor function. We hypothesize that increased sensitivity of the circuitry mediating muscle nociception may play a crucial role in impaired motor control in CRPS

An Integrated System for the Automated Recording and Analysis of Insect Behavior in T-maze Arrays

Host-plant resistance to insects like thrips and aphids is a complex trait that is difficult to phenotype quickly and reliably. Here, we introduce novel hardware and software to facilitate insect choice assays and automate the acquisition and analysis of movement tracks. The hardware consists of an array of individual T-mazes allowing simultaneous release of up to 90 insect individuals from their individual cage below each T-maze with choice of two leaf disks under a video camera. Insect movement tracks are acquired with computer vision software (EthoVision) and analyzed with EthoAnalysis, a novel software package that allows for automated reporting of highly detailed behavior parameters andstatistical analysis. To validate the benefits of the system we contrasted two Arabidopsis accessions that were previously analyzed for differential resistance to western flower thrips. Results of two trials with 40 T-mazes are reported and we show how we arrived at optimized settings for the different filters and statistics. The statistics are reported in terms of frequency, duration, distance and speed of behavior events, both as sum totals and event averages, and both for the total trial period and in time bins of 1 h. Also included are higher level analyses with subcategories like short-medium-long events and slow-medium-fast events. The time bins showed how some behavior elements are more descriptive of differences between the genotypes during the first hours, whereasothers are constant or become more relevant at the end of an 8 h recording. The three overarching behavior categories, i.e., choice, movement, and halting, were automatically corrected for the percentage of time thrips were detected and 24 out of 38 statistics of behavior parameters differed by a factor 2–6 between the accessions. The analysis resulted in much larger contrasts in behavior traits than reported previously. Compared to leaf damage assays on whole plants or detached leaves that take a week or more to complete, results were obtained in 8 h, with more detail, fewer individuals and higher significance. The potential value of the new integrated system, named EntoLab, for discovery of genetic traits in plants and insects by high throughput screening of large populations is discussed

Automated video tracking of thrips behavior to assess host-plant resistance in multiple parallel two-choice setups

Background: Piercing-sucking insects cause severe damage in crops. Breeding for host-plant resistance can significantly reduce the yield losses caused by these insects, but host-plant resistance is a complex trait that is difficult to phenotype quickly and reliably. Current phenotyping methods mainly focus on labor-intensive and time-consuming end-point measurements of plant fitness. Characterizing insect behavior as a proxy for host-plant resistance could be a promising time-saving alternative to end-point measurements. Results: We present a phenotyping platform that allows screening for host-plant resistance against Western flower thrips (WFT, Frankliniella occidentalis (Pergande)) in a parallel two-choice setup using automated video tracking of thrips behavior. The platform was used to establish host-plant preference of WFT with a large plant population of 345 wild Arabidopsis accessions and the method was optimized with two extreme accessions from this population that differed in resistance towards WFT. To this end, the behavior of 88 WFT individuals was simultaneously tracked in 88 parallel two-choice arenas during 8 h. Host-plant preference of WFT was established both by the time thrips spent on either accession and various behavioral parameters related to movement (searching) and non-movement (feeding) events. Conclusion: In comparison to 6-day end-point choice assays with whole plants or detached leaves, the automated video-tracking choice assay developed here delivered similar results, but with higher time- and resource efficiency. This method can therefore be a reliable and effective high throughput phenotyping tool to assess host-plant resistance to thrips in large plant populations

Mobile monitoring application to support sustainable behavioural change towards healthy lifestyle

We describe the development of body area networks (BANs) incorporating sensors and other devices to provide intelligent mobile services in healthcare and well-being. The first BAN applications were designed to simply transmit biosignals and display them remotely. Further developments include analysis and interpretation of biosignals in the light of context data. By including feedback loops, BAN telemonitoring was also augmented with teletreatment services. Recent developments include incorporation of clinical decision support by applying techniques from artificial intelligence. These developments represent a movement towards smart healthcare, making health BAN applications more intelligent by incorporating feedback, context awareness, personalization, and decision support. The element of decision support was first introduced into the BAN health and well-being applications in the Food Valley Eating Advisor (FOVEA) project. Obesity and overweight represent a growing threat to health and well-being in modern society. Physical inactivity has been shown to contribute significantly to morbidity and mortality rates, and this is now a global trend bringing huge costs in terms of human suffering and reduction in life expectancy as well as uncontrolled growth in demand on healthcare services. Part of the solution is to foster healthier lifestyle. A major challenge however is that exercise and dietary programs may work for the individual in the short term, but adherence in the medium and long term is difficult to sustain, making weight management a continuing struggle for individuals and a growing problem for society, governments, and health services. Using ICT to support sustainable behavioral change in relation to healthy exercise and diet is the goal of the FOVEA monitoring and feedback application. We strive to design and develop intelligent BAN-based applications that support motivation and adherence in the long term. We present this healthy lifestyle application and report results of an evaluation conducted by surveying professionals in related disciplines