Rationale, design and conduct of a randomised controlled trial evaluating a primary care-based complex intervention to improve the quality of life of heart failure patients: HICMan (Heidelberg Integrated Case Management) : study protocol

Background: Chronic congestive heart failure (CHF) is a complex disease with rising prevalence, compromised quality of life (QoL), unplanned hospital admissions, high mortality and therefore high burden of illness. The delivery of care for these patients has been criticized and new strategies addressing crucial domains of care have been shown to be effective on patients' health outcomes, although these trials were conducted in secondary care or in highly organised Health Maintenance Organisations. It remains unclear whether a comprehensive primary care-based case management for the treating general practitioner (GP) can improve patients' QoL. Methods/Design: HICMan is a randomised controlled trial with patients as the unit of randomisation. Aim is to evaluate a structured, standardized and comprehensive complex intervention for patients with CHF in a 12-months follow-up trial. Patients from intervention group receive specific patient leaflets and documentation booklets as well as regular monitoring and screening by a prior trained practice nurse, who gives feedback to the GP upon urgency. Monitoring and screening address aspects of disease-specific selfmanagement, (non)pharmacological adherence and psychosomatic and geriatric comorbidity. GPs are invited to provide a tailored structured counselling 4 times during the trial and receive an additional feedback on pharmacotherapy relevant to prognosis (data of baseline documentation). Patients from control group receive usual care by their GPs, who were introduced to guidelineoriented management and a tailored health counselling concept. Main outcome measurement for patients' QoL is the scale physical functioning of the SF-36 health questionnaire in a 12-month follow-up. Secondary outcomes are the disease specific QoL measured by the Kansas City Cardiomyopathy questionnaire (KCCQ), depression and anxiety disorders (PHQ-9, GAD-7), adherence (EHFScBS and SANA), quality of care measured by an adapted version of the Patient Chronic Illness Assessment of Care questionnaire (PACIC) and NTproBNP. In addition, comprehensive clinical data are collected about health status, comorbidity, medication and health care utilisation. Discussion: As the targeted patient group is mostly cared for and treated by GPs, a comprehensive primary care-based guideline implementation including somatic, psychosomatic and organisational aspects of the delivery of care (HICMAn) is a promising intervention applying proven strategies for optimal care. Trial registration: Current Controlled Trials ISRCTN30822978

Inter-hemispheric EEG coherence analysis in Parkinson's disease : Assessing brain activity during emotion processing

Parkinson’s disease (PD) is not only characterized by its prominent motor symptoms but also associated with disturbances in cognitive and emotional functioning. The objective of the present study was to investigate the influence of emotion processing on inter-hemispheric electroencephalography (EEG) coherence in PD. Multimodal emotional stimuli (happiness, sadness, fear, anger, surprise, and disgust) were presented to 20 PD patients and 30 age-, education level-, and gender-matched healthy controls (HC) while EEG was recorded. Inter-hemispheric coherence was computed from seven homologous EEG electrode pairs (AF3–AF4, F7–F8, F3–F4, FC5–FC6, T7–T8, P7–P8, and O1–O2) for delta, theta, alpha, beta, and gamma frequency bands. In addition, subjective ratings were obtained for a representative of emotional stimuli. Interhemispherically, PD patients showed significantly lower coherence in theta, alpha, beta, and gamma frequency bands than HC during emotion processing. No significant changes were found in the delta frequency band coherence. We also found that PD patients were more impaired in recognizing negative emotions (sadness, fear, anger, and disgust) than relatively positive emotions (happiness and surprise). Behaviorally, PD patients did not show impairment in emotion recognition as measured by subjective ratings. These findings suggest that PD patients may have an impairment of inter-hemispheric functional connectivity (i.e., a decline in cortical connectivity) during emotion processing. This study may increase the awareness of EEG emotional response studies in clinical practice to uncover potential neurophysiologic abnormalities

Repeatability of short-duration transient visual evoked potentials in normal subjects

To evaluate the within-session and inter-session repeatability of a new, short-duration transient visual evoked potential (SD-tVEP) device on normal individuals, we tested 30 normal subjects (20/20 visual acuity, normal 24-2 SITA Standard VF) with SD-tVEP. Ten of these subjects had their tests repeated within 1–2 months from the initial visit. Synchronized single-channel EEG was recorded using a modified Diopsys Enfant™ System (Diopsys, Inc., Pine Brook, New Jersey, USA). A checkerboard stimulus was modulated at two reversals per second. Two different contrasts of checkerboard reversal patterns were used: 85% Michelson contrast with a mean luminance of 66.25 cd/m2 and 10% Michelson contrast with a mean luminance of 112 cd/m2. Each test lasted 20 s. Both eyes, independently and together, were tested 10 times (5 times at each contrast level). The following information was identified from the filtered N75-P100-N135 complex: N75 amplitude, N75 latency, P100 amplitude, P100 latency, and Delta Amplitude (N75-P100). The median values for each eye’s five SD-tVEP parameters were calculated and grouped into two data sets based on contrast level. Mean age was 27.3 ± 5.2 years. For OD only, the median (95% confidence intervals) of Delta Amplitude (N75-P100) amplitudes at 10% and 85% contrast were 4.6 uV (4.1–5.9) and 7.1 uV (5.15–9.31). The median P100 latencies were 115.2 ms (112.0–117.7) and 104.0 ms (99.9–106.0). There was little within-session variability for any of these parameters. Intraclass correlation coefficients ranged between 0.64 and 0.98, and within subject coefficients of variation were 3–5% (P100 latency) and 15–30% (Delta Amplitude (N75-P100) amplitude). Bland–Altman plots showed good agreement between the first and fifth test sessions (85% contrast Delta Amplitude (N75-P100) delta amplitude, mean difference, 0.48 mV, 95% CI, −0.18–1.12; 85% contrast P100 latency delay, −0.82 ms, 95% CI, −3.12–1.46; 10% contrast Delta Amplitude (N75-P100) amplitude, 0.58 mV, 95% CI, −0.27–1.45; 10% contrast P100 latency delay, −2.05 mV, 95% CI, −5.12–1.01). The inter-eye correlation and agreement were significant for both SD-tVEP amplitude and P100 latency measurements. For the subset of eyes in which the inter-session repeatability was tested, the intraclass correlation coefficients ranged between 0.71 and 0.86 with good agreement shown on Bland–Altman plots. Short-duration transient VEP technology showed good within-session, inter-session repeatability, and good inter-eye correlation and agreement

Evaluation of TV commercials using neurophysiological responses

Background: In recent years, neuroscientific knowledge has been applied to marketing as a novel and efficient means to comprehend the cognitive and behavioral aspects of consumers. A number of studies have attempted to evaluate media contents, especially TV commercials using various neuroimaging techniques such as electroencephalography (EEG). Yet neurophysiological examination of detailed cognitive and affective responses in viewers is still required to provide practical information to marketers. Here, this study develops a method to analyze temporal patterns of EEG data and extract affective and cognitive indices such as happiness, surprise, and attention for TV commercial evaluation. Methods: Twenty participants participated in the study. We developed the neurophysiological indices for TV commercial evaluation using classification model. Specifically, these model-based indices were customized using individual EEG features. We used a video game for developing the index of attention and four video clips for developing indices of happiness and surprise. Statistical processes including one-way analyses of variance (ANOVA) and the cross validation scheme were used to select EEG features for each index. The EEG features were composed of the combinations of spectral power at selected channels from the cross validation for each individual. The Fisher's linear discriminant classifier (FLDA) was used to estimate each neurophysiological index during viewing four different TV commercials. Post hoc behavioral responses of preference, short-term memory, and recall were measured. Results: Behavioral results showed significant differences for all preference, short-term memory rates, and recall rates between commercials, leading to a 'high-ranked' commercial group and a 'low-ranked' group (P < 0.05). Neural estimation of happiness results revealed a significant difference between the high-ranked and the low-ranked commercials in happiness index (P < 0.01). The order of rankings based on happiness and attention matched well with the order of behavioral response rankings. In the elapsed-time analysis of the highest-ranked commercial, we could point to visual and auditory semantic structures of the commercial that induced increases in the happiness index. Conclusions: Our results demonstrated that the neurophysiological indices developed in this study may provide a useful tool for evaluating TV commercialsclose0

MULTI-TEMPORAL CROP SURFACE MODELS COMBINED WITH THE RGB VEGETATION INDEX FROM UAV-BASED IMAGES FOR FORAGE MONITORING IN GRASSLAND

Remote sensing of crop biomass is important in regard to precision agriculture, which aims to improve nutrient use efficiency and to develop better stress and disease management. In this study, multi-temporal crop surface models (CSMs) were generated from UAV-based dense imaging in order to derive plant height distribution and to determine forage mass. The low-cost UAV-based RGB imaging was carried out in a grassland experiment at the University of Bonn, Germany, in summer 2015. The test site comprised three consecutive growths including six different nitrogen fertilizer levels and three replicates, in sum 324 plots with a size of 1.5×1.5 m. Each growth consisted of six harvesting dates. RGB-images and biomass samples were taken at twelve dates nearly biweekly within two growths between June and September 2015. Images were taken with a DJI Phantom 2 in combination of a 2D Zenmuse gimbal and a GoPro Hero 3 (black edition). Overlapping images were captured in 13 to 16 m and overview images in approximately 60 m height at 2 frames per second. The RGB vegetation index (RGBVI) was calculated as the normalized difference of the squared green reflectance and the product of blue and red reflectance from the non-calibrated images. The post processing was done with Agisoft PhotoScan Professional (SfM-based) and Esri ArcGIS. 14 ground control points (GCPs) were located in the field, distinguished by 30 cm × 30 cm markers and measured with a RTK-GPS (HiPer Pro Topcon) with 0.01 m horizontal and vertical precision. The errors of the spatial resolution in x-, y-, z-direction were in a scale of 3-4 cm. From each survey, also one distortion corrected image was georeferenced by the same GCPs and used for the RGBVI calculation. The results have been used to analyse and evaluate the relationship between estimated plant height derived with this low-cost UAV-system and forage mass. Results indicate that the plant height seems to be a suitable indicator for forage mass. There is a robust correlation of crop height related with dry matter (R² = 0.6). The RGBVI seems not to be a suitable indicator for forage mass in grassland, although the results provided a medium correlation by combining plant height and RGBVI to dry matter (R² = 0.5)