Medical Information Representation Framework for Mobile Healthcare

In mobile healthcare, medical information are often expressed in different formats due to the local policies and regulations and the heterogeneity of the applications, systems, and the adopted Information and communication technology. This chapter describes a framework which enables medical information, in particular clinical vital signs and professional annotations, be processed, exchanged, stored and managed modularly and flexibly in a mobile, distributed and heterogeneous environment despite the diversity of the formats used to represent the information. To deal with medical information represented in multiple formats the authors adopt techniques and constructs similar to the ones used on the Internet, in particular, the authors are inspired by the constructs used in multi-media e-mail and audio-visual data streaming standards. They additionally make a distinction of the syntax for data transfer and store from the syntax for expressing medical domain concepts. In this way, they separate the concerns of what to process, exchange and store from how the information can be encoded or transcoded for transfer over the internet. The authors use an object oriented information model to express the domain concepts and their relations while briefly illustrate how framework tools can be used to encode vital sign data for exchange and store in a distributed and heterogeneous environment

The effect of briefing videos in medical simulation-based education:a randomised controlled trial

The aim of this study is to compare the effects of an affective briefing video with a textual briefing on cognitive appraisal (threat or challenge response). It is hypothesized that briefing videos will cause a threat response, which is associated with increase in cortisol and memory consolidation

Trapezius muscle EMG as predictor of mental stress

Stress is a growing problem in society and can cause musculoskeletal complaints. It would be useful to measure stress for prevention of stress-related health problems. An experiment is described in which EMG signals of the upper trapezius muscle were measured with a wireless system during three different stressful conditions: a calculation task (the Norinder test), a logical puzzle task and a memory task. The latter two tests were newly designed and aimed at creating circumstances that are similar to work stress. Amplitudes of the EMG signals were significantly higher during stress compared to rest (+2.6% of reference contraction level) and relative time with EMG gaps was lower during stress (−14.3% of time). Also, mean and median frequencies were significantly lower during stress than during rest (−8.6 and −8.8 Hz, respectively). EMG amplitude increased not only from rest to stress conditions, but also during stressful conditions and decreased during relaxation periods. EMG features correlated with subjectively indicated stress levels (correlations of 0.32 with RMS and −0.32 with relative gaptime). The results indicate that EMG is a useful parameter to detect stress. Together with other physiological sensors, EMG sensors can be included in a wireless system for ambulatory monitoring of stress levels

Towards continuous mental stress level estimation from physiological signals

It is well known that chronic mental stress can cause health problems. Early stress detection can help prevent these problems. We propose and compare two approaches to estimate stress level from physiology. We have measured physiological signals in three different artificial stressful conditions involving problem solving under time pressure and memorizing exercises. Rest periods were included in the protocol to avoid crossover effects over the stress conditions. The recorded signals were: electrocardiogram (ECG), respiration, skin conductance and electromyogram (EMG) of the upper trapezius muscles. About 40 minutes of data were recorded from 30 healthy subjects. Subjective stress levels were measured using questionnaires. We followed a feature selection process to choose 5 physiological features to be used in the analysis. A 2-minute sliding window was used to extract the features by 1-second steps. The feature values were normalized to eliminate baseline and reactivity differences among subjects. The dataset was divided five times randomly in an 80% training set and a 20% test set. The different stress estimation approaches were evaluated and compared using three metrics. First, the classification accuracy in distinguishing between stress and rest conditions was calculated. Second and third, the root mean square error (RMSE) and the correlation were calculated against the subjective stress levels that the subjects indicated during the protocol. Logistic regression and linear regression were applied to obtain an estimation of the stress level. The logistic regression model provided a probability between 0 and 1of a data point belonging to a stress condition. Three concepts were tested to extend the outcome towards a continuous stress level estimation. In the first method, the probability values were interpreted directly as stress le-vels ranging from 0 to 1. In the second method, the relative amount of time that the measure-ments were classified as stress condition in the past 2 minutes was calculated. In the third me-thod, the average of the probability values of the past 2-minutes was calculated. Linear regression was performed against subjective stress levels measured by questionnaires. For classification we chose the optimal threshold that resulted in the highest classification accuracy to classify the es-timated stress levels into the known rest and stress conditions. Results are shown in Table 1. The values in the table correspond to the average numbers over the five different training and test sets. Examples of continuous stress level estimations using me-thods 1 and 4 are shown in Figure 1. Method 4 (linear regression) resulted in the highest classification rate and the lowest RMSE. Me-thod 1 showed the highest correlation with the subjective stress levels. Overall, we conclude that both linear and logistic regression are possible candidates to provide a continuous estimation of stress level. Logistic regression has the advantage that it does not need a subjective reference like questionnaires. The approach of interpreting the probability of the logistic regression model as an estimate of the stress level has, to our knowledge, not been reported before. Our results suggest that it may provide a good estimate, but this needs to be validated in further investigations

Towards Mental Stress Detection Using Wearable Physiological Sensors

Early mental stress detection can prevent many stress related health problems. This study aimed at using a wearable sensor system to measure physiological signals and detect mental stress. Three different stress conditions were presented to a healthy subject group. During the procedure, ECG, respiration, skin conductance, and EMG of the trapezius muscles were recorded. In total, 19 physiological features were calculated from these signals. After normalization of the feature values and analysis of correlations among these features, a subset of 9 features was selected for further analysis. Principal component analysis reduced these 9 features to 7 principal components (PCs). Using these PCs and different classifiers, a consistent classification accuracy between stress and non stress conditions of almost 80% was found. This suggests that a promising feature subset was found for future development of a personalized stress monitor

Personalized Coaching Systems to support healthy behavior in people with chronic conditions

Chronic conditions cannot be cured but daily behavior has a major effect on the severity of secondary problems and quality of life. Changing behavior however requires intensive support in daily life, which is not feasible with a human coach. A new coaching approach – so-called Personal Coaching Systems (PCSs) – use on-body sensing, combined with smart reasoning and context-aware feedback to support users in developing and maintaining a healthier behavior. Three different PCSs will be used to illustrate the different aspects of this approach: (1) Treatment of neck/shoulder pain. EMG patterns of the Trapezius muscles are used to estimate their level of relaxation. Personal vibrotactile feedback is given, to create awareness and enable learning when muscles are insufficiently relaxed. (2) Promoting a healthy activity pattern. Using a 3D accelerometer to measure activity and a smartphone to provide feedback. Timing and content of the feedback are adapted real-time, using machine-learning techniques, to optimize adherence. (3) Management of stress during daily living. The level of stress is quantified using a personal model involving a combination of different sensor signals (EMG, ECG, skin conductance, respiration). Results show that Personal Coaching Systems are feasible and a promising and challenging way forward to coach people with chronic conditions

Twelve years of circulatory extracorporeal life support at the University Medical Centre Utrecht

INTRODUCTION: Circulatory extracorporeal life support (ECLS) has been performed at the University Medical Centre Utrecht for 12 years. During this time, case mix, indications, ECLS set-ups and outcomes seem to have substantially changed. We set out to describe these characteristics and their evolution over time. METHODS: All patients receiving circulatory ECLS between 2007 and 2018 were retrospectively identified and divided into six groups according to a 2-year period of time corresponding to the date of ECLS initiation. General characteristics plus data pertaining to comorbidities, indications and technical details of ECLS commencement as well as in-hospital, 30-day, 1‑year and overall mortality were collected. Temporal trends in these characteristics were examined. RESULTS: A total of 347 circulatory ECLS runs were performed in 289 patients. The number of patients and ECLS runs increased from 8 till a maximum of 40 runs a year. The distribution of circulatory ECLS indications shifted from predominantly postcardiotomy to a wider set of indications. The proportion of peripheral insertions with or without application of left ventricular unloading techniques substantially increased, while in-hospital, 30-day, 1‑year and overall mortality decreased over time. CONCLUSION: Circulatory ECLS was increasingly applied at the University Medical Centre Utrecht. Over time, indications as well as treatment goals broadened, and cannulation techniques shifted from central to mainly peripheral approaches. Meanwhile, weaning success increased and mortality rates diminished