Study Design. Cross-sectional design. Objective. The aim of this study was to investigate the correlation between intramuscular EMG (iEMG) and surface EMG (sEMG) from lumbar multifidus and erector spinae muscles during (submaximal) voluntary contraction tests in healthy participants. Summary of Background Data. Low back muscle function is a key component in the stability of the lumbar spine in which an important role is attributed to the lumbar multifidus (LM). Impairments in this stabilization system are held responsible for (chronic) low back pain. LM function can be measured by iEMG and sEMG; however, in earlier studies, results from iEMG and sEMG were inconsistent. Methods. Fifteen healthy adults were included. The intervention consisted of five clinical tests: resting, submaximal contraction tests of the lower back, abdominal contraction, and a biofeedback test in which LM and erector spinae (ES) activities were compared by iEMG and sEMG. Correlations were calculated with regard to original signal, co-contraction ratio, and cross-talk ratio. Correlation coefficients for each combination of iEMG and sEMG signals were calculated, to identify original signal (i.e., activity of only the targeted muscle) and possible cross-talk. Correlations >0.75 were considered as good concurrent validity. Results. The original signals of LM showed fair to high correlation coefficients (r: 0.3-0.8). Co-contraction of LM and ES was observed during all tests, but iEMG shows more variation in the correlations (r: 0.1-0.8) compared to sEMG (r: 0.3-0.8). Significant cross-talk was observed in all tests, particularly during the biofeedback test of iEMG(ES) versus sEMG(LM) and iEMG(LM) versus sEMG(ES) (r = 0.8). Conclusion. Surface EMG of ES and LM are no adequate representation of LM and ES activity measured by iEMG because of moderate/high cross-talk and co-contractions. Clinical tests that aim to assess LM activity do not represent isolated LM activity. This should be taken into account in future clinical studies.

The aim of this pilot study was to investigate the effects of an intervention consisting of mental coaching combined with either electro encephalogram (EEG) alpha power feedback or heart rate variability (HRV) feedback on HRV, EEG outcomes and self-reported factors related to stress, performance, recovery and sleep quality in elite athletes. A prospective pilot study was performed with two distinct cohorts. Soccer players were provided with four sessions of mental coaching combined with daily HRV biofeedback (Group A); track and field athletes were provided with four sessions of mental coaching in combination with daily neurofeedback (Group B). Measurements were performed at baseline, post intervention and at 5 weeks follow-up. Objective measures: EEG and ECG. Subjective measures: Numeric Rating Scale for performance, Pittsburgh Sleep Quality Index, Rest and Stress Questionnaire and Sports Improvement-60. Group characteristics were too distinct to compare the interventions. Linear mixed models were used to analyze differences within groups over time. In Group A, significant changes over time were present in alpha power at 5 of 7 EEG locations (p < 0.01–0.03). LF/HF ratio significantly increased (p = 0.02) and the concentration (p = 0.02) and emotional scale (p = 0.03) of the SIM-60 increased significantly (p = 0.04). In Group B, the HRV low frequency power and recovery scale of the REST-Q significantly increased (p = 0.02 and <0.01 resp.). Other measures remained stable or improved non-significantly. A mental coaching program combined with either HRV or EEG alpha power feedback may increase HRV and alpha power and may lead to better performance-related outcomes and stress reduction. Further research is needed to elucidate the effects of either type of feedback and to compare effects with a control group.

Motion artifacts (MA) have long been a problem in biopotential measurements. Adaptive filtering is widely used for optimal noise removal in many biomedical applications. However, the existing adaptive filtering methods involve the use of additional sensors, limiting the applicability of adaptive filtering for MA reduction. In the present study, a novel adaptive filtering method without need for additional sensors is proposed. In biopotential measurements, movement of the electrodes and their leads may cause variations not only in the skin and half-cell potential (motion artifacts), but also in the electrode-skin impedance. Such impedance variations may also cause power-line interference modulation (PLIM), resulting in additional spectral components around the power-line interference (PLI) in the frequency domain. Demodulation of the PLI may reflect the movement-induced electrode-skin impedance variation, and can therefore represent a reference signal for the adaptive filter. Preliminary validation on ECG measurements with seven volunteers showed a high correlation coefficient (R  =  0.97) between MA and PLIM, and excellent MA removal by the proposed adaptive filter, possibly leading to improved analysis of biopotential signals.

The electrohysterogram (EHG) is a promising means of monitoring pregnancy and of detecting a risk of preterm labor. To improve our understanding of the EHG as well as its relationship with the physiologic phenomena involved in uterine contractility, we plan to model these phenomena in terms of generation and propagation of uterine electrical activity. This activity can be realistically modeled by representing the principal ionic dynamics at the cell level, the propagation of electrical activity at the tissue level and then the way it is reflected on the skin surface through the intervening tissue. We present in this paper the different steps leading to the development and validation of a biophysics based multiscale model of the EHG, going from the cell to the electrical signal measured on the abdomen.

A Body Area Network (BAN) is a body worn system which provides the user with a set of mobile services. A BAN incorporates a set of devices (eg. mp3 player, video camera, speakers, microphone, head-up display, positioning device, sensors, actuators). A BAN service platform for mobile healthcare and several health BANs targetting different clinical applications have been developed at the University of Twente. Each specialization of the BAN is equipped with a certain set of devices and associated application components, as appropriate to the clinical application. Different kinds of clinical data may be captured, transmitted and displayed, including text, numeric values, images and multiple biosignal streams. Timely processing and transmission of such multimedia clinical data in a distributed mobile environment requires smart strategies. Here we present one approach to designing smart distributed applications to deal with multimedia BAN data; namely the context awareness approach developed in the FREEBAND AWARENESS project.

A challenge of current innovation in healthcare processes is to improve the time to treatment. This paper addresses the benefits of telematic services and mobile & wireless devices such as vital sign sensors and head mounted cameras for healthcare processes. It explores the telematic requirements for a distributed healthcare environment of body area networks of the mobile devices which are connected by wireless (public) networks (e.g. GPRS and UMTS) to healthcare centres. Our main contribution is the development of enterprise models, which are expressed in terms of the unified modelling language, for the purpose of identification and justification of the telematic system requirements. The developed enterprise models separate organizational modelling concerns such as the separation of medical roles from the agents acting in these roles. This separation enables roles to be dispatched virtually to a point of care without transporting along with all the agents, but it requires support of a telematic system to bridge the distance gap. We validate the proposed models against a trauma team scenario and consequently obtain the telematic system requirements which enable improved time to treatment for emergency services.