Feasibility of transabdominal electrohysterography for analysis of uterine activity in nonpregnant women

Purpose: Uterine activity plays a key role in reproduction, and altered patterns of uterine contractility have been associated with important physiopathological conditions, such as subfertility, dysmenorrhea, and endometriosis. However, there is currently no method to objectively quantify uterine contractility outside pregnancy without interfering with the spontaneous contraction pattern. Transabdominal electrohysterography has great potential as a clinical tool to characterize noninvasively uterine activity, but results of this technique in nonpregnant women are poorly documented. The purpose of this study is to investigate the feasibility of transabdominal electrohysterography in nonpregnant women. Methods: Longitudinal measurements were performed on 22 healthy women in 4 representative phases of the menstrual cycle. Twelve electrohysterogram-based indicators previously validated in pregnancy have been estimated and compared in the 4 phases of the cycle. Using the Tukey honest significance test, significant differences were defined for P values below .05. Results: Half of the selected electrohysterogram-based indicators showed significant differences between menses and at least 1 of the other 3 phases, that is the luteal phase. Conclusion: Our results suggest transabdominal electrohysterography to be feasible for analysis of uterine activity in nonpregnant women. Due to the lack of a golden standard, this feasibility study is indirectly validated based on physiological observations. However, these promising results motivate further research aiming at evaluating electrohysterography as a method to improve understanding and management of dysfunctions (possibly) related to altered uterine contractility, such as infertility, endometriosis, and dysmenorrhea

Effect of Delivery Method on Nursing Students\u27 Math Competency and Learning Perceptions

The delivery method of a math course may affect the math scores of nursing students, which relates to rates of medication errors that could be fatal. The purpose of this study was to discover the relative effectiveness of a delivery method of a math course. Benner\u27s novice-to-expert theory guided the study. A sequential explanatory, mixed-methods, nonexperimental pre-/posttest alternative treatment design was used. Phase 1 answered which delivery methods-online self-directed, face-to-face, or a mix of online self-directed with instructor lead-were associated with the best Medication Administration Competency exam results. Phase 2 included students\u27 assessment of each learning method. The sample size was 148 students who were admitted to 1 nursing school between 2011 and 2013. The data were collected from 4 sources: (a) archival standardized entrance exam math scores, (b) archival standardized exit exam math scores, (c) a qualitative survey regarding student perceptions of the delivery method, and (d) a qualitative section of the same survey with math questions. The ANCOVA analysis showed no statistically significant difference in the delivery method used. Students with lower pretest exam scores took the posttest exam more times and also had lower posttest grades. The content analysis showed that students from all 3 groups did not see an advantage in the delivery method, but in certain teaching strategies that support learning. Therefore, the nursing school should continue to allow students to select their preferred delivery method, or offer fewer methods as they were equivalent. Positive change could come from using teaching strategies that students valued, improving their ability to provide correct dosages and increasing patient safety in the healthcare environment

Vectorial analysis of the electrohysterogram for prediction of preterm delivery: a preliminary study

Electrophysiological measurement of uterine contractions, referred to as electrohysterogram (EHG), is potentially more informative than methods currently used during pregnancy for timely recognition of complications such as preterm labor. Unfortunately, EHG measurement and interpretation remain challenging. Recently, some attention has been dedicated to the analysis of the EHG propagation, which is hypothetically predictive of the delivery time. This hypothesis, though physiologically reasonable, has not been investigated yet. A dedicated maximum likelihood (ML) method has been proposed and validated for identifying the conduction velocity vector of single EHG spikes. This validated ML method is here employed for comparing the conduction velocity vector in two groups of pregnant women with uterine contractions that were prospectively classified as productive or unproductive contractions. The estimated conduction velocity vector showed significant differences in the two groups. The spikes extracted from those contractions eventually classified as unproductive showed a significantly lower conduction velocity amplitude (CV = 4.89 ± 1.19 cm.s 1 vs CV 8.63 ± 2.92 cm.s 1) and a higher occurrence of upward propagation relative to productive contractions. These results suggest that productive and unproductive uterine contractions are associated to significantly different properties of the conduction velocity vector, which is likely to be proven fundamental in predicting preterm delivery

Electromyographic assessment of muscle fatigue during isometric vibration training at varying frequencies

Resistance exercise is essential to improve or maintain muscle performance. Vibration training has been suggested as an alternative option for muscle conditioning, aiming especially at improving muscle strength and power. Several studies link the effects of vibration training to enhanced neuromuscular stimulation, measured by electromyography (EMG) and typically ascribed to involuntary reflex mechanisms. However, the underlying mechanisms are still unclear, limiting the use of vibration training. This paper proposes additional methods to analyze the mechanisms involved in vibration training. A dedicated measurement setup was realized to relate vibration parameters to muscle fatigue in the biceps brachii. Fatigue is estimated by EMG mean frequency and conduction velocity assessments as well as by maximum voluntary contraction (MVC) force measurements. A modified maximum likelihood algorithm is proposed for the conduction velocity estimation based on high-density EMG recording. Five volunteers performed four isometric contractions of 50 s at 80% MVC with no vibration (control) and with superimposed vibration at 20, 30, and 40 Hz. Fatigue was estimated from the decay of force, EMG mean frequency, and EMG conduction velocity. 30-Hz vibrations represented the most fatiguing stimulus. Our preliminary results also show a better correlation between force and conduction velocity decay than between force and mean frequency decay, indicating the former as a better EMG indicator of fatigue. The proposed methods provide important advancements for the analysis of vibration exercise and guidance towards the definition of optimal training protocols

Analysis of vibration exercise at varying frequencies by different fatigue estimators

Vibration exercise (VE) has been suggested to improve muscle strength and power performance, due to enhanced neuromuscular demand. However, understanding of the most appropriate VE protocols is lacking, limiting the optimal use of VE in rehabilitation programs. In this study, the fatiguing effect of vibration at different frequencies was investigated by employing a force-modulation VE system. Twenty volunteers performed 12-s isometric contractions of the biceps brachii with a load consisting of a baseline force of 80% of their maximum voluntary contraction (MVC) and a superimposed sinusoidal force at 0 (control condition with no vibration), 20, 30, and 40 Hz. Mechanical fatigue was estimated by assessment of MVC decay after each task while myoelectric fatigue was estimated by analysis of multichannel electromyography (EMG) signals recorded during VE. EMG conduction velocity, spectral compression, power, and fractal dimension were estimated as indicators of myoelectric fatigue. Our results suggest vibration, in particular at 30 Hz, to produce a larger degree of fatigue as compared to control condition. These results motivate further research aiming at introducing VE in rehabilitation programs with improved training protocols

Towards real-time estimation of muscle-fiber conduction velocity using delay-locked loop

Decrease in muscle-fiber conduction velocity (MFCV) during sustained contraction has been widely accepted as myoelectric manifestation of muscle fatigue. Several methods have been proposed in the literature for MFCV estimation by analysing surface electromyography (EMG), e.g., cross-correlation (CC) function and maximum likelihood (ML). However, for all the available methods, windowing of the EMG signal and computationally demanding calculations are required, limiting the possibility to continuously monitor muscle fatigue in real time. In the present study, an adaptive scheme is proposed that permits real-time estimation of MFCV. The proposed scheme is based on a delay-locked loop (DLL). A second-order loop is adopted to track the delay variation over time. An error filter is employed to approximate a ML estimation in case of colored noise. Furthermore, the DLL system is extended for multichannel CV estimation. The performance of the proposed method is evaluated by both dedicated simulations and real EMG signals. Our results show the accuracy of the proposed method to be comparable to that of the ML method for much lower (1/40) computational complexity, especially suited for real-time MFCV measurements. Use of this method can enable new studies on myoelectric fatigue, possibly leading to new insight on the underlying physiological processes

Automatic optimization of multichannel electrode configurations for robust fetal heart rate detection by Blind Source Separation

Objective. Fetal heart rate (fHR) evaluation is fundamental to guarantee timely medical intervention in case of pregnancy complications. Due to the limitations of traditional cardiotocography, multichannel electrophysiological recording was proposed as a viable alternative, which requires Blind Source Separation (BSS) techniques. Yet effective and reliable separation of the fetal ECG remains challenging due to multiple noise sources and the effects of varying fetal position. In this work, we demonstrate that the adopted electrode configuration plays a key role in the effectiveness of BSS and propose guidelines for optimal electrode positioning. Moreover, a model is proposed to automatically predict the most suited configuration for accurate BSS-based fHR estimation with a minimal number of leads, to facilitate practical implementation. Methods. We compared fHR estimation accuracy with different electrode configurations on in-silico data, identifying the optimal configuration for a recent BSS method. Based on features extracted from raw signals, we proposed a support vector regression model to automatically identify the best electrode configuration in terms of fHR estimation accuracy and to dynamically adjust it to varying fetal presentation. Evaluation was performed on real and synthetic data. Results. Guidelines for the optimal electrode configuration are proposed by using 4 leads. Prediction of configuration quality shows 80.9% accuracy; the optimal configuration is recognized in 92.2% of the subjects. Conclusion. The proposed method successfully predicts the quality of the configurations, demonstrating the impact of the electrode configuration on the BSS performance. Significance. The method holds potential for long-term fetal monitoring, by dynamically choosing the optimal configuration