RESUMEN
BACKGROUND AND OBJECTIVE: Preterm delivery is an important factor in the disease burden of the newborn and infants worldwide. Electrohysterography (EHG) has become a promising technique for predicting this condition, thanks to its high degree of sensitivity. Despite the technological progress made in predicting preterm labor, its use in clinical practice is still limited, one of the main barriers being the lack of tools for automatic signal processing without expert supervision, i.e. automatic screening of motion and respiratory artifacts in EHG records. Our main objective was thus to design and validate an automatic system of segmenting and screening the physiological segments of uterine origin in EHG records for robust characterization of uterine myoelectric activity, predicting preterm labor and help to promote the transferability of the EHG technique to clinical practice. METHODS: For this, we combined 300 EHG recordings from the TPEHG DS database and 69 EHG recordings from our own database (Ci2B-La Fe) of women with singleton gestations. This dataset was used to train and evaluate U-Net, U-Net++, and U-Net 3+ for semantic segmentation of the physiological and artifacted segments of EHG signals. The model's predictions were then fine-tuned by post-processing. RESULTS: U-Net 3+ outperformed the other models, achieving an area under the ROC curve of 91.4 % and an average precision of 96.4 % in detecting physiological activity. Thresholds from 0.6 to 0.8 achieved precision from 93.7 % to 97.4 % and specificity from 81.7 % to 94.5 %, detecting high-quality physiological segments while maintaining a trade-off between recall and specificity. Post-processing improved the model's adaptability by fine-tuning both the physiological and corrupted segments, ensuring accurate artifact detection while maintaining physiological segment integrity in EHG signals. CONCLUSIONS: As automatic segmentation proved to be as effective as double-blind manual segmentation in predicting preterm labor, this automatic segmentation tool fills a crucial gap in the existing preterm delivery prediction system workflow by eliminating the need for double-blind segmentation by experts and facilitates the practical clinical use of EHG. This work potentially contributes to the early detection of authentic preterm labor women and will allow clinicians to design individual patient strategies for maternal health surveillance systems and predict adverse pregnancy outcomes.
Asunto(s)
Aprendizaje Profundo , Humanos , Femenino , Embarazo , Semántica , Procesamiento de Señales Asistido por Computador , Trabajo de Parto Prematuro/diagnóstico , Adulto , Bases de Datos Factuales , Electromiografía/métodos , Recién NacidoRESUMEN
Functional gastric disorders entail chronic or recurrent symptoms, high prevalence and a significant financial burden. These disorders do not always involve structural abnormalities and since they cannot be diagnosed by routine procedures, electrogastrography (EGG) has been proposed as a diagnostic alternative. However, the method still has not been transferred to clinical practice due to the difficulty of identifying gastric activity because of the low-frequency interference caused by skin-electrode contact potential in obtaining spatiotemporal information by simple procedures. This work attempted to robustly identify the gastric slow wave (SW) main components by applying multivariate variational mode decomposition (MVMD) to the multichannel EGG. Another aim was to obtain the 2D SW vectorgastrogram VGGSW from 4 electrodes perpendicularly arranged in a T-shape and analyse its dynamic trajectory and recurrence quantification (RQA) to assess slow wave vector movement in healthy subjects. The results revealed that MVMD can reliably identify the gastric SW, with detection rates over 91% in fasting postprandial subjects and a frequency instability of less than 5.3%, statistically increasing its amplitude and frequency after ingestion. The VGGSW dynamic trajectory showed a statistically higher predominance of vertical displacement after ingestion. RQA metrics (recurrence ratio, average length, entropy, and trapping time) showed a postprandial statistical increase, suggesting that gastric SW became more intense and coordinated with a less complex VGGSW and higher periodicity. The results support the VGGSW as a simple technique that can provide relevant information on the "global" spatial pattern of gastric slow wave propagation that could help diagnose gastric pathologies.
Asunto(s)
Voluntarios Sanos , Estómago , Humanos , Estómago/fisiología , Adulto , Masculino , Femenino , Movimiento/fisiología , Análisis Multivariante , Adulto Joven , Electrodos , Procesamiento de Señales Asistido por Computador , Periodo Posprandial/fisiologíaRESUMEN
It has been demonstrated that laparoscopic procedures benefit patients in terms of recovery time, exposure to infections and trauma. Nevertheless, it increases the number of problems for the surgeons, including the frequency and duration of awkward postures for surgeons. The repetition of these movements is considered the main cause for musculoskeletal disorders in surgeons' upper limbs. The goal of this study is to evaluate the muscular activity and muscular fatigue effect produced by both, a conventional instrument and an instrument provided with the Postural Freedom (PF) feature; which consists in a ball socket articulation that allows a variable handle-to-shaft angle, on a conventional laparoscopic pistol-grip handle. Seventeen participants were evaluated during a static simulation using both instruments. Surface electromyography was used to compare the instruments in terms of muscular activity in each target position and muscular fatigue produced in the muscles trapezius, deltoids, biceps, and flexor carpi radialis. Trapezius and deltoids were the muscles most affected. Entrance and exit targets and targets facing the participants showed the higher muscular activity values. The PF prototype reduced muscular activity in all the muscles and in the majority of the target positions showing a reduction greater than 70% of the activity required by the trapezius and deltoid muscles in comparison to the conventional tool. Muscular fatigue was produced by both instruments but it presented lower frequency values with PF prototype. The results indicated that the use of conventional instruments impacts negatively on muscular activity during laparoscopic procedures, in terms of positions adopted. The PF feature in laparoscopic instrumentation reduced the muscular activity and also decreased the signals of muscular fatigue in the muscles evaluated in comparison with the conventional tool.
Asunto(s)
Electromiografía/instrumentación , Laparoscopía , Músculo Esquelético , Humanos , Fatiga Muscular , PosturaRESUMEN
Although the surface electroenterogram (EEnG) is a weak signal contaminated by strong physiological interference, such as ECG and respiration, abdominal surface recordings of the EEnG could provide a non-invasive method of studying intestinal activity. The goal of this work was to develop a modular, active, low-cost and easy-to-use sensor to obtain a direct estimation of the Laplacian of the EEnG on the abdominal surface in order to enhance the quality of bipolar surface monitoring of intestinal activity. The sensor is made up of a set of 3 concentric dry Ag/AgCl ring electrodes and a battery-powered signal-conditioning circuit. Each section is etched on a different printed circuit board (PCB) and the sections are joined to each other by surface mount technology connectors. This means the sensing electrodes can be treated independently for purposes of maintenance and replacement and the signal conditioning circuit can be re-used. A total of ten recording sessions were carried out on humans. The results show that the surface recordings of the EEnG obtained by the active sensor present significantly less ECG and respiration interference than those obtained by bipolar recordings. In addition, bioelectrical sources whose frequency fitted with the slow wave component of the EEnG (SW) were identified by parametric spectral analysis in the surface signals picked up by the active sensors.
Asunto(s)
Electromiografía/instrumentación , Intestinos/fisiología , Abdomen , Electrodos , Humanos , Masculino , Procesamiento de Señales Asistido por ComputadorRESUMEN
The electroenterogram (EEnG) is a surface recording of the myoelectrical activity of the smooth muscle layer of the small intestine. It is made up of two signals: a low-frequency component, known as the slow wave (SW), and high-frequency signals, known as spike bursts (SB). Most methods of studying bowel motility are invasive due to the difficult anatomic access of the intestinal tract. Abdominal surface EEnG recordings could be a noninvasive solution for monitoring human intestinal motility. However, surface EEnG recordings in humans present certain problems, such as the low amplitude of the signals and the influence of physiological interference such as the electrocardiogram (ECG) and respiration. In this study, a discrete estimation of the abdominal surface Laplacian potential was obtained using Hjorth's method. The objective was to analyze the enhancement given by Laplacian EEnG estimation compared to bipolar recordings. Eight recording sessions were carried out on eight healthy human volunteers in a state of fasting. First, the ECG interference content present in the bipolar signals and in the Laplacian estimation were quantified and compared. Secondly, to identify the SW component of the EEnG, respiration interference was removed by using an adaptive filter, and spectral estimation techniques were applied. The following parameters were obtained: the dominant frequency (DF) of the signals, stability of the rhythm (RS) of the DF detected and the percentage of DFs within the typical frequency range for the SW (TFSW). Results show the better ability of the Laplacian estimation to attenuate ECG interference, as compared to bipolar recordings. As regards the identification of the SW component of the EEnG, after removing respiration interference, the mean value of the DF in all abdominal surface recording channels and in their Laplacian estimation ranged from 0.12 to 0.14 Hz (7.3 to 8.4 cycles min(-1) (cpm)). Furthermore in 80% of the cases, the detected DFs were inside the typical human SW frequency range, and the ratio of frequency change in the surface bipolar and Laplacian estimation signals, in 90% of the cases, was within the frequency change accepted for human SW. Significant statistical differences were also found between the DF of all surface signals (bipolar and Laplacian estimation) and the DF of respiration. In conclusion, it was demonstrated that the discrete Laplacian potential estimation attenuated the physiological interference present in bipolar surface recordings, especially ECG. Furthermore, a slow frequency component, whose frequency, rhythm stability and amplitude fitted with the SW patterns in humans, was identified in bipolar and Laplacian estimation signals. This could be a useful non-invasive tool for monitoring intestinal activity by abdominal surface recordings.
Asunto(s)
Algoritmos , Diagnóstico por Computador/métodos , Electromiografía/métodos , Motilidad Gastrointestinal/fisiología , Intestino Delgado/fisiología , Modelos Biológicos , Músculo Liso/fisiología , Abdomen/fisiología , Potenciales de Acción/fisiología , Adulto , Simulación por Computador , Femenino , Humanos , MasculinoRESUMEN
An external electroenterogram (EEnG) is the recording of the small bowel myoelectrical signal using contact electrodes placed on the abdominal surface. It is a weak signal affected by possible movements and by the interferences of respiration and, principally, of the cardiac signal. In this paper an adaptive filtering technique was proposed to identify and subsequently cancel ECG interference on canine surface EEnGs by means of a signal averaging process time-locked with the R-wave. Twelve recording sessions were carried out on six conscious dogs in the fasting state. The adaptive filtering technique used increases the signal-to-interference ratio of the raw surface EEnG from 16.7 +/- 6.5 dB up to 31.9 +/- 4.0 dB. In addition to removing ECG interference, this technique has been proven to respect intestinal SB activity, i.e. the EEnG component associated with bowel contractions, despite the fact that they overlap in the frequency domain. In this way, more robust non-invasive intestinal motility indicators can be obtained with correlation coefficients of 0.68 +/- 0.09 with internal intestinal activity. The method proposed here may also be applied to other biological recordings affected by cardiac interference and could be a very helpful tool for future applications of non-invasive recordings of gastrointestinal signals.
Asunto(s)
Algoritmos , Electrocardiografía/métodos , Electromiografía/métodos , Motilidad Gastrointestinal/fisiología , Intestino Delgado/fisiología , Músculo Liso/fisiología , Procesamiento de Señales Asistido por Computador , Animales , Artefactos , PerrosRESUMEN
Electroenterogram (EEnG), which is the myoelectrical activity of the small bowel, can be non-invasively recorded from abdominal external surface. However, this bioelectrical signal is weak and noisy compared to internal recording from bowel serous layers, because of bioelectric transmission through abdominal layers. Furthermore, it is contaminated with several interferences from other biological activities as cardiac muscle (ECG), skeletal muscles (EMG), or respiration movements. The goal of present work is to study abdominal recording of EEnG and its signal-to-noise ratio by means of the coherence estimation technique. External and internal recordings were obtained simultaneously in 12 sessions, which went on more than two hours in six beagle dogs. Coherence function, based on periodograms, is estimated in periods of 15 minutes. Thus, SNR is calculated from coherence estimation for each recording session. Results show that SNR reaches a maximum value of 8.8 dB for 0.31 Hz, which corresponds to fundamental frequency of the EEnG slow wave. However, SNR is weak at frequencies upper 2 Hz, which corresponds to rapid action potentials (spike bursts) of the EEnG. In conclusion, slow wave can be clearly identified in abdominal recording; however spike bursts are contaminated by noise, attenuation and biological interferences.
Asunto(s)
Algoritmos , Diagnóstico por Computador/métodos , Electromiografía/métodos , Motilidad Gastrointestinal/fisiología , Intestino Delgado/fisiología , Músculo Liso/fisiología , Animales , Perros , Reproducibilidad de los Resultados , Sensibilidad y EspecificidadRESUMEN
The first aim of this study was to obtain the discrete Laplacian of the myoelectric small intestine signal (electroenterogram, EEnG) from bipolar recordings on the abdominal surface in humans. In addition, the objective was to identify the slow wave (SW) component of the EEnG in the estimated Laplacian, as well as to compare this signal with the bipolar surface recordings. It was carried out 8 recording sessions in 6 healthy volunteers. The discrete Laplacian of the surface potential was performed using Hjorth's Laplacian estimation method. In order to identify the SW component of the EEnG, an adaptive filter, which removes breath interference from abdominal surface recordings, was designed. After that, periodograms and their dominant frequency were obtained. The results show that this frequency, in all surface recording channels and in their corresponding Laplacian, ranges from 0.12 to 0.16 Hz (7.3 to 9.8 cycles per minute) inside of the SW frequency range, whereas the frequencies of the respiration ranges from 0.21 to 0.31 Hz (12.9-18.4 cpm). Furthermore abdominal surface Laplacian potential contains averaged SW, information unless any bipolar surface channel do not record properly this signal. Consequently EEnG surface recordings can become a low cost technique to study bowel motility non-invasively.
Asunto(s)
Electromiografía/instrumentación , Monitoreo Ambulatorio/instrumentación , Abdomen/patología , Adulto , Simulación por Computador , Diagnóstico por Computador , Conductividad Eléctrica , Electromiografía/métodos , Diseño de Equipo , Femenino , Motilidad Gastrointestinal , Humanos , Intestino Delgado/patología , Masculino , Persona de Mediana Edad , Monitoreo Ambulatorio/métodos , Contracción Muscular , Procesamiento de Señales Asistido por ComputadorRESUMEN
Intestinal myoelectrical activity (IMA), which determines bowel mechanical activity, is the result of two components: a low-frequency component [slow wave (SW)] that is always present, and a high-frequency component [spike bursts (SB)] which is associated with bowel contractions. Despite of the diagnostic significance of internal recordings of IMA, clinical application of this technique is limited due to its invasiveness. Thus, surface recording of IMA which is also called electroenterogram (EEnG) could be a solution for noninvasive monitoring of intestinal motility. The aim of our work was to identify slow wave and spike burst activity on surface EEnG in order to quantify bowel motor activity. For this purpose, we conducted simultaneous recordings of IMA in bowel serosa and on abdominal surface of five Beagle dogs in fast state. Surface EEnG was studied in spectral domain and frequency bands for slow wave and spike burst energy were determined. Maximum signal-to-interference ratio (7.5 dB +/- 36%) on SB frequency band was obtained when reducing upper frequency limit of signal analysis. Energy of external EEnG in reduced SB frequency band (2-7.9 Hz) presented a high correlation (0.71 +/- 7%) with internal intensity of contractions. Our results suggest that energy of SB can be quantified on external EEnG which could provide a noninvasive method for monitoring intestinal mechanical activity.