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Analysis and Interpretation of Uterine Contraction Signals Using Artificial Intelligence
Published in Saravanan Krishnan, Ramesh Kesavan, B. Surendiran, G. S. Mahalakshmi, Handbook of Artificial Intelligence in Biomedical Engineering, 2021
P. Mahalakshmi, S. Suja Priyadharsini
In this work, the performance of classifiers such as the SVM, ELM, KNN, RF, ANN and RBFNN is evaluated individually, in terms of accuracy, to classify the EHG signals into true and false labor pains. EHG records from the Term–Preterm Electrohysterogram Database of PhysioNet were used for evaluation. It comprises 300 records of pregnant women, of which 262 are full-term pregnancies and 38 are premature births. Here, 162 records were taken before the 26th week of pregnancy and 138 records after, collected from 1997 until 2005 at the Department of Obstetrics and Gynaecology, Ljubljana University Medical Centre Slovenia. The records were acquired from the general population, in addition to patients admitted to the hospital with a diagnosis of anticipated preterm labor One record per pregnancy was recorded with a sampling frequency (Fs) of 20 Hz.
Simulation-Based Training for Ultrasound Practice
Published in Christopher M. Hayre, Dave J. Muller, Marcia J. Scherer, Virtual Reality in Health and Rehabilitation, 2020
Ensuring patient safety in ultrasound practice is a superior aim to training for skills acquisition, as some sensitive procedures cannot be undertaken during for long scans, and passive observations are thus sometimes performed with such scans rather than hands-on training. Even with the safe nature of ultrasound beams, as a non-ionising radiation, employing the ALARA principle is still crucial to ensure patient safety. ALARA stands for ‘As Low As Reasonably Achievable’, and refers to the minimisation of acoustic output with shortest scanning time while achieving optimum diagnosis (Joy et al., 2006). The international ultrasound societies emphasise the importance of occupying safe ultrasound practice in clinical fields. For example, both the American Institution for Ultrasound in Medicine (AIUM) and the British Medical Ultrasound Society (BMUS) provide the highest evidence-based guidelines that recommend ultrasound users to ascertain the endorsed measures of exposure time and thermal/mechanical index for sensitive scans such as obstetric, neonatal, trans-cranial and vascular ultrasound (BMUS, 2009; AIUM, 2016; SCoR/BMUS, 2019). Moreover, The International Society of Ultrasound in Obstetrics and Gynaecology (ISUOG) recommends that practitioners follow the ALARA principle in early pregnancy ultrasound and do not include pulsed Doppler ultrasound in routine scanning during the first trimester. If used at all, the thermal index (TI) should be ≤1.0 and the exposure time should be minimised as far as possible with no longer than 5–10 minutes' exposure (Salvesen et al., 2011, 2016).
Implementing the Assessment of Surgical Skills and Non-Technical Behaviours in the Operating Room
Published in Rhona Flin, Lucy Mitchell, Safer Surgery, 2009
Joy Marriott, Helen Purdie, Jim Crossley, Jonathan Beard
Preliminary validation studies on PBA have been performed by Rowley and Pitts (see Chapter 3). Our study seeks to further examine the validity and evaluate the reliability of the PBA tool. OSATS has demonstrated inter-rater reliability and construct validity in assessing general surgeons performing common operations (Winckel et al. 1994). However, there have not been validity and reliability studies performed for the ten OSATS of obstetrics and gynaecology procedures used by the RCOG.
Performance evaluation of linear and nonlinear filters for despeckling B mode foetal heart ultrasound images
Published in The Imaging Science Journal, 2023
N. Sriraam, V. Punya Prabha, T. V. Sushma, S. Suresh
Ultrasound images are generated by using sound waves of frequency above the human audible range of 20 KHz. Medical ultrasound uses signals in the range of 1–20 MHz with obstetrics and gynaecology applications using a frequency range of 2–5 MHz. The incident ultrasound waves from the transducer propagate through the underlying medium, and based on acoustic impedance of the underlying structures, different amounts of sound waves are reflected [4,5]. The interference of the reflected acoustic echoes is used to produce an image pattern based on the intensity of the reflections. The random phase and the amplitude of the reflected acoustic signal create a noise pattern referred to as the speckle noise [6], which is granular in nature. Many studies have been conducted on the properties and statistical distribution of speckle [5,7,8]. Speckle noise tends to reduce the visual quality of the image making delineation of anatomical structures difficult, resulting in false interpretations and analysis of medical images. It reduces the diagnostic value of the images.
Study and implementation of automated system for detection of PCOS from ultrasound scan images using artificial intelligence
Published in The Imaging Science Journal, 2023
M. Sumathi, P. Chitra, S. Sheela, C. Ishwarya
Research has also revealed the still existing significant gap between the existing evidence and its use to earlier diagnosis and evidence-based therapy [9,10]. Regarding the diagnosis and treatment of PCOS, there are still information gaps in several medical specialties (such as obstetrics and gynaecology (OBGYN), medicine, paediatrics, and dermatology), and women with PCOS report considerable delays in the diagnosis [11]. Atherosclerosis and cardiovascular disease (CV) are linked to metabolic syndrome (MBS), a prevalent ailment associated with visceral obesity and insulin resistance (IR) [12,13]. MBS is highly prevalent, affecting 23.7% of Americans over the age of 20 [14]. Roy, D.G et al., investigated how several life evaluation elements affected people's quality of life (QoL). Together with the use of AI and statistical techniques, the role of data analytics in the monitoring and management of human quality of life has also been considered. It has aided in locating the variables that can boost human quality of life on the whole [15].
Population characteristics associated with adherence to prenatal group-based exercise programs
Published in Journal of Sports Sciences, 2022
Taniya S. Nagpal, Miguel Sánchez-Polán, Danilo F. da Silva, Sara C.S. Souza, Mireia Pelaez, María Perales, Yaiza Cordero, Marina Vargas-Terrones, Kristi B. Adamo, Ruben Barakat
The group prenatal exercise classes were led by a certified exercise physiologist and involved a warm up, aerobic exercise, muscular strength and flexibility, coordination and balance work, and pelvic floor training meeting the standards of the Society of Obstetricians and Gynaecologists of Canada/Canadian Society for Exercise Physiology, and American College of Obstetrics and Gynaecology guidelines for exercise during pregnancy (American College of Obstetricians and Gynecologists, 2015; Davies et al., 2003). Exercise programme frequency was between 2 and 3 sessions/week, 45–60 minutes/session, with moderate intensity exercises. Intervention programmes were initiated at <20 weeks gestation and concluded at late pregnancy (between 36 and 40 weeks gestation). The total intervention duration was approximately 6 months depending on the anticipated delivery date and gestational age when the programme commenced.