Comparative finite element analysis of the first thoracic vertebra in artiodactyls.

Artiodactyls exhibit a striking diversity of the cervical vertebral column in terms of length and overall mobility. Using finite element analysis, this study explores the morphology at the cervico-thoracic boundary and its performance under loads in artiodactyls with different habitual neck postures and body sizes. The first thoracic vertebra of 36 species was loaded with (i) a compressive load on the vertebral body to model the weight of the head and neck exerted onto the trunk; and (ii) a tensile load at the spinous process to model the pull via the nuchal ligament. Additional focus was laid on the peculiar shape of the first thoracic vertebra in giraffes. We hypothesized that a habitually upright neck posture should be reflected in the greater ability to withstand compressive loads compared to tensile loads, whereas for species with a habitually suspended posture it should be the opposite. In comparison to species with a suspended posture, species with an upright posture exhibited lower stress (except Giraffidae). For compressive loads in larger species, stress surprisingly increased. Tensile loads in larger species resulted in decreased stress only in species with an intermediate or suspensory neck posture. High stress under tensile loads was mainly reflecting the relative length of the spinous process, while high stress under compressive loads was common in more "bell"-shaped vertebral bodies. The data supports a stability-mobility trade-off at the cervico-thoracic transition in giraffes. Performance under load at the cervico-thoracic boundary is indicative of habitual neck posture and is influenced by body size.

Effects of auditory noise intensity and color on the dynamics of upright stance.

Previous work assessing the effect of additive noise on the postural control system has found a positive effect of additive white noise on postural dynamics. This study covers two separate experiments that were run sequentially to better understand how the structure of the additive noise signal affects postural dynamics, while also furthering our knowledge of how the intensity of auditory stimulation of noise may elicit this phenomenon. Across the two experiments, we introduced three auditory noise stimulations of varying structure (white, pink, and brown noise). Experiment 1 presented the stimuli at 35 dB while Experiment 2 was presented at 75 dB. Our findings demonstrate a decrease in variability of the postural control system regardless of the structure of the noise signal presented, but only for high intensity auditory stimulation.

The Impact of Dual-Tasks and Disease Severity on Posture, Gait, and Functional Mobility among People Living with Dementia in Residential Care Facilities: A Pilot Study.

Gait speed and timed-up-and-go (TUG) predict cognitive decline, falls, and mortality. Dual-tasks may be useful in cognitive screening among people living with dementia (PWD), but more evidence is needed. This cross-sectional study aimed to compare single- and dual-task performance and determine the influence of dementia severity on dual-task performance and interference. Thirty PWD in two residential care facilities (Age: 81.3 ± 7.1 years; Montreal Cognitive Assessment: 10.4 ± 6.0 points) completed two trials of single- (feet apart) and dual-task posture (feet apart while counting backward), single- (walk 4 m) and dual-task gait (walk 4m while naming words), and single- (timed-up-and-go (TUG)), and dual-task functional mobility (TUG while completing a category task) with APDM inertial sensors. Dual-tasks resulted in greater sway frequency, jerk, and sway area; slower gait speed; greater double limb support; shorter stride length; reduced mid-swing elevation; longer TUG duration; reduced turn angle; and slower turn velocity than single-tasks (ps < 0.05). Dual-task performance was impacted (reduced double limb support, greater mid-swing elevation), and dual-task interference (greater jerk, faster gait speed) was related to moderate-to-severe compared to mild PWD. Moderate-to-severe PWD had poorer dynamic stability and a reduced ability to appropriately select a cautious gait during dual-tasks than those with mild PWD, indicating the usefulness of dual-tasks for cognitive screening.

Adaptation of Postural Sway in a Standing Position during Tilted Video Viewing Using Virtual Reality: A Comparison between Younger and Older Adults.

This study aimed to investigate the effects of wearing virtual reality (VR) with a head-mounted display (HMD) on body sway in younger and older adults. A standing posture with eyes open without an HMD constituted the control condition. Wearing an HMD and viewing a 30°-tilt image and a 60°-tilt image in a resting standing position were the experimental conditions. Measurements were made using a force plate. All conditions were performed three times each and included the X-axis trajectory length (mm), Y-axis trajectory length (mm), total trajectory length (mm), trajectory length per unit time (mm/s), outer peripheral area (mm2), and rectangular area (mm2). The results showed a significant interaction between generation and condition in Y-axis trajectory length (mm) and total trajectory length (mm), with an increased body center-of-gravity sway during the viewing of tilted VR images in older adults than in younger adults in both sexes. The results of this study show that body sway can be induced by visual stimulation alone with VR without movement, suggesting the possibility of providing safe and simple balance training to older adults.

In-Laboratory Polysomnography Worsens Obstructive Sleep Apnea by Changing Body Position Compared to Home Testing.

(1) Background: Home sleep apnea testing, known as polysomnography type 3 (PSG3), underestimates respiratory events in comparison with in-laboratory polysomnography type 1 (PSG1). Without head electrodes for scoring sleep and arousal, in a home environment, patients feel unfettered and move their bodies more naturally. Adopting a natural position may decrease obstructive sleep apnea (OSA) severity in PSG3, independently of missing hypopneas associated with arousals. (2) Methods: Patients with suspected OSA performed PSG1 and PSG3 in a randomized sequence. We performed an additional analysis, called reduced polysomnography, in which we blindly reassessed all PSG1 tests to remove electroencephalographic electrodes, electrooculogram, and surface electromyography data to estimate the impact of not scoring sleep and arousal-based hypopneas on the test results. A difference of 15 or more in the apnea-hypopnea index (AHI) between tests was deemed clinically relevant. We compared the group of patients with and without clinically relevant differences between lab and home tests (3) Results: As expected, by not scoring sleep, there was a decrease in OSA severity in the lab test, similar to the home test results. The group of patients with clinically relevant differences between lab and home tests presented more severe OSA in the lab compared to the other group (mean AHI, 42.5 vs. 20.2 events/h, p = 0.002), and this difference disappeared in the home test. There was no difference between groups in the shift of OSA severity by abolishing sleep scoring in the lab. However, by comparing lab and home tests, there were greater variations in supine AHI and time spent in the supine position in the group with a clinically relevant difference, either with or without scoring sleep, showing an impact of the site of the test on body position during sleep. These variations presented as a marked increase or decrease in supine outcomes according to the site of the test, with no particular trend. (4) Conclusions: In-lab polysomnography may artificially increase OSA severity in a subset of patients by inducing marked changes in body position compared to home tests. The location of the sleep test seems to interfere with the evaluation of patients with more severe OSA.

Estimation of Shoulder Joint Rotation Angle Using Tablet Device and Pose Estimation Artificial Intelligence Model.

Traditionally, angle measurements have been performed using a goniometer, but the complex motion of shoulder movement has made these measurements intricate. The angle of rotation of the shoulder is particularly difficult to measure from an upright position because of the complicated base and moving axes. In this study, we attempted to estimate the shoulder joint internal/external rotation angle using the combination of pose estimation artificial intelligence (AI) and a machine learning model. Videos of the right shoulder of 10 healthy volunteers (10 males, mean age 37.7 years, mean height 168.3 cm, mean weight 72.7 kg, mean BMI 25.6) were recorded and processed into 10,608 images. Parameters were created using the coordinates measured from the posture estimation AI, and these were used to train the machine learning model. The measured values from the smartphone's angle device were used as the true values to create a machine learning model. When measuring the parameters at each angle, we compared the performance of the machine learning model using both linear regression and Light GBM. When the pose estimation AI was trained using linear regression, a correlation coefficient of 0.971 was achieved, with a mean absolute error (MAE) of 5.778. When trained with Light GBM, the correlation coefficient was 0.999 and the MAE was 0.945. This method enables the estimation of internal and external rotation angles from a direct-facing position. This approach is considered to be valuable for analyzing motor movements during sports and rehabilitation.

Biomechanical Posture Analysis in Healthy Adults with Machine Learning: Applicability and Reliability.

Posture analysis is important in musculoskeletal disorder prevention but relies on subjective assessment. This study investigates the applicability and reliability of a machine learning (ML) pose estimation model for the human posture assessment, while also exploring the underlying structure of the data through principal component and cluster analyses. A cohort of 200 healthy individuals with a mean age of 24.4 ± 4.2 years was photographed from the frontal, dorsal, and lateral views. We used Student's t-test and Cohen's effect size (d) to identify gender-specific postural differences and used the Intraclass Correlation Coefficient (ICC) to assess the reliability of this method. Our findings demonstrate distinct sex differences in shoulder adduction angle (men: 16.1° ± 1.9°, women: 14.1° ± 1.5°, d = 1.14) and hip adduction angle (men: 9.9° ± 2.2°, women: 6.7° ± 1.5°, d = 1.67), with no significant differences in horizontal inclinations. ICC analysis, with the highest value of 0.95, confirms the reliability of the approach. Principal component and clustering analyses revealed potential new patterns in postural analysis such as significant differences in shoulder-hip distance, highlighting the potential of unsupervised ML for objective posture analysis, offering a promising non-invasive method for rapid, reliable screening in physical therapy, ergonomics, and sports.

Smart Sensing Chairs for Sitting Posture Detection, Classification, and Monitoring: A Comprehensive Review.

Incorrect sitting posture, characterized by asymmetrical or uneven positioning of the body, often leads to spinal misalignment and muscle tone imbalance. The prolonged maintenance of such postures can adversely impact well-being and contribute to the development of spinal deformities and musculoskeletal disorders. In response, smart sensing chairs equipped with cutting-edge sensor technologies have been introduced as a viable solution for the real-time detection, classification, and monitoring of sitting postures, aiming to mitigate the risk of musculoskeletal disorders and promote overall health. This comprehensive literature review evaluates the current body of research on smart sensing chairs, with a specific focus on the strategies used for posture detection and classification and the effectiveness of different sensor technologies. A meticulous search across MDPI, IEEE, Google Scholar, Scopus, and PubMed databases yielded 39 pertinent studies that utilized non-invasive methods for posture monitoring. The analysis revealed that Force Sensing Resistors (FSRs) are the predominant sensors utilized for posture detection, whereas Convolutional Neural Networks (CNNs) and Artificial Neural Networks (ANNs) are the leading machine learning models for posture classification. However, it was observed that CNNs and ANNs do not outperform traditional statistical models in terms of classification accuracy due to the constrained size and lack of diversity within training datasets. These datasets often fail to comprehensively represent the array of human body shapes and musculoskeletal configurations. Moreover, this review identifies a significant gap in the evaluation of user feedback mechanisms, essential for alerting users to their sitting posture and facilitating corrective adjustments.

Effect of the early diastolic blood pressure response to the head-up tilt test on the recurrence of benign paroxysmal positional vertigo.

BACKGROUND: Otolith organ acts complementarily with the autonomic nervous system to maintain blood pressure. However, the effect of blood pressure variability in the autonomic nervous system on otolith organ has not yet been determined. This study aimed to verify the hypothesis that blood pressure variability in the autonomic nervous system affects the recurrence of benign paroxysmal positional vertigo (BPPV), which is the most common disease of the vestibular organs, by using the head-up tilt test (HUTT). METHODS: This study included 432 patients diagnosed with idiopathic BPPV. The follow-up period for all patients was 12 months. Age, sex, hypertension, diabetes and recurrence were analyzed. The HUTT parameters were divided into a group of patients whose average diastolic blood pressure increased in the upright position compared to supine position during the HUTT (DBP1) and a group of patients whose average diastolic blood pressure decreased in the upright position compared to supine position during the HUTT (DBP2). Model selection, general loglinear analysis, and logit loglinear analysis were performed using a hierarchically progressing loglinear analysis. RESULTS: In summary, the group with increased average diastolic blood pressure (DBP1) showed a higher tendency for BPPV recurrence compared to the group with decreased diastolic blood pressure (DBP2) in the upright position during the HUTT, although the difference was not statistically significant (p = 0.080). However, in males, the DBP1 group demonstrated a significantly higher recurrence rate of BPPV than the DBP2 group during the HUTT (95% CI, -20.021 to -16.200; p < 0.001). CONCLUSIONS: It is presumed that poor autonomic nervous system response through vestibulosympathetic reflex maintains elevated diastolic blood pressure in the upright position during the HUTT. This variability is assumed to affect the recurrence of BPPV.

LEAPSE: Learning Environment Affordances for 3D Human Pose and Shape Estimation.

We live in a 3D world where people interact with each other in the environment. Learning 3D posed humans therefore requires us to perceive and interpret these interactions. This paper proposes LEAPSE, a novel method that learns salient instance affordances for estimating a posed body from a single RGB image in a non-parametric manner. Existing methods mostly ignore the environment and estimate the human body independently from the surroundings. We capture the influences of non-contact and contact instances on a posed body as an adequate representation of the "environment affordances". The proposed method learns the global relationships between 3D joints, body mesh vertices, and salient instances as environment affordances on the human body. LEAPSE achieved state-of-the-art results on the 3DPW dataset with many affordance instances, and also demonstrated excellent performance on Human3.6M dataset. We further demonstrate the benefit of our method by showing that the performance of existing weak models can be significantly improved when combined with our environment affordance module.

Cortical activity associated with the maintenance of balance during unstable stances.

Background: Humans continuously maintain and adjust posture during gait, standing, and sitting. The difficulty of postural control is reportedly increased during unstable stances, such as unipedal standing and with closed eyes. Although balance is slightly impaired in healthy young adults in such unstable stances, they rarely fall. The brain recognizes the change in sensory inputs and outputs motor commands to the musculoskeletal system. However, such changes in cortical activity associated with the maintenance of balance following periods of instability require further clarified. Methods: In this study, a total of 15 male participants performed two postural control tasks and the center of pressure displacement and electroencephalogram were simultaneously measured. In addition, the correlation between amplitude of center of pressure displacement and power spectral density of electroencephalogram was analyzed. Results: The movement of the center of pressure was larger in unipedal standing than in bipedal standing under both eye open and eye closed conditions. It was also larger under the eye closed condition compared with when the eyes were open in unipedal standing. The amplitude of high-frequency bandwidth (1-3 Hz) of the center of pressure displacement was larger during more difficult postural tasks than during easier ones, suggesting that the continuous maintenance of posture was required. The power spectral densities of the theta activity in the frontal area and the gamma activity in the parietal area were higher during more difficult postural tasks than during easier ones across two postural control tasks, and these correlate with the increase in amplitude of high-frequency bandwidth of the center of pressure displacement. Conclusions: Taken together, specific activation patterns of the neocortex are suggested to be important for the postural maintenance during unstable stances.

Evaluation of a method to quantify posture and scapula position using biplanar radiography.

BACKGROUND: Recent studies have stated the relevance of having new parameters to quantify the position and orientation of the scapula with patients standing upright. Although biplanar radiography can provide 3D reconstructions of the scapula and the spine, it is not yet possible to acquire these images with patients in the same position. METHODS: Two pairs of images were acquired, one for the 3D reconstruction of the spine and ribcage and one for the 3D reconstruction of the scapula. Following 3D reconstructions, scapular alignment was performed in two stages, a coarse alignment based on manual annotations of landmarks on the clavicle and pelvis, and an adjusted alignment. Clinical parameters were computed: protraction, internal rotation, tilt and upward rotation. Reproducibility was assessed on an in vivo dataset of upright biplanar radiographs. Accuracy was assessed using supine cadaveric CT-scans and digitally reconstructed radiographs. FINDINGS: The mean error was less than 2° for all clinical parameters, and the 95 % confidence interval for reproducibility ranged from 2.5° to 5.3°. INTERPRETATION: The confidence intervals were lower than the variability measured between participants for the clinical parameters assessed, which indicates that this method has the potential to detect different patterns in pathological populations.

Plantar load distribution with centers of gravity balance and rearfoot posture in daily lives of Taiwanese college elite table tennis players: a cross-sectional study.

Background: Table tennis is an asymmetric sport involving the powerful forward swing of the upper limbs depends on the solid support of the lower limbs. The foot drive really affects the weight balance and stroke accuracy even though the distance and momentum of the lower limb displacement are limited within a limited range. Given that previous research on table tennis has typically focused on the footwork and stroke performance of professional players, the study aimed to investigate the daily static and dynamic plantar load distribution as well as the centers of gravity balance and rearfoot posture among Taiwanese college elite table tennis players. Methods: This is a cross-sectional study of 70 elite male table tennis players (age: 20.0 ± 0.9 years; height: 173.4 ± 5.1 cm, weight: 67.6 ± 5.3 kg, experience: 10.0 ± 1.6 years) and 77 amateur table tennis players of the same gender (age: 20.1 ± 0.8 years, height: 167.4 ± 4.4 cm, weight: 64.3 ± 4.0 kg, experience: 4.4 ± 1.2 years) from Taiwanese universities. The JC Mat optical plantar pressure analyzer was applied to determine the plantar load distribution along with arch index (AI) and centers of gravity balance. Assessment of rearfoot postural alignment was mainly used to contrast the performance of the centers of gravity balance. Results: The static arch indices of both feet in the elite group were symmetrical and considered normal arches (AI: 0.22 ± 0.07) during their non-training and non-competition daily lives. Their static plantar loads were symmetrically concentrated on the bipedal lateral metatarsals (P < 0.05) as well as shifted to the medial and lateral heels (P < 0.05) and the lateral metatarsals (P < 0.05) during the walking midstance phase. Additionally, the plantar loads were mainly applied to the bipedal medial (P < 0.01) and lateral heels (P < 0.05) during the transitional changes between both states. Elite athletes had symmetrical and evenly distributed centers of gravity on both feet (left: 50.03 ± 4.47%; right: 49.97 ± 4.47%) when standing statically, along with symmetrical rearfoot angles and neutral position of the subtalar joint (left: 2.73 ± 2.30°; right: 2.70 ± 2.32°) even though they were statistically lower than those of the amateur athletes (P < 0.05). Conclusions: The daily static and dynamic foot patterns of Taiwanese college elite table tennis players were characterized by plantar load distribution on the lateral metatarsals and the entire calcaneus along with balanced centers of gravity and normal rearfoot posture. This foot and posture layout outlines the excellent athletic performance of the foot and ankle in professional athletes. Portions of this text were previously published as part of a preprint (https://doi.org/10.21203/rs.3.rs-2993403/v1).

sEMG-Based Robust Recognition of Grasping Postures with a Machine Learning Approach for Low-Cost Hand Control.

The design and control of artificial hands remains a challenge in engineering. Popular prostheses are bio-mechanically simple with restricted manipulation capabilities, as advanced devices are pricy or abandoned due to their difficult communication with the hand. For social robots, the interpretation of human intention is key for their integration in daily life. This can be achieved with machine learning (ML) algorithms, which are barely used for grasping posture recognition. This work proposes an ML approach to recognize nine hand postures, representing 90% of the activities of daily living in real time using an sEMG human-robot interface (HRI). Data from 20 subjects wearing a Myo armband (8 sEMG signals) were gathered from the NinaPro DS5 and from experimental tests with the YCB Object Set, and they were used jointly in the development of a simple multi-layer perceptron in MATLAB, with a global percentage success of 73% using only two features. GPU-based implementations were run to select the best architecture, with generalization capabilities, robustness-versus-electrode shift, low memory expense, and real-time performance. This architecture enables the implementation of grasping posture recognition in low-cost devices, aimed at the development of affordable functional prostheses and HRI for social robots.

Measurement of Sedentary Behavior-The Outcomes of the Angle for Posture Estimation (APE) Method.

Hip-worn accelerometers are commonly used to assess habitual physical activity, but their accuracy in precisely measuring sedentary behavior (SB) is generally considered low. The angle for postural estimation (APE) method has shown promising accuracy in SB measurement. This method relies on the constant nature of Earth's gravity and the assumption that walking posture is typically upright. This study investigated how cardiorespiratory fitness (CRF) and body mass index (BMI) are related to APE output. A total of 3475 participants with adequate accelerometer wear time were categorized into three groups according to CRF or BMI. Participants in low CRF and high BMI groups spent more time in reclining and lying postures (APE ≥ 30°) and less time in sitting and standing postures (APE < 30°) than the other groups. Furthermore, the strongest partial Spearman correlation with CRF (r = 0.284) and BMI (r = -0.320) was observed for APE values typical for standing. The findings underscore the utility of the APE method in studying associations between SB and health outcomes. Importantly, this study emphasizes the necessity of reserving the term "sedentary behavior" for studies wherein the classification of SB is based on both intensity and posture.

Susceptibility of optic nerve head in children with posture-related elevation of intraocular pressure.

BACKGROUND/AIMS: This work aimed to investigate changes in optic nerve head (ONH) morphometry based on Bruch membrane opening in children with extensive nocturnal intraocular pressure (IOP) elevations. METHODS: The course of Bruch membrane opening-based optic nerve head (ONH) morphometry was analysed in thirty-two patients younger than 18 years with evaluable SD-OCT examinations of the ONH and nocturnal posture-dependent IOP elevation above 25 mmHg. Longitudinal changes in neuroretinal rim tissue, as measured by Bruch Membrane opening minimum rim width (BMO-MRW) and peripapillary retinal nerve fiber layer (RNFL) thickness, were assessed. RESULTS: One year after the 24 h IOP measurement, global BMO-MRW (- 1.61 ± 16.8 µm, n.s.; p = 0.611) and RNFL (+ 0.64 ± 3.17 µm; n.s.; p = 0.292) measurements were not significantly different from the baseline. No significant BMO-MRW reduction (- 3.91 ± 24.3 µm; n.s. p = 0.458) or deviation in RNFL thickness (+ 1.10 ± 3.52 µm) was observed at the four-year follow-up. Absolute IOP values measured in the supine position did not correlate with changes in global BMO-MRW or RNFL thickness. CONCLUSION: Posture-dependent IOP elevations do not seem to influence retinal nerve fibre layer thickness or Bruch membrane opening-based morphometric data in childhood.

Gender differences in spinal mobility during postural changes: a detailed analysis using upright CT.

Lumbar spinal alignment is crucial for spine biomechanics and is linked to various spinal pathologies. However, limited research has explored gender-specific differences using CT scans. The objective was to evaluate and compare lumbar spinal alignment between standing and sitting CT in healthy individuals, focusing on gender differences. 24 young and 25 elderly males (M) and females (F) underwent standing and sitting CT scans to assess lumbar spinal alignment. Parameters measured and compared between genders included lumbar lordosis (LL), sacral slope (SS), pelvic tilt (PT), pelvic incidence (PI), lordotic angle (LA), foraminal height (FH), and bony boundary area (BBA). Females showed significantly larger changes in SS and PT when transitioning from standing to sitting (p = .044, p = .038). A notable gender difference was also observed in the L4-S LA among the elderly, with females showing a significantly larger decrease in lordotic angle compared to males (- 14.1° vs. - 9.2°, p = .039*). Females consistently exhibited larger FH and BBA values, particularly in lower lumbar segments, which was more prominent in the elderly group (M vs. F: L4/5 BBA 80.1 mm2 [46.3, 97.8] vs. 109.7 mm2 [74.4, 121.3], p = .019 in sitting). These findings underline distinct gender-related variations in lumbar alignment and flexibility, with a focus on noteworthy changes in BBA and FH in females. Gender differences in lumbar spinal alignment were evident, with females displaying greater pelvic and sacral mobility. Considering gender-specific characteristics is crucial for assessing spinal alignment and understanding spinal pathologies. These findings contribute to our understanding of lumbar spinal alignment and have implications for gender-specific spinal conditions and treatments.

Machine learning-based detection of acute psychosocial stress from body posture and movements.

Investigating acute stress responses is crucial to understanding the underlying mechanisms of stress. Current stress assessment methods include self-reports that can be biased and biomarkers that are often based on complex laboratory procedures. A promising additional modality for stress assessment might be the observation of body movements, which are affected by negative emotions and threatening situations. In this paper, we investigated the relationship between acute psychosocial stress induction and body posture and movements. We collected motion data from N = 59 individuals over two studies (Pilot Study: N = 20, Main Study: N = 39) using inertial measurement unit (IMU)-based motion capture suits. In both studies, individuals underwent the Trier Social Stress Test (TSST) and a stress-free control condition (friendly-TSST; f-TSST) in randomized order. Our results show that acute stress induction leads to a reproducible freezing behavior, characterized by less overall motion as well as more and longer periods of no movement. Based on these data, we trained machine learning pipelines to detect acute stress solely from movement information, achieving an accuracy of 75.0 ± 17.7 % (Pilot Study) and 73.4 ± 7.7 % (Main Study). This, for the first time, suggests that body posture and movements can be used to detect whether individuals are exposed to acute psychosocial stress. While more studies are needed to further validate our approach, we are convinced that motion information can be a valuable extension to the existing biomarkers and can help to obtain a more holistic picture of the human stress response. Our work is the first to systematically explore the use of full-body body posture and movement to gain novel insights into the human stress response and its effects on the body and mind.

Analysis of the obstetrician's posture and movements during a simulated forceps delivery.

BACKGROUND: The objective of this study was to identify and qualify, by means of a three-dimensional kinematic analysis, the postures and movements of obstetricians during a simulated forceps birth, and then to study the association of the obstetricians' experience with the technique adopted. METHOD: Fifty-seven volunteer obstetricians, 20 from the Limoges and 37 from the Poitiers University hospitals, were included in this multi-centric study. They were classified into 3 groups: beginners, intermediates, and experts, beginners having performed fewer than 10 forceps deliveries in real conditions, intermediates between 10 and 100, and experts more than 100. The posture and movements of the obstetricians were recorded between December 2020 and March 2021 using an optoelectronic motion capture system during simulated forceps births. Joint angles qualifying these postures and movements were analysed between the three phases of the foetal traction. These phases were defined by the passage of a virtual point associated with the forceps blade through two anatomical planes: the mid-pelvis and the pelvic outlet. Then, a consolidated ascending hierarchical classification (AHC) was applied to these data in order to objectify the existence of groups of similar behaviours. RESULTS: The AHC distinguished four different postures adopted when crossing the first plane and three different traction techniques. 48% of the beginners adopted one of the two raised posture, 22% being raised without trunk flexion and 26% raised with trunk flexion. Conversely, 58% of the experts positioned themselves in a "chevalier servant" posture (going down on one knee) and 25% in a "squatting" posture before initiating traction. The results also show that the joint movement amplitude tends to reduce with the level of expertise. CONCLUSION: Forceps delivery was performed in different ways, with the experienced obstetricians favouring postures that enabled observation at the level of the maternal perineum and techniques reducing movement amplitude. The first perspective of this work is to relate these different techniques to the traction force generated. The results of these studies have the potential to contribute to the training of obstetricians in forceps delivery, and to improve the safety of women and newborns.

An enhanced real-time human pose estimation method based on modified YOLOv8 framework.

The objective of human pose estimation (HPE) derived from deep learning aims to accurately estimate and predict the human body posture in images or videos via the utilization of deep neural networks. However, the accuracy of real-time HPE tasks is still to be improved due to factors such as partial occlusion of body parts and limited receptive field of the model. To alleviate the accuracy loss caused by these issues, this paper proposes a real-time HPE model called CCAM - Person based on the YOLOv8 framework. Specifically, we have improved the backbone and neck of the YOLOv8x-pose real-time HPE model to alleviate the feature loss and receptive field constraints. Secondly, we introduce the context coordinate attention module (CCAM) to augment the model's focus on salient features, reduce background noise interference, alleviate key point regression failure caused by limb occlusion, and improve the accuracy of pose estimation. Our approach attains competitive results on multiple metrics of two open-source datasets, MS COCO 2017 and CrowdPose. Compared with the baseline model YOLOv8x-pose, CCAM-Person improves the average precision by 2.8% and 3.5% on the two datasets, respectively.