Postural Variables Research Articles

Gesture Recognition through Mechanomyogram Signals: An Adaptive Framework for Arm Posture Variability.

In hand gesture recognition, classifying gestures across multiple arm postures is challenging due to the dynamic nature of muscle fibers and the need to capture muscle activity through electrical connections with the skin. This paper presents a gesture recognition architecture addressing the arm posture challenges using an unsupervised domain adaptation technique and a wearable mechanomyogram (MMG) device that does not require electrical contact with the skin. To deal with the transient characteristics of muscle activities caused by changing arm posture, Continuous Wavelet Transform (CWT) combined with Domain-Adversarial Convolutional Neural Networks (DACNN) were used to extract MMG features and classify hand gestures. DACNN was compared with supervised trained classifiers and shown to achieve consistent improvement in classification accuracies over multiple arm postures. With less than 5 minutes of setup time to record 20 examples per gesture in each arm posture, the developed method achieved an average prediction accuracy of 87.43% for classifying 5 hand gestures in the same arm posture and 64.29% across 10 different arm postures. When further expanding the MMG segmentation window from 200 ms to 600 ms to extract greater discriminatory information at the expense of longer response time, the intraposture and inter-posture accuracies increased to 92.32% and 71.75%. The findings demonstrate the capability of the proposed method to improve generalization throughout dynamic changes caused by arm postures during non-laboratory usages and the potential of MMG to be an alternative sensor with comparable performance to the widely used electromyogram (EMG) gesture recognition systems.

The effects of umbrella handle shape and grip type on muscle activation and postural variability under windy conditions

This study investigated how different shapes of umbrella handles and grip types influence muscle activation and postural variability under windy conditions. Seventeen adult participants were enrolled in this study, and different handle shapes (cylindrical, ellipsoidal, and triangular prism-shaped), grip types (four- and five-finger grip), and wind strengths were tested. Activation of the forearm and upper arm muscles was recorded using surface electromyography. Postural variability and ratings of (1) perceived difficulty of use and (2) perceived grip-posture variability were measured. The results indicated that activation of the finger flexor muscle increased under windy conditions, whereas postural variability was not affected. Weak wind (3.2–7.5 m/s) conditions caused greater perceived postural variability and activation of the wrist extensor muscle. The ellipsoidal handle shape had lower endpoint postural variability when held with a five-finger grip and also had lower perceived postural variability and difficulty compared to that with the cylindrical shape. Our findings can be used to select appropriate umbrella handle designs based on grip type and wind conditions.

The effects of dual screen layout on neck-shoulder muscle activity and head-neck posture variability during computer tasks.

Larger dual screens have been widely used during office work and their biomechanical exposure should be explored. To investigate the biomechanical effect of two dual screen layouts on neck-shoulder muscle activity and the variability of head-neck posture in computer users. A preliminary study of the user-preferred dual screen angles was carried out in V-shaped and L-shaped layouts. Twenty healthy participants aged 19 to 26 years were recruited and assigned to perform reading, typing, and searching tasks for 30 minutes in both workstation layouts. Electromyography was measured at bilateral cervical erector spinae (CES), sternocleidomastoid (SCM), and upper trapezius (UT). The head-neck lateral bending, rotation, and flexion angles were recorded. The visual analog scale (VAS) was used to evaluate visual strain. The muscle activity at the left UT and right CES sites when using the V-shaped layout was significantly higher than the L-shaped. There were significant differences in head-neck rotation and flexion angles between the two layouts in reading and typing tasks. In the searching task, there was no significant difference in the head-neck rotation and flexion angles between the two layouts. The visual strain score was significantly higher in the V-shaped layout. The CES and UT muscles displayed higher levels of activation while using the V-shaped layout in comparison to the L-shaped layout. The head-neck rotation and flexion angles differed due to varied types of work when using V-shaped and L-shaped layouts.

Measurement of Three-Dimensional Back Shape of Normal Adults Using a Novel Three-Dimensional Imaging Mobile Surface Topography System (MSTS): An Intra- and Inter-Rater Reliability Study

Postural and spinal deformities are major contributing factors to musculoskeletal (MSK) disorders. Posture screening and assessment can help to identify early morphological deformities, thereby preventing progression and reducing or correcting them with effective treatments. The study evaluates both intra- and inter-repeatability of using a mobile structured light sensor with a structured light pattern for building an accurate 3D human model and its use in postural screening. 16 young males (age: 25 ± 5.6 years, height: 172 ± 5.3 cm, mass: 69 ± 8.6 kg) participated without any musculoskeletal pain or pre-existing leg or spinal abnormalities. An iPad-based 3D mobile scanning tool, Structure SensorTM (2018 version), was used to capture the participants’ back and whole-body shape. The collected data (3D model) were realigned and processed in the open-source software, Netfabb BasicTM (7.2 version). For each participant, five trained raters individually measured three trials of standing back and body posture on two separate occasions to calculate both intra- and inter-rater reliability. With the use of this software, nine postural variables and angular displacements were individually measured by the raters. The results indicated good to excellent intra-rater and good to moderate inter-rater reliability for measuring 78% (7 out of 9) of postural variables with an ICC ranging from 0.70 to 0.98. The remaining 22% of variables (2 out of 9; lateral pelvic tilt and right frontal knee angle) showed moderate to low inter- and intra-rater reliability, with ICCs ranging from 0.26 to 0.79.

Numerical study on the effect of the realistic mouth-inhaler positions on orally inhaled drug delivery in pediatric intersubject upper airways

The relative position between the pediatric upper airway and the inhalation device during real inhalation administration has significant effects on the delivery efficiency of orally inhaled drugs. Morphological variability plays an important role in this process. However, the mouth-throat differences between adults and children were usually neglected because most of the commercial inhalation devices currently are designed for adults or older adolescents. The main objective of this study is to investigate these effects by four realistic pediatric mouth-throat (RMT) geometries. In addition, an idealized mouth-throat (IMT) model was developed to validate the numerical model and to compare with the RMT models. Computational fluid dynamics (CFD) simulations were performed to investigate the flow pattern and deposition pattern in these models and the results were compared with the cascade impactor experiments, replica experiments and in vivo results. No significant correlation (p > 0.1) between the relative position parameters and inhaler insertion depth can be noticed among the RMT models. Notably, significant variability in the inhaler posture was observed in RMT models, especially for the S4 model. Airflow structure shows that the RMT model has a complex onset of turbulence, reverse flow and subsequently vortex formation when compared with the IMT model. The oral cavity is the region with the largest deposition fraction (DF) and deposition efficiency (DE). The DF and DE of the oral cavity are negatively correlated to the position parameter (Lm) when mass median aerodynamic diameter (MMAD) of indacaterol 150 μg was utilized as the input particle parameter. The relative position between the inhaler and oral cavity has significant effects on the particle transport and deposition. Furthermore, in silico results overestimated the lung deposition in comparison to the in vivo and experimental results when MMAD was used as input. To resolve the disparity between the in silico and in vivo results, a modified prediction method based on the cascade impactor and original in silico results was proposed and a good correlation of the relative contribution of pulmonary absorption to total systemic exposure (flung) was found between the predicted and observed results. The findings of present work will provide useful information in understanding the particle transport and deposition in the pediatric airways for the design of inhaler.

RETRACTED: Vision-based tracking method of nighttime construction workers by integrating YOLOv5 and Deepsort

Due to poor visibility and fatigue factors, although nighttime construction has been widely used, its safety problems like struck-by accidents have also become increasingly prominent. Most of the current tracking methods of workers are not suitable for direct application in nighttime construction scenarios, so this research proposes a vision-based method, which integrates low-light image enhancement technology, YOLOv5 and Deepsort to track nighttime workers. The proposed method is mainly composed of four modules, including illumination enhancement module, detection module, the Kalman filter and matching module. In the experiment based on nine test videos, the method achieved the average multiple-object tracking accuracy (MOTA) of 89.93% and multiple-object tracking precision (MOTP) of 97.07%. At the same time, the experimental results also show that the method is robust to the common tracking challenges of occlusions, scale variations and posture variations. The proposed method has practical application potential in the monitoring task in nighttime construction, which makes the nighttime construction activities safer and more efficient.

RETRACTED: Vision-based tracking method of nighttime construction workers by integrating YOLOv5 and Deepsort (REDIRECT)

Due to poor visibility and fatigue factors, although nighttime construction has been widely used, its safety problems like struck-by accidents have also become increasingly prominent. Most of the current tracking methods of workers are not suitable for direct application in nighttime construction scenarios, so this research proposes a vision-based method, which integrates low-light image enhancement technology, YOLOv5 and Deepsort to track nighttime workers. The proposed method is mainly composed of four modules, including illumination enhancement module, detection module, the Kalman filter and matching module. In the experiment based on nine test videos, the method achieved the average multiple-object tracking accuracy (MOTA) of 89.93% and multiple-object tracking precision (MOTP) of 97.07%. At the same time, the experimental results also show that the method is robust to the common tracking challenges of occlusions, scale variations and posture variations. The proposed method has practical application potential in the monitoring task in nighttime construction, which makes the nighttime construction activities safer and more efficient.

Complex Neck Loading and Injury Tolerance in Lateral Bending With Head Rotation From Human Cadaver Tests.

Advancements in automated vehicles may position the occupant in postures different from the current standard posture. It may affect human tolerance responses. The objective of this study was to determine the lateral bending tolerance of the head-cervical spine with initial head rotation posture using loads at the occipital condyles and lower neck and describe injuries. Using a custom loading device, head-cervical spine complexes from human cadavers were prepared with load cells at the ends. Lateral bending loads were applied to prerotated specimens at 1.5 m/s. At the occipital condyles, peak axial and antero-posterior and medial-lateral shear forces were: 316-954 N, 176-254 N, and 327-508 N, and coronal, sagittal, and axial moments were: 27-38 N·m, 21-38 N·m, and 9.7-19.8 N·m, respectively. At the lower neck, peak axial and shear forces were: 677-1004 N, 115-227 N, and 178-350 N, and coronal, sagittal, and axial moments were: 30-39 N·m, 7.6-21.3 N·m, and 5.7-13.4 N·m, respectively. Ipsilateral atlas lateral mass fractures occurred in four out of five specimens with varying joint diastasis and capsular ligament involvements. Acknowledging that the study used a small sample size, initial tolerances at the occipital condyles and lower neck were estimated using survival analysis. Injury patterns with posture variations are discussed.

Head posture impacts mammalian hyoid position and suprahyoid muscle length: implication for swallowing biomechanics.

Instantaneous head posture (IHP) can extensively alter resting hyoid position in humans, yet postural effects on resting hyoid position remain poorly documented among mammals in general. Clarifying this relationship is essential for evaluating interspecific variation in hyoid posture across evolution, and understanding its implications for hyolingual soft tissue function and swallowing motor control. Using Didelphis virginiana as a model, we conducted static manipulation experiments to show that head flexion shifts hyoid position rostrally relative to the cranium across different gapes. IHP-induced shifts in hyoid position along the anteroposterior axis are comparable to in vivo hyoid protraction distance during swallowing. IHP also has opposite effects on passive genio- and stylohyoid muscle lengths. High-speed biplanar videoradiography suggests Didelphis consistently swallows at neutral to flexed posture, with stereotyped hyoid kinematics across different head postures. IHP change can affect suprahyoid muscle force production by shifting their positions on the length-tension curve, and redirecting lines of action and the resultant force from supra- and infrahyoid muscles. We hypothesize that demands on muscle performance may constrain the range of swallowing head postures in mammals. This article is part of the theme issue 'Food processing and nutritional assimilation in animals'.

Wearable sensors-based postural analysis and fall risk assessment among patients with diabetic foot neuropathy

AimsTo investigate the cross-sectional association between deep and superficial diabetic neuropathy, postural impairment assessed by wearable inertial sensors, and the risk of fall among patients with diabetic foot. MethodsDiabetic patients attending a University Podiatric Clinic were evaluated for the presence of deep and superficial peripheral neuropathy in sensory tests. Postural impairment was assessed using a wearable inertial sensor, and the evaluation of balance/gait and risk of fall was determined by the Tinetti Scale and Downton Index, respectively. Glycemic control was measured by glycated haemoglobin concentration and fasting glycaemia.The postural parameters measured were the anteroposterior and medio-lateral sway of the center of mass (CoM) and the sway area (area traveled by the CoM per second). The results were analyzed through a logistic regression model to assess those posture variables mostly significantly associated with neuropathy and risk of fall scales. ResultsA total of 85 patients were evaluated. Spearman's rank correlation coefficients showed a strong and significant relationship (p < 0.05) between deep diabetic neuropathy assessed by Semmes-Weinstein monofilament, diapason and biothensiometer and postural alterations, whereas no significant correlations between superficial (painful sensitivity) neuropathy and the postural parameters. The sway path of the displacement along the anterior-posterior axis recorded during tests performed with eyes open and feet close together were significantly (p < 0.05) correlated with a poor glycemic (glycated haemoglobin concentration) control and each other with all diabetic neuropathy tests, fall risk scales, muscular weakness, ankle joint limitation and history of ulcers. ConclusionsThe results support the existence of a strong association between alterations of the deep somato-sensitive pathway (although depending on the tool used to measure peripheral neuropathy), glycemic control and balance impairments assessed using a wearable sensors. Wearable-based postural analysis might be part of the clinical assessment that enables the detection of balance impairments and the risk of fall in diabetic patients with diabetic peripheral neuropathy.

The Effect of Skeletal Muscle-Pump on Blood Pressure and Postural Control in Parkinson's Disease.

Activation of the calf (gastrocnemius and soleus) and tibialis anterior muscles play an important role in blood pressure regulation (via muscle-pump mechanism) and postural control. Parkinson's disease is associated with calf (and tibialis anterior muscles weakness and stiffness, which contribute to postural instability and associated falls. In this work, we studied the role of the medial and lateral gastrocnemius, tibialis anterior, and soleus muscle contractions in maintaining blood pressure and postural stability in Parkinson's patients and healthy controls during standing. In addition, we investigated whether the activation of the calf and tibialis anterior muscles is baroreflex dependent or postural-mediated. We recorded electrocardiogram, blood pressure, center of pressure as a measure of postural sway, and muscle activity from the medial and lateral gastrocnemius, tibialis anterior, and soleus muscles from twenty-six Parkinson's patients and eighteen sex and age-matched healthy controls during standing and with eyes open. The interaction and bidirectional causalities between the cardiovascular, musculoskeletal, and postural variables were studied using wavelet transform coherence and convergent cross-mapping techniques, respectively. Parkinson's patients experienced a higher postural sway and demonstrated mechanical muscle-pump dysfunction of all individual leg muscles, all of which contribute to postural instability. Moreover, our results showed that coupling between the cardiovascular, musculoskeletal, and postural variables is affected by Parkinson's disease while the contribution of the calf and tibialis anterior muscles is greater for blood pressure regulation than postural sway. The outcomes of this study could assist in the development of appropriate physical exercise programs that target lower limb muscles to improve the muscle-pump function and reduce postural instability in Parkinson's disease.

Physiotherapeutic Interventions for Upper Cross Syndrome: A Systematic Review and Meta-Analysis.

Upper cross syndrome is a postural dysfunction that can cause a variety of upper-body musculoskeletal problems. Early detection and physiotherapy can help to prevent further complications. However, no systematic review has evaluated the effect of various physiotherapy intervention strategies to treat this syndrome. Therefore, this study aims to conduct a detailed methodological literature search of the most effective treatment strategies available for the correction of upper cross syndrome. Prospective human subject studies published in the English language that report the assessment and rehabilitation of upper cross syndrome were included. Clinical trials (randomized and non-randomized) were included when compared to a comparator, control group, and no treatment. The search was limited to human subjects and English-language articles. Outcome measures included craniovertebral angle, kyphotic angle, rounded shoulder, neck or shoulder pain, neck range of motion, electromyographic activity of neck or scapular muscles, and functional limitations. To evaluate the methodological quality of randomized controlled trials, the Cochrane collaboration tool was employed. For non-randomized studies, the Risk of Bias in Non-randomized Studies of Intervention was used. The Grading of Recommendations, Assessment, Development, and Evaluation system was used to rate the effectiveness of the evidence. A random-effect meta-analysis was performed for quantitative analysis to report significant differences based on calculated mean differences, with matching 95% confidence intervals (CIs) whenever possible. Out of the 34 potentially relevant articles, 18 were included. The postural variables including craniovertebral angle, kyphotic angle, and rounded shoulder showed a significant improvement with the physiotherapy group compared to the no-treatment group (standardized mean difference = -1.78; 95% CI = -2.68 to -0.87; p = 0.0001). Secondary outcomes such as pain and functional limitation showed a significant difference when advanced manual therapy techniques were used compared to conventional therapy (standardized mean difference = -0.71; 95% CI = -1.04 to -0.39; p< 0.0001; and standardized mean difference = -0.57; 95% CI = -1.00 to -0.14; p = 0.009, respectively). Exercise therapy was found to be beneficial in correcting postural alignment and movement patterns, while manual therapy was found to be similarly effective in pain reduction and functional improvement.

Efficient disentangled representation learning for multi-modal finger biometrics

Most multi-modal biometric systems use multiple devices to capture different traits and directly fuse multi-modal data while ignoring correlation information between modalities. In this paper, finger skin and finger vein images are acquired from the same region of the finger and therefore have a higher correlation. To represent data efficiently, we propose a novel Finger Disentangled Representation Learning Framework (FDRL-Net) that is based on a factorization concept, which disentangles each modality into shared and private features, thereby improving complementarity for better fusion and extracting modality-invariant features for heterogeneous recognition. Besides, to capture as much finger texture as possible, we utilize three-view finger images to reconstruct full-view multi-spectral finger traits, which increases the identity information and the robustness to finger posture variation. Finally, a Boat-Trackers-based multi-task distillation method is proposed to migrate the feature representation ability to a lightweight multi-task network. Extensive experiments on six single-view multi-spectral finger datasets and two full-view multi-spectral finger datasets demonstrate the effectiveness of our approach.

The Importance of Understanding Foot Posture Strategies during Stair Descent for Forensic Incident Investigations

Falls on stairs are commonly claimed to be caused by slipping on the tread nosing, but few studies have explored specific foot kinematics at initial contact during stair descent. Further understanding of such kinematics can aid forensic incident investigations. We investigated foot posture at initial contact with the tread surface of seven participants while descending stairs to determine: a) foot posture variability across participants, and b) the effects of foot posture with respect to the nosing on foot placement. We calculated foot posture as the angle at initial contact relative to the horizontal plane using two consistent landmark points on the subjects’ shoes. Our preliminary results demonstrated inter-subject and intra-subject significant differences in foot posture (P&lt;0.05) for both legs. These results demonstrate that further exploring this at specific instances of the gait cycle during stair descent is crucial to better understand fall events during forensic investigations.

Recognizing the rooting action of prepartum sow in free-farrowing pen using computer vision

The behavior of prepartum sows in natural or semi-natural environments is primarily characterized by their motivation for nest-building. This behavior includes actions such as rooting, pawing, and foraging. Automatic recognition of these specific actions can be beneficial for identifying this nesting behavior and assessing a sow’s maternal ability, as well as predicting the approach of the delivery time. In this study, an automatic method for rooting action recognition was developed for prepartum sow in opened movable crate farrowing pen using computer vision. An object detection model was trained first using the YOLOv5 network to enable the segmentation of the sow body and the head region, as well as posture estimation simultaneously. Then, the FlowNet2.0 network was implemented to estimate the optical flow of sow’s head movement. A histogram of oriented optical flow with adaptive direction adjustment was proposed to select the frames in which the sow’s head moved in the direction of the animal’s body orientation. Finally, a support vector machine (SVM) classifier was trained to classify rooting and non-rooting actions. The input feature vector for the classifier was constructed from variations in head motion direction, sow posture and head position. The developed method was tested using 324 short video episodes (each lasting at least 4 s) and 10 long videos (each lasting about 47 min) of sows in opened movable crate farrowing pens. The test results indicated that the developed method can identify whether a video episode containing rooting action or not with the accuracy, sensitivity, and precision of 93.2%, 93.8%, and 92.7%, respectively. For long videos, our method achieved a sensitivity of 80.3% and precision of 84.5% in detecting temporal rooting action proposals with a temporal Intersection-over-Union (tIOU) ≥ 0.5. The presented method provides an automatic way to detect prepartum sow’s rooting actions, which can be further utilized to recognize their nest-building behavior and predict the impending delivery time of the sows.

VHR-BirdPose: Vision Transformer-Based HRNet for Bird Pose Estimation with Attention Mechanism

Pose estimation plays a crucial role in recognizing and analyzing the postures, actions, and movements of humans and animals using computer vision and machine learning techniques. However, bird pose estimation encounters specific challenges, including bird diversity, posture variation, and the fine granularity of posture. To overcome these challenges, we propose VHR-BirdPose, a method that combines Vision Transformer (ViT) and Deep High-Resolution Network (HRNet) with an attention mechanism. VHR-BirdPose effectively extracts features using Vision Transformer’s self-attention mechanism, which captures global dependencies in the images and allows for better capturing of pose details and changes. The attention mechanism is employed to enhance the focus on bird keypoints, improving the accuracy of pose estimation. By combining HRNet with Vision Transformer, our model can extract multi-scale features while maintaining high-resolution details and incorporating richer semantic information through the attention mechanism. This integration of HRNet and Vision Transformer leverages the advantages of both models, resulting in accurate and robust bird pose estimation. We conducted extensive experiments on the Animal Kingdom dataset to evaluate the performance of VHR-BirdPose. The results demonstrate that our proposed method achieves state-of-the-art performance in bird pose estimation. VHR-BirdPose based on bird images is of great significance for the advancement of bird behaviors, ecological understanding, and the protection of bird populations.

Differences in the effects of orthodontic treatment on airway-craniocervical functional environment in adult and adolescent patients with skeletal class II high-angle: a retrospective pilot study

IntroductionThis retrospective cohort study aimed to compare the change in upper airway and craniocervical posture after orthodontic treatment between adolescent and adult patients with Class II high-angle malocclusion.MethodsA total of 12 adolescent (mean ± standard deviation age = 13.0 ± 2.0 years) and 12 adult patients with Class II high-angle malocclusion (mean ± standard deviation age = 23.7 ± 6.4 years) were selected in this study. The lateral cephalograms and cone beam computed tomography images of adolescent and adult patients were taken before and after treatment, which can be employed to evaluate the variables of craniofacial morphology, upper airway, and craniocervical posture through paired t tests, respectively. An independent sample t test was performed to observe the differences between two groups after orthodontic intervention. For adults and adolescents, the correlation between craniofacial morphology, upper airway, and craniocervical posture was determined through Pearson correlation analysis.ResultsIn all subjects, the improvements in vertical and sagittal facial morphology after treatment were observed. Anterior and inferior movements of the hyoid bone, an increase of upper airway dimension, posterior tipping of the head and a reduction of cervical inclination in the lower and middle segments post-treatment were identified in adolescence (P < 0.05). Adults displayed anterior movements of the hyoid bone, whereas no significant difference was observed in upper airway dimension and craniocervical posture (P < 0.05). Notable differences were identified in the change of hyoid position and airway volume between two groups (P > 0.05). Mandibular plane inclination, growth pattern, occlusal plane inclination, and chin position were all significantly correlated with craniocervical posture in adolescent patients. Besides, the mandibular growth pattern and chin position in adult patients were significantly correlated with craniocervical posture (P < 0.05).ConclusionsOrthodontic treatment is capable of enhancing the facial profile of patients with skeletal class II high-angle while improving their upper airway morphology and craniocervical posture, where adolescents and adults differ substantially in that the former exhibit a more favorable alteration in the airway-craniocervical functional environment.

Multiple Pedestrian Tracking With Graph Attention Map on Urban Road Scene

Pedestrians are often vulnerable users of urban roads and ensuring their safety is a pressing challenge in the filed of intelligent transportation. Multiple pedestrian tracking is one of the key technologies for traffic statistics and abnormal behavior analysis, etc. Detection-based tracking methods have achieved remarkable results and have become mainstream processing schemes. However, target association is still immature and less effective in complex scenarios. In the proposed tracking system, several candidates surrounding each detected pedestrian are selected sparsely, and the associating relationship between the target and these candidates is determined based on a graph attention map. These graph attention maps contain positional correlations of the matching pairs and are applicable with pedestrians&#x2019; posture variations. The weighted correlating value is estimated with the positional weighted matrix and merged attention map. The correlating relationship is confirmed with the weighted correlating value and distance matching loss. To enhance the computation efficiency of the graph attention maps for these tracked targets and candidates, feature extraction is processed separately. Convolutional features extracted from one specific middle layer of the backbone network are used to represent each target or candidate. The experiment results show that the proposed tracker achieves better performance than the other five state-of-the-art trackers on three publicly available databases.

Time-domain Features of Angular-velocity Signals for Camera-based Respiratory RoI detection: A Clinical Study in NICU.

Camera-based measurement of respiratory rate (RR) is emerging for preterm infants monitoring in Neonatal Intensive Care Units (NICU). Accurate detection of respiratory region of interest (Resp-RoI), e.g. thorax and abdomen of infants, is essential for achieving a fully-automatic solution and for high-quality RR estimation. However, the application of fast Fourier transform (FFT) for detecting Resp-RoI in premature infants may not be appropriate due to their irregular breathing patterns. This study proposes a new method for detecting Resp-RoIs in premature infants that uses time-domain features of angular-velocity of respiration. By fusing respiratory motion on orthogonal directions, the proposed method is more robust to variations of infant posture in the incubator.. In addition, using inter-beat interval (IBI) features in the time domain helps to distinguish between Resp-RoI and background. The proposed method was validated on 20 preterm infants in NICU. It obtains a clear improvement on Resp-RoI detection (RoI correspondence = 0.74) and RR estimation (MAE = 3.62 bpm) against the benchmarked approaches (maxFFT: RoI correspondence = 0.45, MAE = 5.61 bpm).

Effect of sit-stand workstation position and computer task on head and trunk postural sway and discomfort

Adjustable-height desks may provide musculoskeletal health benefits to offset the effects of prolonged sitting. One mechanism may be increased postural variability, here characterized by head and trunk postural sway. Linear acceleration of the head and trunk were measured while participants used computer workstations in seated and standing positions during keyboard and mouse tasks; secondary measures were discomfort and proprioception (head and neck repositioning error). Median accelerations of the head and trunk were 20–26% lower in mouse tasks compared to keyboard tasks (p < 0.01). There were no significant differences in sway parameters between seated and standing positions. Discomfort and proprioception were correlated; subjects who experienced increased neck discomfort after 1.5 h of computer work had almost twice the head and neck repositioning error. The results suggest that postural sway is more affected by different tasks (keyboard vs. mouse) than by different workstation configurations and that low proprioception acuity may relate to the development of discomfort.