Posture Monitoring During Breastfeeding: Smart Underwear Integrated with an Accelerometer and Flexible Sensors.

The position that a woman adopts during breastfeeding is important for both infant and maternal health; however, many women experience musculoskeletal pain due to poor posture during breastfeeding, which is a known factor in low exclusive breastfeeding rates. Posture monitoring is an effective intervention, but existing wearable devices do not consider the ergonomics of nursing mothers and breastfeeding scenarios. In this study, nursing underwear was developed with posture monitoring and a real-time feedback system using accelerometers and flexible bending sensors targeting the neck and upper thoracic spine.

Health status monitoring of bridge cable and telescopic compensation device based on fiber grating sensing array.

Laying power cables along the bridge is a new way of laying submarine cables across the sea. Monitoring the health status of cables and their telescopic compensation devices is necessary. In this study, fiber grating sensing technology was used to monitor the strain, temperature, and vibration of the bridge cable of the Zhoushan-Daishan Bridge in Zhoushan, Zhejiang Province, and its compensation device.

Electromyographic Discrepancy in Paravertebral Muscle Activity Predicts Early Curve Progression of Untreated Adolescent Idiopathic Scoliosis.

Study Design: This study adopted a prospective cohort study design.

Purpose: This study aimed to examine electromyogram (EMG) discrepancy in paravertebral muscle activity and scoliosis progression, determine how vertebral morphology and EMG discrepancy evolve during scoliosis progression, and identify differences in EMG activity between individuals with and without adolescent idiopathic scoliosis (AIS).

Overview Of Literature: Higher EMG activity is observed in the convex side of scoliotic curves, but not in populations without scoliosis, suggesting that higher EMG activity is a causative factor for curve progression.

A Neural Network Approach for Inertial Measurement Unit-Based Estimation of Three-Dimensional Spinal Curvature.

The spine is an important part of the human body. Thus, its curvature and shape are closely monitored, and treatment is required if abnormalities are detected. However, the current method of spinal examination mostly relies on two-dimensional static imaging, which does not provide real-time information on dynamic spinal behaviour.

A Systematic Analysis of 3D Deformation of Aging Breasts Based on Artificial Neural Networks.

The measurement and prediction of breast skin deformation are key research directions in health-related research areas, such as cosmetic and reconstructive surgery and sports biomechanics. However, few studies have provided a systematic analysis on the deformations of aging breasts. Thus, this study has developed a model order reduction approach to predict the real-time strain of the breast skin of seniors during movement.

Energy-efficient workload allocation in edge-cloud fiber-wireless networks.

In order to realize the green computing of the edge-cloud fiber-wireless networks, the cooperation between the edge servers and the cloud servers is particularly important to reduce the network energy consumption. Therefore, this paper proposes an energy-efficient workload allocation (EEWA) scheme to improve the energy efficiency by using the architecture of edge-cloud fiber-wireless networks. The feasibility of the proposed EEWA scheme was verified on our SDN testbed.

Electromyographic Analysis of Paraspinal Muscles of Scoliosis Patients Using Machine Learning Approaches.

A large number of studies have used electromyography (EMG) to measure the paraspinal muscle activity of adolescents with idiopathic scoliosis. However, investigations on the features of these muscles are very limited even though the information is useful for evaluating the effectiveness of various types of interventions, such as scoliosis-specific exercises. The aim of this cross-sectional study is to investigate the characteristics of participants with imbalanced muscle activity and the relationships among 13 features (physical features and EMG signal value).