Examining the validity and reliability of a portable sleep posture assessment protocol, using infrared cameras, under a variety of light and bed cover situations in the home environment

Deciphering Optimal Radar Ensemble for Advancing Sleep Posture Prediction through Multiview Convolutional Neural Network (MVCNN) Approach Using Spatial Radio Echo Map (SREM)

Assessing sleep posture, a critical component in sleep tests, is crucial for understanding an individual's sleep quality and identifying potential sleep disorders. However, monitoring sleep posture has traditionally posed significant challenges due to factors such as low light conditions and obstructions like blankets. The use of radar technolsogy could be a potential solution. The objective of this study is to identify the optimal quantity and placement of radar sensors to achieve accurate sleep posture estimation. We invited 70 participants to assume nine different sleep postures under blankets of varying thicknesses. This was conducted in a setting equipped with a baseline of eight radars-three positioned at the headboard and five along the side. We proposed a novel technique for generating radar maps, Spatial Radio Echo Map (SREM), designed specifically for data fusion across multiple radars. Sleep posture estimation was conducted using a Multiview Convolutional Neural Network (MVCNN), which serves as the overarching framework for the comparative evaluation of various deep feature extractors, including ResNet-50, EfficientNet-50, DenseNet-121, PHResNet-50, Attention-50, and Swin Transformer. Among these, DenseNet-121 achieved the highest accuracy, scoring 0.534 and 0.804 for nine-class coarse- and four-class fine-grained classification, respectively. This led to further analysis on the optimal ensemble of radars. For the radars positioned at the head, a single left-located radar proved both essential and sufficient, achieving an accuracy of 0.809. When only one central head radar was used, omitting the central side radar and retaining only the three upper-body radars resulted in accuracies of 0.779 and 0.753, respectively. This study established the foundation for determining the optimal sensor configuration in this application, while also exploring the trade-offs between accuracy and the use of fewer sensors.

The Structural Adaptations That Mediate Disuse-Induced Atrophy of Skeletal Muscle

The maintenance of skeletal muscle mass plays a fundamental role in health and issues associated with quality of life. Mechanical signals are one of the most potent regulators of muscle mass, with a decrease in mechanical loading leading to a decrease in muscle mass. This concept has been supported by a plethora of human- and animal-based studies over the past 100 years and has resulted in the commonly used term of 'disuse atrophy'. These same studies have also provided a great deal of insight into the structural adaptations that mediate disuse-induced atrophy. For instance, disuse results in radial atrophy of fascicles, and this is driven, at least in part, by radial atrophy of the muscle fibers. However, the ultrastructural adaptations that mediate these changes remain far from defined. Indeed, even the most basic questions, such as whether the radial atrophy of muscle fibers is driven by the radial atrophy of myofibrils and/or myofibril hypoplasia, have yet to be answered. In this review, we thoroughly summarize what is known about the macroscopic, microscopic, and ultrastructural adaptations that mediated disuse-induced atrophy and highlight some of the major gaps in knowledge that need to be filled.

Examining relationships between sleep posture, waking spinal symptoms and quality of sleep: A cross sectional study

INTRODUCTION

Research with a focus on sleep posture has been conducted in association with sleep pathologies such as insomnia and positional obstructive sleep apnoea. Research examining the potential role sleep posture may have on waking spinal symptoms and quality of sleep is however limited. The aims of this research were to compare sleep posture and sleep quality in participants with and without waking spinal symptoms.

METHODS

Fifty-three participants (36 female) were, based on symptoms, allocated to one of three groups; Control (n = 20, 16 female), Cervical (n = 13, 10 female) and Lumbar (n = 20, 10 female). Participants completed an online survey to collect general information and patient reported outcomes and were videoed over two consecutive nights to determine sleep posture using a validated classification system including intermediate sleep postures.

RESULTS

Participants in the symptomatic groups also reported a lower sleep quality than the Control group. Compared to Control group participants, those in the Cervical group had more frequent posture changes (mean (SD); 18.3(6.5) versus 23.6(6.6)), spent more time in undesirable/provocative sleep postures (median IQR; 83.8(16.4,105.2) versus 185.1(118.0,251.8)) minutes and had more long periods of immobility in a provocative posture, (median IQR: 0.5(0.0,1.5) versus 2.0 (1.5,4.0)). There were no significant differences between the Control and Lumbar groups in the number of posture changes (18.3(6.5) versus 22.9(9.1)) or the time spent in provocative sleep postures (0.5(0.0,1.5) versus 1.5(1.5,3.4)) minutes.

DISCUSSION

This is the first study using a validated objective measure of sleep posture to compare symptomatic and Control group participants sleeping in their home environment. In general, participants with waking spinal symptoms spent more time in provocative sleep postures, and experienced poorer sleep quality.