Sleep Posture Research Articles

Is sleep position associated with glenohumeral shoulder pain and rotator cuff tendinopathy: a cross-sectional study

BackgroundGlenohumeral pain and rotator cuff tendinopathy (RCT) are common musculoskeletal complaints with high prevalence among working populations. The primary proposed pathophysiologic mechanisms are sub-acromial RC tendon impingement and reduced tendon blood flow. Some sleep postures may increase subacromial pressure, potentially contributing to these postulated mechanisms. This study uses a large population of workers to investigate whether there is an association between preferred sleeping position and prevalence of: (1) shoulder pain, and (2) rotator cuff tendinopathy.MethodsA cross-sectional analysis was performed on baseline data from a multicenter prospective cohort study. Participants were 761 workers who were evaluated by questionnaire using a body diagram to determine the presence of glenohumeral pain within 30 days prior to enrollment. The questionnaire also assessed primary and secondary preferred sleep position(s) using 6 labeled diagrams. All workers underwent a structured physical examination to determine whether RCT was present. For this study, the case definition of RCT was glenohumeral pain plus at least one of a positive supraspinatus test, painful arc and/or Neer’s test. Prevalence of glenohumeral pain and RCT were individually calculated for the primary and secondary sleep postures and odds ratios were calculated.ResultsAge, sex, Framingham cardiovascular risk score and BMI had significant associations with glenohumeral pain. For rotator cuff tendinopathy, increasing age, Framingham risk score and Hand Activity Level (HAL) showed significant associations. The sleep position anticipated to have the highest risk of glenohumeral pain and RCT was paradoxically associated with a decreased prevalence of glenohumeral pain and also trended toward being protective for RCT. Multivariable logistic regression showed no further significant associations.ConclusionThis cross-sectional study unexpectedly found a reduced association between one sleep posture and glenohumeral pain. This cross-sectional study may be potentially confounded, by participants who are prone to glenohumeral pain and RCT may have learned to avoid sleeping in the predisposing position. Longitudinal studies are needed to further evaluate a possible association between glenohumeral pain or RCT and sleep posture as a potential risk factor.

Protective effects of REM sleep without atonia against obstructive sleep apnea in patients with idiopathic REM sleep behavior disorder

BackgroundThis study investigated the protective effect of rapid eye movement (REM) sleep without atonia against obstructive sleep apnea (OSA) in patients with idiopathic REM sleep behavior disorder (RBD). MethodsIn this case–control study, patients with idiopathic RBD and OSA (RBD-OSA) were consecutively enrolled and OSA controls without RBD were matched for age, sex, and apnea–hypopnea index (AHI). Clinical and polysomnographic characteristics were compared between RBD-OSA patients and OSA controls. Additionally, differences in AHIs depending on sleep state and posture were analyzed. ResultsIn total, 109 OSA patients (81 males and 28 females) with idiopathic RBD were included in the study. In OSA controls without RBD, AHI and respiratory distress index (RDI) were significantly higher during REM sleep than during non-rapid eye movement (NREM) sleep (p < 0.01). In RBD-OSA patients, however, AHI and RDI were slightly lower during REM sleep than during NREM sleep (p < 0.05). During REM sleep, AHI and RDI were significantly lower in RBD-OSA patients than in OSA controls (p < 0.001). Differences in apnea severity between RBD-OSA patients and OSA controls increased in supine REM sleep but disappeared or lessened in non-supine REM sleep. The prevalence of REM-related OSA was lower in RBD-OSA patients (9.2%) than in OSA controls (33.0%). ConclusionsREM sleep without atonia has protective effects against OSA in patients with idiopathic RBD. These protective effects are much more potent in supine sleep than in non-supine sleep.

Sleeping posture recognition using fuzzy c-means algorithm

BackgroundPressure sensors have been used for sleeping posture detection, which meet privacy requirements. Most of the existing techniques for sleeping posture recognition used force-sensitive resistor (FSR) sensors. However, lower limbs cannot be recognized accurately unless thousands of sensors are deployed on the bedsheet.MethodWe designed a sleeping posture recognition scheme in which FSR sensors were deployed on the upper part of the bedsheet to record the pressure distribution of the upper body. In addition, an infrared array sensor was deployed to collect data for the lower body. Posture recognition was performed using a fuzzy c-means clustering algorithm. Six types of sleeping body posture were recognized from the combination of the upper and lower body postures.ResultsThe experimental results showed that the proposed method achieved an accuracy of above 88%. Moreover, the proposed scheme is cost-efficient and easy to deploy.ConclusionsThe proposed sleeping posture recognition system can be used for pressure ulcer prevention and sleep quality assessment. Compared to wearable sensors and cameras, FSR sensors and infrared array sensors are unobstructed and meet privacy requirements. Moreover, the proposed method provides a cost-effective solution for the recognition of sleeping posture.

Effects of sleep body posture on subjective sleepiness in patients with OSAHS

Objective:To observe the effects of sleep body posture on subjective sleepiness in patients with OSAHS.Method: We assessed the sleeping body position, the sleep structure, position specific AHI and the Epworth Sleepiness Scale (ESS) in a total of 90 patients with OSAHS. The patients were grouped according to AHI: mild OSAHS (5≤AHI<15), moderate (15≤AHI<30) and severe (AHI≥30). The polysomnography data and clinical characteristics were compared between each group.Result: There was statistically significant difference in arousal index，MinSpO2，REM% and NREM% among three groups (F value was 12.10,43.67,15.81,13.17，respectively，P<0.05). Compared with supine，the severe OSAHS group had significantly bigger changes in MinSpO2， REM% and NREM%（t value was 3.02,2.41,2.90，respectively，P<0.05）. For mild-to-moderate groups，there was no correlation between the ESS and the AHI at any position（P>0.05）. For severe group，the ESS was significantly correlated with L-AHI（r=0.454，P<0.01)；the REM L-AHI and NREM L-AHI was also significantly correlated with ESS of severe group (r=0.522 and 0.425，P<0.01). Conclusion:The sleep body posture had significant effects on sleep structure and respiratory events in severe OSAHS group. The L-AHI was found to have a closer association with daytime sleepiness in severe OSAHS than other groups.

Sleep Posture Classification using a Convolutional Neural Network.

Sleep is a process of rest and renewal that is vital for humans. However, there are several sleep disorders such as rapid eye movement (REM) sleep behaviour disorder (RBD), sleep apnea, and restless leg syndrome (RLS) that can have an impact on a significant portion of the population. These disorders are known to be associated with particular behaviours such as specific body positions and movements. Clinical diagnosis requires patients to undergo polysomnography (PSG) in a sleep unit as a gold standard assessment. This involves attaching multiple electrodes to the head and body. In this experiment, we seek to develop non-contact approach to measure sleep disorders related to body postures and movement. An Infrared (IR) camera is used to monitor body position unaided by other sensors. Twelve participants were asked to adopt and then move through a set of 12 pre-defined sleep positions. We then adopted convolutional neural networks (CNNs) for automatic feature generation from IR data for classifying different sleep postures. The results show that the proposed method has an accuracy of between 0.76 & 0.91 across the participants and 12 sleepposes with, and without a blanket cover, respectively. The results suggest that this approach is a promising method to detect common sleep postures and potentially characterise sleep disorder behaviours.

A lightweight sensing platform for monitoring sleep quality and posture: a simulated validation study

BackgroundThe prevalence of self-reported shoulder pain in the UK has been estimated at 16%. This has been linked with significant sleep disturbance. It is possible that this relationship is bidirectional, with both symptoms capable of causing the other. Within the field of sleep monitoring, there is a requirement for a mobile and unobtrusive device capable of monitoring sleep posture and quality. This study investigates the feasibility of a wearable sleep system (WSS) in accurately detecting sleeping posture and physical activity.MethodsSixteen healthy subjects were recruited and fitted with three wearable inertial sensors on the trunk and forearms. Ten participants were entered into a ‘Posture’ protocol; assuming a series of common sleeping postures in a simulated bedroom. Five participants completed an ‘Activity’ protocol, in which a triphasic simulated sleep was performed including awake, sleep and REM phases. A combined sleep posture and activity protocol was then conducted as a ‘Proof of Concept’ model. Data were used to train a posture detection algorithm, and added to activity to predict sleep phase. Classification accuracy of the WSS was measured during the simulations.ResultsThe WSS was found to have an overall accuracy of 99.5% in detection of four major postures, and 92.5% in the detection of eight minor postures. Prediction of sleep phase using activity measurements was accurate in 97.3% of the simulations. The ability of the system to accurately detect both posture and activity enabled the design of a conceptual layout for a user-friendly tablet application.ConclusionsThe study presents a pervasive wearable sensor platform, which can accurately detect both sleeping posture and activity in non-specialised environments. The extent and accuracy of sleep metrics available advances the current state-of-the-art technology. This has potential diagnostic implications in musculoskeletal pathology and with the addition of alerts may provide therapeutic value in a range of areas including the prevention of pressure sores.

A novel depth image analysis for sleep posture estimation

Recognition of sleep posture and its changes are related to information monitoring in a number of health-related applications such as apnea prevention and elderly care. This paper uses a less privacy-invading approach to classify sleep postures of a person in various configurations including side and supine postures. In order to accomplish this, a single depth sensor has been utilized to collect selective depth signals and populated a dataset associated with the depth data. The data is then analyzed by a novel frequency-based feature selection approach. These extracted features were then correlated in order to rank their information content in various 2D scans from the 3D point cloud in order to train a support vector machine (SVM). The data of subjects are collected under two conditions. First when they were covered with a thin blanket and second without any blanket. In order to reduce the dimensionality of the feature space, a T-test approach is employed to determine the most dominant set of features in the frequency domain. The proposed recognition approach based on the frequency domain is also compared with an approach using feature vector defined based on skeleton joints. The comparative studies are performed given various scenarios and by a variety of datasets. Through our study, it is shown that our proposed method offers better performance to that of the joint-based method.

The change of sleeping and lying posture of Japanese black cows after moving into new environment.

ObjectiveEnvironmental change is one of the stressful events in livestock production. Change in environment disturbs cow behavior and cows require several days to regain a stable behavioral pattern. Sleeping posture (SP) and lying posture (LP) have been used as indicators for animal that are relaxed and well-acclimated to their environment. The aim of this study was to examine the time required by Japanese black cows for stabilization of SP and LP after moving into new environment.MethodsSeven pregnant Japanese black cows were used. Cows were moved into new tie-stall shed and their sleeping and lying posture measured 17 times during 35 experimental days. Both SP and LP were detected by accelerometer fixed on middle occipital and hip-cross, respectively. Daily total time, frequency, and average bout of both SP and LP were calculated.ResultsDaily SP time was the shortest on day 1 and increased to the highest on day 3. It then decreased until day 9, after that stabilized about 65 min/d till the end of experiment. Daily LP time changed in same manner as daily SP time. The average SP bout was the longest on day 1, and then decreased to stable level on day 7. On the other hand, the average LP bout was the shortest on day 1, and it increased to stable level on day 7.ConclusionThese results showed that pregnant Japanese black cows needed 1 week to stabilize their SP. However, there were different change patterns between the average SP and LP bout, even though the change pattern of daily SP and LP time were similar.

Detection of Cardiopulmonary Activity and Related Abnormal Events Using Microsoft Kinect Sensor.

Monitoring of cardiopulmonary activity is a challenge when attempted under adverse conditions, including different sleeping postures, environmental settings, and an unclear region of interest (ROI). This study proposes an efficient remote imaging system based on a Microsoft Kinect v2 sensor for the observation of cardiopulmonary-signal-and-detection-related abnormal cardiopulmonary events (e.g., tachycardia, bradycardia, tachypnea, bradypnea, and central apnoea) in many possible sleeping postures within varying environmental settings including in total darkness and whether the subject is covered by a blanket or not. The proposed system extracts the signal from the abdominal-thoracic region where cardiopulmonary activity is most pronounced, using a real-time image sequence captured by Kinect v2 sensor. The proposed system shows promising results in any sleep posture, regardless of illumination conditions and unclear ROI even in the presence of a blanket, whilst being reliable, safe, and cost-effective.

Volumetric reconstruction of thermal-depth fused 3D models for occluded body posture estimation

Abstract Reliable and effective occluded skeletal posture estimation is a challenging problem for vision-based modalities that do not provide inter-surface imaging. These include both visible-light and depth-based devices that all existing pose estimation techniques are derived from. This fundamental limitation in skeletal tracking is due to the inability of these techniques to penetrate occluding surface materials to derive joint configurations that are not directly visible to the camera. In this work, we present a new method of estimating skeletal posture in occluded applications using both depth and thermal imaging through volumetric modeling and introduce a new occluded ground-truth tracking method inspired by modern motion capture solutions for tracking occluded joint positions. Using this integrated volumetric model, we utilize Convolutional Neural Networks to characterize and identify volumetric thermal distributions that match trained skeletal posture estimates which includes disconnected skeletal definitions and allows correct posture estimation in highly ambiguous cases. We demonstrate this approach by accurately identifying common sleep postures that present challenging cases for current skeletal joint estimation techniques and evaluate the use of volumetric thermal models for various sleep-study related applications.

Cortical beta EEG oscillations related to changes in muscle tone activity during sleep in spider monkey (Ateles geoffroyi).

The physiological mechanisms that allow for sleeping in a vertical position, which is primordial for arboreal primates, have not been studied yet. A non-invasive polysomnographic study of 6 spider monkeys (Ateles geoffroyi) was conducted. The relative beta power of the motor cortex and its linear relation with muscle tone in the facial mentalis muscle and the abductor caudae medialis muscle of the tail during wakefulness and sleep stages were calculated. A strong negative linear relationship (r=-.8, P=.03) was found between the relative power of the beta2 band in the left motor cortex and abductor caudae medialis muscle tone during delta sleep. The left motor cortex, through beta2 band activity, interacts with abductor caudae medialis muscle tonicity during delta sleep. This interaction takes part in the mechanisms that regulate the sleep postures.

A clinical analysis of 101 infants with plagiocephaly

To investigate the possible causes of plagiocephaly in infants and the therapeutic effect of postural correction training on plagiocephaly. A total of 101 infants who were diagnosed with plagiocephaly were enrolled. According to the age at diagnosis, these infants were divided into 1-4 month group (31 infants), 5-8 month group (40 infants), and 9-12 month group (30 infants). The possible causes of plagiocephaly were analyzed in three groups. The cranial vault asymmetry index (CVAI) before and after postural correction training was compared in three groups. Of the 101 infants, 89 (88.1%) had a sleeping posture in the supine position, and there was no significant difference in the percentage of infants with such posture between the three groups. Compared with the 5-8 month group and the 9-12 month group, the 1-4 month group had significantly higher rate of preterm birth, incidence rate of adverse perinatal factors, and incidence rate of congenital muscular torticollis. The three groups showed a significant decrease in CVAI 3 months after postural correction training (P<0.001). Compared with the 5-8 month group and the 9-12 month group, the 1-4 month group had a significantly greater change in CVAI after postural correction training (P<0.001). The sleeping posture in the supine position may be associated with the development of plagiocephaly. Adverse perinatal factors, preterm birth, and congenital muscular torticollis as possible causes of plagiocephaly are commonly seen in early infancy. Postural correction training has a significant effect in improving plagiocephaly, especially in early infancy.

A nationwide, cross-sectional survey on unusual sleep postures and sleep-disordered breathing-related symptoms in people with Down syndrome.

People with Down syndrome (DS) often have sleep-disordered breathing (SDB). Unusual sleep postures, such as leaning forward and sitting, are observed in people with DS. This study aimed to clarify the prevalence of unusual sleep postures and their relationships with SDB-related symptoms (SDB-RSs), such as snoring, witnessed apnoea, nocturnal awakening and excessive daytime sleepiness. A questionnaire, including demographic characteristics and the presence of unusual sleep postures, as well as SDB-RSs, was completed by 1149 parents of people with DS from Japan. Unusual sleep postures were recorded in 483 (42.0%) people with DS. These participants were significantly younger and had a history of low muscle tone more frequently than people without unusual sleep postures. In all ages, the leaning forward posture was more frequent than sitting. People with DS with unusual sleep postures suffered from SDB-RSs. Those who slept in the sitting posture had more frequent SDB-RSs than did those who slept with the leaning forward posture. Snoring, witnessed apnoea and nocturnal awakening were observed in 73.6, 27.2 and 58.2% of participants, respectively. Snoring increased with aging. Witnessed apnoea was more common in males and in those with hypothyroidism than in females and in those without hypothyroidism. Our study shows that there is a close relationship between unusual sleep postures and SDB-RSs. We recommend that all people with DS with unusual sleep postures should be checked for the presence of SDB.

Activity Monitoring and Heart Rate Variability as Indicators of Fall Risk: Proof-of-Concept for Application of Wearable Sensors in the Acute Care Setting.

Growing concern for falls in acute care settings could be addressed with objective evaluation of fall risk. The current proof-of-concept study evaluated the feasibility of using a chest-worn sensor during hospitalization to determine fall risk. Physical activity and heart rate variability (HRV) of 31 volunteers admitted to a 29-bed adult inpatient unit were recorded using a single chest-worn sensor. Sensor data during the first 24-hour recording were analyzed. Participants were stratified using the Hendrich II fall risk assessment into high and low fall risk groups. Univariate analysis revealed age, daytime activity, nighttime side lying posture, and HRV were significantly different between groups. Results suggest feasibility of wearable technology to consciously monitor physical activity, sleep postures, and HRV as potential markers of fall risk in the acute care setting. Further study is warranted to confirm the results and examine the efficacy of the proposed wearable technology to manage falls in hospitals. [Journal of Gerontological Nursing, 43(7), 53-62.].

Sleep comfort analysis using a part-based mixture model with nighttime infrared video

This work investigated a new challenging problem: how to analyze human sleep comfort which is an urgent problem in intelligent home and medical supervision, especially in intelligent temperature control of air conditioners. To overcome this problem, a novel part-based mixture model is proposed to estimate human sleep comfort. Unlike conventional human sleep comfort analysis using uncomfortable and expensive wearable-device, a remote infrared camera and a cheap temperature sensor are used to collect human sleep posture and real-time temperature information. Moreover, a robust sleep posture feature extraction method is firstly proposed to describe sleep comfort not matter human body is covered by a sheet or not. Experiments on a custom-made database demonstrated that the proposed method has promising performance for on-line human sleep comfort analysis.

Effect of Local Cooling on Thermal Comfort of People in a Sleeping Posture

Local cooling has been shown to have the potential to adjust human thermal comfort. Previous studies on local cooling are mainly conducted with subjects in sitting posture. When in a sleeping posture, the distribution of blood flow and the contact area between human body and the environment are different. In this study, the effects of local cooling on thermal comfort were investigated when people in a sleeping posture in a 30℃ environment. Thirty-six healthy adults participated into this experiment. Local cooling was applied to five parts, including the head-and-neck part, chest-and-abdomen part, upper arm, back and thigh, each for 10 min. The cooling conditions were separated by 30 min of ‘no-cooling’. Thermal sensation and thermal comfort were evaluated with visual analog scales. Physiological parameter (skin temperature) was measured during the exposure. The results show that: when people in sleeping posture, local cooling of the back is an effective way to improve thermal sensation and thermal comfort. Thus back is recommended to be selected as the exposure part when the effect of local conductive cooling on sleep quality and thermal comfort in a hot environment are studied.

A Respiration-Derived Posture Method Based on Dual-Channel Respiration Impedance Signals

Sleep posture has been used as a sleep assessment indicator in home health monitoring and clinical monitoring in recent years. Considering comfort and usability, unobtrusive sleep posture detection is needed. In this paper, we proposed a novel sleep respiration-derived posture (RDP) method based on left and right lung respiration impedance signals. We developed a dual-channel respiratory impedance acquisition system with wireless transmission. Then, support vector machine using radial basis function kernel was applied to recognize four typical sleep postures. Moreover, the performance of the SVM classifier was improved by using backward elimination. In-situ experiments with 16 subjects indicated that the RDP method reached an accuracy of 99.67%. Thus, our method is reliable in sleep posture recognition. Furthermore, a whole-night monitoring system based on respiration impedance can be conducted for sleep quality assessment.

Effect of sleep posture on neck muscle activity.

[Purpose] This study investigated the effect of sleep posture on neck muscle activity. [Subjects and Methods] The study recruited 20 healthy subjects, who were positioned in three supine sleeping positions: both hands at sides, both hands on the chest, and dominant hand on the forehead. The activities of the scalene and upper trapezius muscles bilaterally were measured by surface electromyography. [Results] The upper trapezius and scalene muscle activity on the right side was significantly greater in the supine with dominant hand on the forehead position than in the other positions. [Conclusion] Sleep posture is important and prevent neck and shoulder musculoskeletal pain.

Obstructive Sleep Apnoea: Therapeutic Options and Challenges

Obstructive sleep apnoea (OSA) is a common sleep disorder that is associated with significant negative health outcomes including cardiovascular disease, daytime sleepiness, neurocognitive deficits, and increased motor vehicle and workplace accidents. There is wide variation in OSA symptoms and other downstream effects between patients highlighting the need to individualise therapy. Continuous positive airway pressure delivered by a face mask is the gold standard treatment, but adherence to this therapy is poor and improvements in outcomes are often incomplete. A range of alternative treatments are available and may suit different patients. These include behavioural treatments such as weight loss, mandibular advancement using an oral device, sleep posture modification, upper airway surgery, and upper airway muscle stimulation. Towards individualised OSA therapy, novel phenotyping approaches are being developed to identify the specific pathophysiological causes of OSA applying to individual patients. Furthe...

Effects of Mattress Material on Body Pressure Profiles in Different Sleeping Postures

ObjectivesThis study compared the body contact pressure profiles of 2 types of mattresses: latex and polyurethane. MethodsTwenty participants were required to lie down on the different mattresses in 3 different postures for 6 minutes, and their body contact pressure profiles were recorded with a pressure mat sensor. ResultsThe data indicated that the latex mattress was able to reduce the peak body pressure on the torso and buttocks and achieve a higher proportion of low-pressure regions compared with the polyurethane mattress. ConclusionsLatex mattress reduced peak body pressure and achieved a more even distribution of pressure compared with polyurethane mattress across different sleeping postures.