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Age and gender distribution of cases of CTS confirmed electrically at two locations in the UK (copied from Bland JP, Rudolfer SM. Clinical surveillance of carpal tunnel syndrome in two areas of the United Kingdom, 1991–2001. J Neurol Neurosurg Psychiatry 2003;74:1674–1679).
Source publication
Carpal tunnel syndrome (CTS) is thought to be due to compression of the median nerve in the carpal tunnel. It is known that carpal tunnel pressures are elevated in wrist postures of flexion and extension and in those patients with CTS. Classic symptoms of CTS include night waking with pain, tingling, and numbness. These classic symptoms stimulated...
Contexts in source publication
Context 1
... Gender, and Insomnia There is extensive literature that links age and gender with sleep disturbances [5,26]. Insomnia is more common in women and increases with age, increasing more in women than in men [11]. Figure 1 shows the age and sex distribution of prevalence of insomnia in a large survey in Italy, whereas Fig. 2 shows the age and gender distribution of cases of CTS confirmed electrically at two locations in the UK [7]. There is similarity in gender and age distribution of insomnia and the development of CTS. Both increase with increasing age, both show a bimodal distribution primarily in women, and both are more prevalent in women. Recently, ...
Context 2
... in CTS patients and the prevalence of sleep disorders in the US population. Using the knowledge that wrist position causes increased pressure in the carpal tunnel, we were vigilant for information that could lead to inference about wrist position. Looking closely at the shared relationship of CTS and insomnia with age and gender, as evidenced by Figs. 1 and 2, it became apparent that the relationship was unlikely to be a random event. We could not think of an obvious link to sleep or wrist position or a direct biologic mechanism for insomnia to cause CTS, although at first glance, the opposite could be true. The prevalence of CTS is much less than insomnia, so we felt the direction of this ...
Citations
... In the treatment of CTS, different types of splints that keep the wrist in extension or neutral position can be used. 10 In the literature, it has been reported that the splints used at night could be safe and effective in the treatment of CTS. 11 It is also known that splinting in addition to physical ther apy modalities is more effective in reducing symptoms than nonsplinted approaches. ...
Background
Carpal tunnel syndrome (CTS) is a common musculoskeletal problem in pregnancy. The aim of this study is to compare the effects of rigid and elastic wrist splints on edema, pain levels, grip strength, and upper-extremity functionality in pregnant women with CTS.
Methods
Forty-one pregnant women in the last trimester of pregnancy who were diagnosed with CTS were included in the study. The grip strength was evaluated with the Jamar hand dynamometer, functionality with the Quick Disabilities of the Arm, Shoulder, and Hand and Boston Carpal Tunnel Syndrome Questionnaire, pain with the Visual Analog Scale (VAS), and edema with the water overflow method.
Results
The mean age of the participants was 31.71 ± 5.78 years, body mass index was 28.85 ± 3.63 kg/m ² , duration of pain was 2.24 ± 0.79 months, and their pain intensity was 6.63 ± 1.69 according to the VAS. As a result of the study, reductions in pain ( P = .001), increases in functionality values ( P = .001), increases in grip strength ( P = .001), and decreases in edema ( P = .001) were observed in both groups after the treatment. However, there was no significant difference in pain, functionality, or grip strength values between the groups after the treatment ( P > .05).
Conclusion
In this study comparing the effects of a wrist splint to those of an elastic splint, both treatment methods for pregnant women with CTS decreased pain and edema, increased grip strength, and improved upper-extremity functionality. Considering individual needs, characteristics, and living conditions, both splints can be recommended for pregnant women with CTS.
... CTS is associated also with other less frequently investigated symptoms. One of such these is the disordered sleep associated with pain and paresthesias, which intensify at night due to increased pressure in the carpal tunnel as a result of the prolonged wrist flexion [3]. Another reason pretability [19]. ...
... [10] According to the development of CTS with aging, McCabe et al. reported that incidence increased with age, even it became severe after 59 years. [11] Another study revealed that 45-54 years in males and 55-64 years in females were the highest prevalence of CTS patients. Furthermore, the authors found a bimodal distribution of CTS incidents with age, the highest at age 50-54 years, followed by another peak at age 75-84 years. ...
Objectives
Carpal tunnel syndrome (CTS) generally causes functional disabilities and consequently develops socioeconomic burdens for individuals and our community in the long run. The negative consequences are more recorded in developing nations. Therefore, early addressing the disorder is essential to eliminate the negative impacts on any health-care system.
Methods
This descriptive cross-sectional study was conducted on patients with CTS attending the professorial surgical clinics at Teaching Hospital Jaffna. The demographic and clinical presentation while a self-reported Boston Carpal Tunnel Questionnaire (BCTQ) was used to assess the severity of symptoms and functional status of the wrist and hand.
Results
This study involved 63 respondents whose mean age and body mass index were 55.4 ± 12.4 years and 25.6 ± 3.1, respectively. The larger proportion was female (74.6%) and the majority’s civil status was married (90.5%). Menial and skilled jobs were 46.6% and 31.7%, respectively, whereas the remaining were professionals. The right-hand dominance was 93.7%, although 57.1% had the right hand affected. There was a significant association (r = 0.739 and P = 0.0001) between the clinical tests and the severity of symptoms score.
Conclusion
This study outcomes of CTSs severity and functional status with the BCTQ recommend that this tool and its scales indicate the association between CTSs baseline characteristics and impairments resulting from CTS in the clinical context.
... Incorrect positioning of the wrist causes increased pressure in the carpal tunnel and prolonged pressure on the median nerve. Studies have reported that incorrect positioning during sleep exacerbates CTS symptoms acutely, resulting in nighttime symptoms [23,24]. For this reason, keeping the pressure in the carpal tunnel under control during the night with a correct positioning (splint), we think that it will reduce nighttime symptoms, which will increase the person's daytime functionality and quality of life as well as good sleep quality. ...
Background
Splinting is frequently used in the treatment of CTS (carpal tunnel syndrome) and is mostly preferred at night. On the other hand, there are some studies suggesting the use of splint throughout the day. However, there is still no consensus. The aim of this randomized controlled study was to evaluate the effects of day and night splinting in terms of pain, symptom severity, functional status, and quality of life in patients with CTS.
Results
Seventy wrists of 46 patients with CTS were evaluated. In the day-night splint group, according to without splint group and night-only splint group, a statistically significant improvement was found in terms of pain level assessed by Visual Analogue Scale ( p = 0.001, p = 0.015, respectively), Boston Carpal Tunnel Questionnaire-Functional Severity Scale ( p = 0.004, p = 0.020, respectively), The Nottingham Health Profile-pain ( p = 0.001, p = 0.003, respectively), The Nottingham Health Profile-social isolation ( p = 0.001, p = 0.001, respectively), and The Nottingham Health Profile-total score ( p = 0.001, p = 0.012, respectively). In addition, it was found that even the use of splint only at night resulted in a significant reduction in pain compared to the control group ( p = 0.018).
Conclusions
Continuation of splinting as much as possible during the daytime in addition to night splinting is beneficial in terms of pain, nocturnal symptoms, functionality, and quality of life.
... A confounder is an external independent variable that should meet three requirements: (1) it should be associated with the exposure (or intervention), that is, it must be unequally distributed between exposure groups or intervention and control groups; (2) it should be associated with the effect (disease or outcome) -even in those patients who were not exposed, it must be a risk or protective factor; and (3) it should not be an intermediate variable between the exposure and the effect, that is, the confounder cannot be part of the causal pathway and it should not be a consequence of the exposure. Figure 1 shows an example using hypothetical data from an observational study with a cohort design investigating the association between sleep disturbances and carpal tunnel syndrome (CTS) (McCabe et al., 2007). Based on the crude rate of the effect it can be concluded that the risk of CTS is four times higher in individuals with sleep disturbances than in those without sleep disturbances. ...
Confounding and effect modification are two key epidemiological concepts in clinical research. They influence the association between an exposure and a disease in causation or aetiology studies, or between an intervention and an outcome in treatment effect studies. Although they are different concepts, distinguishing between confounding and effect modification is not always easy. Moreover, a covariate may be a confounder, an effect modifier, or both at the same time.
The purpose of this article is to introduce these epidemiological concepts that may not be familiar in the field of hand surgery and explain how they should be handled in clinical research, focusing on multivariate regression analysis.
... This provides clinicians with an advantageous access to human-interpretable and simplified posture definition alongside the output pose labels. The choice of ankle and wrist joints stems from their strong connection with various sleep-related pathologies, such as ankle osteoarthritis [38] and carpal tunnel syndrome [39]. Such intuitive postural information is envisaged to bring clinicians more comprehensibility of the posture classification algorithm, making it a better fit as a future medical diagnostic tool. ...
Sleep posture is linked to several health conditions such as nocturnal cramps and more serious musculoskeletal issues. However, in-clinic sleep assessments are often limited to vital signs (e.g. brain waves). Wearable sensors with embedded inertial measurement units are used for sleep posture classification; nonetheless, existing works consider only few (commonly four) postures, which are inadequate for advanced clinical assessments. Moreover, posture learning algorithms typically require longitudinal data collection to function reliably, and often operate on raw inertial sensor readings unfamiliar to clinicians. This paper proposes a new framework for sleep posture classification based on a minimal set of joint angle measurements. The proposed framework is validated on a rich set of twelve postures in two experimental pipelines: computer animation to obtain synthetic postural data, and human participant pilot study using custom-made miniature wearable sensors. Through fusing raw geo-inertial sensor measurements to compute a filtered estimate of relative segment orientations across the wrist and ankle joints, the body posture can be characterised in a way comprehensible to medical experts. The proposed sleep posture learning framework offers plug-and-play posture classification by capitalising on a novel kinematic data augmentation method that requires only one training example per posture. Additionally, a new metric together with data visualisations are employed to extract meaningful insights from the postures dataset, capture the added value of the data augmentation method, and lend explainability to the classification performance. The proposed framework attained promising overall accuracy as high as 100% on synthetic data and 92.7% on real data, on par with state of the art data-hungry algorithms available in the literature.
... Compression on the nerve foremost to sensory symptoms such as paresthesia, numbness and pain, motor symptoms such as stiffness, clumsiness and weakness of the hands [14]. Factors that cause the development of Carpal Tunnel Syndrome are, repetitive wrist movements, vigorous contractions in a tendon, a downwardbending (flexed) wrist movement or bending up (extension), hand movement while working (pinching motion), mechanical pressure on the median nerve [9]. Owing to play the stringed instruments needs redundant utilization of muscle usually with helpless stance of gliding joint associated with inflated risk of musculoskeletal disorder. ...
Introduction: Awkward postures of guitarist such as working with the joints near their end range of motion; uneven loading and static muscle activity increase the biomechanics stress on the muscles and the surrounding joint. Carpal tunnel syndrome often results from physical job activities that involve using tools and hand-held vibrating equipment's. This study aimed to predict risk associated with symptoms of carpal tunnel syndrome in picking hand of guitarist. Materials and Method: 100 participants of both gender with age range of 15-35 years from various music academy with experience of more than one year in playing guitar were assessed using the Boston Carpal Tunnel Questionnaire. Results: Mild to moderate risk predicted in picking hand among guitarists on basis of symptom severity and functional status. Conclusion: Proper warm up and cool down exercise, stretches and ergonomic advice must be tackled among the risk population to prevent carpal tunnel syndrome among guitarists in picking hand.
... While sleep aims to relieve the fatigue of muscles and ligaments, a side-lying posture accompanied by poor support may lead to a sagging spine and sinking lumbar, resulting in sleep-related musculoskeletal problems, such as neck and back pain [7][8][9]. Sleep postures and posture changes were also associated with sleep bruxism [10], carpal tunnel syndrome [11], and restless leg syndrome [12]. Additionally, for patients with obstructive sleep apnea, supine and prone postures may affect their respiration because of tongue and palate prolapse and pressure on the thorax [13]. ...
Emerging sleep health technologies will have an impact on monitoring patients with sleep disorders. This study proposes a new deep learning model architecture that improves the under-blanket sleep posture classification accuracy by leveraging the anatomical landmark feature through an attention strategy. The system used an integrated visible light and depth camera. Deep learning models (ResNet-34, EfficientNet B4, and ECA-Net50) were trained using depth images. We compared the models with and without an anatomical landmark coordinate input generated with an open-source pose estimation model using visible image data. We recruited 120 participants to perform seven major sleep postures, namely, the supine posture, prone postures with the head turned left and right, left- and right-sided log postures, and left- and right-sided fetal postures under four blanket conditions, including no blanket, thin, medium, and thick. A data augmentation technique was applied to the blanket conditions. The data were sliced at an 8:2 training-to-testing ratio. The results showed that ECA-Net50 produced the best classification results. Incorporating the anatomical landmark features increased the F1 score of ECA-Net50 from 87.4% to 92.2%. Our findings also suggested that the classification performances of deep learning models guided with features of anatomical landmarks were less affected by the interference of blanket conditions.
... This provides clinicians with an advantageous access to human-interpretable and simplified posture definition alongside the output pose labels. The choice of ankle and wrist joints stems from their strong connection with various sleep-related pathologies, such as ankle osteoarthritis [38] and carpal tunnel syndrome [39]. Such intuitive postural information is envisaged to bring clinicians more comprehensibility of the posture classification algorithm, making it a better fit as a future medical diagnostic tool. ...
Sleep posture is linked to several health conditions such as nocturnal cramps and more serious musculoskeletal issues. However, in-clinic sleep assessments are often limited to vital signs (e.g. brain waves). Wearable sensors with embedded inertial measurement units have been used for sleep posture classification; nonetheless, previous works consider only few (commonly four) postures, which are inadequate for advanced clinical assessments. Moreover, posture learning algorithms typically require longitudinal data collection to function reliably, and often operate on raw inertial sensor readings unfamiliar to clinicians. This paper proposes a new framework for sleep posture classification based on a minimal set of joint angle measurements. The proposed framework is validated on a rich set of twelve postures in two experimental pipelines: computer animation to obtain synthetic postural data, and human participant pilot study using custom-made miniature wearable sensors. Through fusing raw geo-inertial sensor measurements to compute a filtered estimate of relative segment orientations across the wrist and ankle joints, the body posture can be characterised in a way comprehensible to medical experts. The proposed sleep posture learning framework offers plug-and-play posture classification by capitalising on a novel kinematic data augmentation method that requires only one training example per posture. Additionally, a new metric together with data visualisations are employed to extract meaningful insights from the postures dataset, demonstrate the added value of the data augmentation method, and explain the classification performance. The proposed framework attained promising overall accuracy as high as 100% on synthetic data and 92.7% on real data, on par with state of the art data-hungry algorithms available in the literature.
... The insights from this research offer stepping stones towards robust automated privacy-preserving systems that utilize multimodal feature fusion to support the assessment and diagnosis of medical conditions. In-bed human pose estimation has demonstrated its utility for many healthcare applications, including remote patient monitoring and preventing conditions such as carpal tunnel syndrome, pressure ulcers, and sleep apnea [23]. ...
Recently, in-bed human pose estimation has attracted the interest of researchers due to its relevance to a wide range of healthcare applications. Compared to the general problem of human pose estimation, in-bed pose estimation has several inherent challenges, the most prominent being frequent and severe occlusions caused by bedding. In this paper we explore the effective use of images from multiple non-visual and privacy-preserving modalities such as depth, long-wave infrared (LWIR) and pressure maps for the task of in-bed pose estimation in two settings. First, we explore the effective fusion of information from different imaging modalities for better pose estimation. Secondly, we propose a framework that can estimate in-bed pose estimation when visible images are unavailable, and demonstrate the applicability of fusion methods to scenarios where only LWIR images are available. We analyze and demonstrate the effect of fusing features from multiple modalities. For this purpose, we consider four different techniques: 1) Addition, 2) Concatenation, 3) Fusion via learned modal weights, and 4) End-to-end fully trainable approach; with a state-of-the-art pose estimation model. We also evaluate the effect of reconstructing a data-rich modality (i.e., visible modality) from a privacy-preserving modality with data scarcity (i.e., long-wavelength infrared) for in-bed human pose estimation. For reconstruction, we use a conditional generative adversarial network. We conduct ablative studies across different design decisions of our framework. This includes selecting features with different levels of granularity, using different fusion techniques, and varying model parameters. Through extensive evaluations, we demonstrate that our method produces on par or better results compared to the state-of-the-art.
