Evaluation Of Sleep Quality Research Articles

Evaluation of peripheral muscle strength, behavior and sleep quality in women’s amateur basketball

Evaluation of peripheral muscle strength, behavior and sleep quality in women’s amateur basketball

Evaluation of sleep quality of mothers of children diagnosed with food allergy

Evaluation of sleep quality of mothers of children diagnosed with food allergy

Associação entre o risco de cronificação de sintomas musculoesqueléticos e a qualidade do sono em Bombeiros Militares no Distrito Federal

Abstract Musculoskeletal symptoms (MS) can derive from injuries or dysfunctions that affect biological tissues such as muscles, bones, and nerves, among others. Military Firefighters (MF) exercise their activities exposed to varied and complex biological conditions, in which the physical demands are intense. Shift work is another remarkable characteristic of the career, which is associated with sleep disorders. Our objective was to estimate the association between the risk of chronification of MS and sleep quality in MF with MS. Our study is a Cross-Sectional Observational Study, whose sample was composed of 753 BM from the Federal District. The analysis was performed with a Sample Characterization Questionnaire, Örebro Musculoskeletal Symptoms Screening Questionnaire (OMPSQ) and the Pittsburgh Sleep Quality Index (PSQI), answered remotely. Statistical analysis used the Spearman Correlation test, p<0.05. The correlation between OMPSQ and PSQI was rated moderate, demonstrating that sleep quality has an influence on the chronification process. The average of the evaluation of Sleep Quality through the PSQI is 8.79, indicating that military personnel present a deficient quality of sleep. There was a correlation between the PSQI score and the OMPSQ of 0.542 (p<0.001), a moderate correlation between the variables. We conclude that MF show correlation between SM and sleep quality, indicating a moderate relationship between the variables, where sleep quality explains 25% of SM. We found that most MF were classified as Low Risk for chronification of SM.

A Temporal-Spectral Fused and Attention-based Deep Model for Automatic Sleep Staging.

Sleep staging is a vital process for evaluating sleep quality and diagnosing sleep-related diseases. Most of the existing automatic sleep staging methods focus on time-domain information and often ignore the transformation relationship between sleep stages. To deal with the above problems, we propose a Temporal-Spectral fused and Attention-based deep neural Network model (TSA-Net) for automatic sleep staging, using a single-channel electroencephalogram (EEG) signal. The TSA-Net is composed of a two-stream feature extractor, feature context learning, and conditional random field (CRF). Specifically, the two-stream feature extractor module can automatically extract and fuse EEG features from time and frequency domains, considering that both temporal and spectral features can provide abundant distinguishing information for sleep staging. Subsequently, the feature context learning module learns the dependencies between features using the multi-head self-attention mechanism and outputs a preliminary sleep stage. Finally, the CRF module further applies transition rules to improve classification performance. We evaluate our model on two public datasets, Sleep-EDF-20 and Sleep-EDF-78. In terms of accuracy, the TSA-Net achieves 86.64% and 82.21% on the Fpz-Cz channel, respectively. The experimental results illustrate that our TSA-Net can optimize the performance of sleep staging and achieve better staging performance than state-of-the-art methods.

Objective Sleep Quality Measurement based on Fuzzy Logic and Wearable Device

Sleep is the natural state of relaxation for human being. Sleep quality is an essential yet frequently neglected aspect of sleep in general. Sleep quality is essential because it allows the body to restore itself and prepare for the next day. The standard method for evaluating sleep quality was subjective evaluation. Actigraphy devices, which can measure the sleep cycle, are now widely available. This study developed a method using Fuzzy Logic and an actigraphy device to measure and classify sleep quality. The fuzzy logic method was developed in several stages, which are determining the sleep quality measurement parameters, constructing the fuzzy set for each input variable, and developing the fuzzy rules. To evaluate the proposed fuzzy model, five individuals were invited to participate in the experiment and required to complete the PSQI subjective sleep questionnaire. The evaluation result shows that our proposed Fuzzy model achieves lower error compared to the existing method.

Sleep Quality Evaluation Based on Single-Lead Wearable Cardiac Cycle Acquisition Device.

In clinical conditions, polysomnography (PSG) is regarded as the "golden standard" for detecting sleep disease and offering a reference of objective sleep quality. For healthy adults, scores from sleep questionnaires are more reliable than other methods in obtaining knowledge of subjective sleep quality. In practice, the need to simplify PSG to obtain subjective sleep quality by recording a few channels of physiological signals such as single-lead electrocardiogram (ECG) or photoplethysmography (PPG) signal is still very urgent. This study provided a two-step method to differentiate sleep quality into "good sleep" and "poor sleep" based on the single-lead wearable cardiac cycle data, with the comparison of the subjective sleep questionnaire score. First, heart rate variability (HRV) features and ECG-derived respiration features were extracted to construct a sleep staging model (wakefulness (W), rapid eye movement (REM), light sleep (N1&N2) and deep sleep (N3)) using the multi-classifier fusion method. Then, features extracted from the sleep staging results were used to construct a sleep quality evaluation model, i.e., classifying the sleep quality as good and poor. The accuracy of the sleep staging model, tested on the international public database, was 0.661 and 0.659 in Cardiology Challenge 2018 training database and Sleep Heart Health Study Visit 1 database, respectively. The accuracy of the sleep quality evaluation model was 0.786 for our recording subjects, with an average F1-score of 0.771. The proposed sleep staging model and sleep quality evaluation model only requires one channel of wearable cardiac cycle signal. It is very easy to transplant to portable devices, which facilitates daily sleep health monitoring.

Association between smartphone overdependency and mental health in Korean adolescents during the COVID pandemic; Age-and gender-matched study.

This study aimed to examine the relationship between smartphone dependency (SD) and mental health (MH) in adolescents in order to develop and implement plans pertaining to SD control. Raw data from the 16th Online Adolescent Health Behavior Survey in 2020 were analyzed. A total of 482 respondents were selected as study subjects based on their experience of smartphone overdependence (SO), specifically, 241 participants whose score for SO was 37 or higher (Group 2) and age- and gender-matched 241 participants whose score was lower than 10 (Group 1). Frequency analysis, cross-tab analysis (χ2 test), and multinomial logistic regression were performed Analysis shows that the MH affecting the increase in SO is the subjective perception of happiness, subjective perception of stress, sadness and despair, and experience of Loneliness. But, the variable affecting the reduction is the subjective evaluation of sleep quality. The likelihood of SO increased as adolescents felt unhappier [Exp (β) = 2.408] and more stressed [Exp (β) = 4.453] and more often felt lonely [Exp (β) = 8.149], but the likelihood decreased as they had neither sufficient nor insufficient sleep duration [Exp (β) = 0.344]. The findings suggest that it is necessary to develop aggressive measures for the prevention and management of MH in adolescents showing SO because mental health is closely linked to SD. In developing the measures, realistic approaches to widely pervasive SO among adolescents should be explored by taking into account MH factors, that is, predictors of SO, and the characteristics of youths, such that they can self-control smartphone use and form desirable life habits.

Sleep quality evaluation, correlation with headache frequency, and propensity to conversion from episodic to chronic daily headache in migraine patients: A cross-sectional study.

The aim of the study was to determine the association between sleep quality with headache frequency in migraine patients and also to evaluate migraine trigger and non-headache symptoms in episodic and chronic migraine groups and evaluation of the same in poor and good sleepers (GSs) in migraine population. In a cross-sectional and observational study in a tertiary care hospital of East India between January 2018 and September 2020, migraine patients were evaluated. Migraine patients were divided into two groups: Episodic migraine (EM) and chronic migraine (CM) group according to ICHD 3 b classification and into poor sleepers (PSs, Global Pittsburgh Sleep Quality Index [PSQI] >5) and GSs (Global PSQI ≤5). Sleep was evaluated using PQSI - a self-rated questionnaire and disease pattern, associated non-headache symptoms, and triggers were evaluated in between groups. Demographic, headache character, and sleep parameters including seven "component" scores: Subjective sleep quality, sleep latency, sleeps duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction and global PQSI were compared between groups (EM and CM). Similar parameters were also compared between PSs and GSs group. Statistical analysis was performed using the χ2 test for categorical variables and the t-test and Wilcoxon rank-sum test for continuous variables. Correlation between two normally distributed numerical was tested by Pearson correlation coefficient assessment. One hundred migraine patients were analyzed, among which 57 were PSs and 43 were GSs and 51 patients had EM and 49 patients had CM. Moderately significant "r" value noted in between headache frequency and global PQSI score (r = 0.45, P < 0.01). In non-headache symptoms, blurring of vision (EM 8 [16%] and CM 16 [33%] P = 0.05), nasal congestion (EM - 3 [6%] and CM - 12 [24%], P = 0.01), and cervical muscle tenderness (EM- 23 [45%] and CM - 34 [69%], P = 0.01) were more prevalent in chronic headache group along with allodynia (EM - 11 [22%] and CM - 25 [51%], P < 0.01). Chronic headache group had poor subjective sleep quality, increased sleep latency, decreased sleep duration, decreased sleep efficiency, and increased sleep disturbance in comparison to episodic group which has therapeutic implication. The non-headache symptoms which are more prevalent in CM patients increase the overall disability.

Evaluation of chronotype and sleep quality in infertile population and comparison with fertile population: a cross-sectional study

Purpose Infertility is a stressful condition for couples and can affect patients’ circadian rhythm and sleep quality. The goal of this study is to assess differences in chronotype and sleep quality between infertile and fertile people. Methods A cross-sectional study was conducted. The infertile patient population consisted study group. Primiparous patients without any known gynecological disease who presented for routine cervical cancer screening follow-up were included in the control group. The Turkish version of the Morningness-Eveningness Questionnaire (MEQ) and Pittsburg Sleep Quality Index (PSQI) scores were evaluated between groups. Results A total of 227 patients were assessed. There were 110 patients in the study (infertile) group and 117 patients in the control (fertile) group. The evening chronotype proportion (23.6 vs. 0.9%, p < 0.001) was higher in the infertile group. The median of MEQ score was significantly higher in the fertile patients (50, IQR = 43 − 55 vs. 56, IQR = 51 − 59; p < 0.001), and the median of PSQI score was significantly higher in the infertile patients (5, IQR = 4 − 6, vs. 4, IQR = 3 − 5; p < 0.001). Conclusions In this study, we found significantly worse sleep quality, and more evening chronotype in the patients with infertility.

Global psychological assessment with the evaluation of life and sleep quality and sexual and cognitive function in a large number of patients with acromegaly: a cross-sectional study.

Acromegaly is associated with somatic disfigurements which impair self-perception of well-being and quality of life. Nowadays, limited data are available on the interplay between hormonal excess and psychological discomfort. The study aimed at investigating the psychological profile, sleep quality, sexual function, cognitive functions, and quality of life in patients with acromegaly. In 223 acromegaly patients from 5 referral centres, global psychological profile, sleep quality, sexual function, cognitive function, and quality of life were investigated. Depression was found in ~30% of patients, and anxiety in two-thirds, together with severe discomfort in body image mainly in women. Obstructive sleep apnoea syndrome risk and sleep disorders were found in >50% of patients and daily sleepiness in ~20%. Sexual dysfunction was reported in most of the patients, with the most severe impairment in women. Cognitive functions were compromised in ~10% of cases. Disease duration and patient's age and gender were the main determinants of these psychopathological conditions. Depression (P = 0.047), somatic-affective mood lowering (P = 0.021), state (P < 0.001) and trait (P = 0.013) anxiety, and body image distortion in body uneasiness test A (P < 0.001) and B (P = 0.006) were significantly worsened in patients <45 years and slightly worsened in those with disease duration less than 2 years. Male (P < 0.001) and female (P < 0.001) sexual function scores were significantly worsened in patients aged >64 years and slightly worsened in those with disease duration for more than 10 years, particularly in presence of cardiometabolic and respiratory complications. Cognitive symptoms were slightly worsened in older patients and in those with long disease duration. Acromegaly is associated with a relevant impairment of psychological profile persisting despite remission and long-term medical treatment.

Worse objective and subjective sleep‐wake metrics are associated with locus coeruleus hypopigmentation: a retrospective post‐mortem study

AbstractBackgroundThe brainstem locus coeruleus (LC) was recently put forward as a key nucleus to connect early sleep‐wake disruption and Alzheimer’s disease (AD) pathophysiological processes. Here, we sought to investigate the relationships between post‐mortem LC hypopigmentation, reflecting LC neurodegeneration, and retrospective subjective/objective sleep‐wake regulation metrics in two longitudinal datasets.MethodLC pigmentation ratings were extracted from autopsy data across 517 Rush Memory and Aging Project (MAP) and 637 National Alzheimer’s Coordinating Center (NACC) cases. Actigraphy‐derived intradaily variability, an objective measure of rest‐activity rhythm fragmentation, was obtained in the MAP dataset, and subjective evaluations of sleep quality were retrieved from the NACC cohort. For both studies, sleep‐wake measures were extracted at the furthest and closest available time points, on average 6.8 y. and 2.5 y. before death, respectively. Logistic regressions adjusted for age at death, sex, race, and post‐mortem interval were used to assess whether sleep‐wake variables could predict post‐mortem LC pigmentation ratings. In the next step, additional models including AD‐related variables of APOE genotype and cortical neuropathology (amyloid‐beta and tau burden) were further performed to test for independence in the relationships between sleep‐wake measures and LC pigmentation.ResultsIn the MAP cohort, higher rest‐activity rhythm fragmentation at both time points was significantly associated with greater odds of LC hypopigmentation at autopsy (Table 1). In models considering additional AD‐related variables, these relationships remained significant independently of the effects of APOE and cortical AD neuropathology (Table 1). In the NACC dataset, worse subjective sleep quality at the closest time point, but not at the furthest, was significantly linked to greater odds of LC hypopigmentation at autopsy (Table 2). Likewise, additional models indicated that this relationship is independent of APOE and cortical AD neuropathology (Table 2).ConclusionThese findings highlight the utility of evaluating sleep and wakefulness, especially with objective measurements, to predict LC neurodegenerative processes in older populations, as far as 6.8 years before death and beyond the effects of APOE genotype and cortical AD neuropathology. Our results thus have implications for improved detection of at‐risk individuals.

Judgement of sleep quality of the previous night changes as the day unfolds: A prospective experience sampling study.

How we form judgements of sleep quality is poorly understood. Emerging literature suggests that people infer their sleep quality based on multiple sources of accessible information, raising the possibility that sleep quality judgement may evolve as new relevant information becomes available. This study investigated whether people's rating of sleep quality of the night before changes throughout the following day, and what post-sleep factors are associated with the changes. A prospective experience sampling study of 119 healthy young adults, who completed eight short online surveys interspaced 2hr apart from 08:00 hours to 22:00 hours. Each survey asked the participants to report total sleep time and sleep quality of the night before, and to provide ratings of current mood, physical and social activity, and pain/discomfort. A memory test was added to the final survey of the day to measure the participants' recall of their first survey responses to sleep quality, as well as total sleep time and mood. The absolute majority (91.1%) of the participants had one or more change in their sleep quality rating across the eight surveys. A similar percentage of change was found for mood rating (100%) but not total sleep time report (20.5%). Memory test in the final survey revealed that the within-person variations in sleep quality rating were not simply memory errors. Instead, positive physical activity post-sleep predicted increases in sleep quality rating. Therefore, judgement of sleep quality of the night before changes as the day unfolds, and post-sleep information can be used by people to infer their sleep quality.

A Deep Transfer Learning Framework for Sleep Stage Classification with Single-Channel EEG Signals.

The polysomnogram (PSG) is the gold standard for evaluating sleep quality and disorders. Attempts to automate this process have been hampered by the complexity of the PSG signals and heterogeneity among subjects and recording hardwares. Most of the existing methods for automatic sleep stage scoring rely on hand-engineered features that require prior knowledge of sleep analysis. This paper presents an end-to-end deep transfer learning framework for automatic feature extraction and sleep stage scoring based on a single-channel EEG. The proposed framework was evaluated over the three primary signals recommended by the American Academy of Sleep Medicine (C4-M1, F4-M1, O2-M1) from two data sets that have different properties and are recorded with different hardware. Different Time-Frequency (TF) imaging approaches were evaluated to generate TF representations for the 30 s EEG sleep epochs, eliminating the need for complex EEG signal pre-processing or manual feature extraction. Several training and detection scenarios were investigated using transfer learning of convolutional neural networks (CNN) and combined with recurrent neural networks. Generating TF images from continuous wavelet transform along with a deep transfer architecture composed of a pre-trained GoogLeNet CNN followed by a bidirectional long short-term memory (BiLSTM) network showed the best scoring performance among all tested scenarios. Using 20-fold cross-validation applied on the C4-M1 channel, the proposed framework achieved an average per-class accuracy of 91.2%, sensitivity of 77%, specificity of 94.1%, and precision of 75.9%. Our results demonstrate that without changing the model architecture and the training algorithm, our model could be applied to different single-channel EEGs from different data sets. Most importantly, the proposed system receives a single EEG epoch as an input at a time and produces a single corresponding output label, making it suitable for real time monitoring outside sleep labs as well as to help sleep lab specialists arrive at a more accurate diagnoses.

Evaluation of Sleep Quality in Patients With Genital and Non-Genital Cutaneous Warts: a Prospective Controlled Study.

Diseases affect sleep quality, and sleep quality may also affect diseases by affecting the immune system. Depending on the immune status of patients with cutaneous warts, the extent of the disease and the response to treatment may vary. This study aimed to characterize the association between cutaneous warts and sleep quality. A prospective controlled study was conducted. Patients over 18 years with cutaneous warts were enrolled. The control subjects were healthy, age- and sex-matched people. Demographic and clinical data on the participants were gathered. The sleep quality of participants was evaluated with the Pittsburgh Sleep Quality Index (PSQI). A total of 138 patients with genital or non-genital cutaneous warts (N = 59, N = 79, respectively) and 83 controls were interviewed. The average global PSQI score of the group with cutaneous warts was significantly higher than that of the control group (1.292 95% confidence interval 1.174-1.422). The rate of poor sleep quality in the patient group was higher than in the control group (odds ratio 3.835). Patients with genital warts had a significantly higher average global PSQI score than patients with non-genital warts (8.61 ± 3.63 versus. 6.98 ± 3.32). Female patients with genital warts had a significantly higher average global PSQI score than male patients with genital warts. Evaluation of sleep quality in patients with warts, especially in patients with genital warts, may be suggested. The management of sleep disturbances associated with cutaneous warts may help increase the quality of life of patients and may affect disease control.

Evaluation of sleep quality and physical activity levels of university students during the COVID-19 pandemic

Evaluation of sleep quality and physical activity levels of university students during the COVID-19 pandemic

A Low-Cost Flexible Perforated Respiratory Sensor Based on Platinum for Continuous Respiratory Monitoring.

Monitoring sleep conditions is of importance for sleep quality evaluation and sleep disease diagnosis. Accurate respiration detection provides key information about sleep conditions. Here, we propose a perforated temperature sensor that can be worn below the nasal cavity to monitor breath. The sensing system consists of two perforated temperature sensors, signal conditioning circuits, a transmission module, and a supporting analysis algorithm. The perforated structure effectively enhances the sensitivity of the system and shortens the response time. The sensor’s response time is 0.07 s in air and sensitivity is 1.4‰°C−1. The device can achieve a monitoring respiratory temperature range between normal room temperature and 40 °C. The simple and standard micromachining process ensures low cost and high reproducibility. We achieved the monitoring of different breathing patterns, such as normal breathing, panting, and apnea, which can be applied to sleep breath monitoring and exercise information recording.

Evaluation of sleep quality and related factors in pregnant women

Objective: Although the pregnancy period is a physiological process, it can disrupt the sleep pattern and quality with some changes it causes. In this study, it was aimed to determine sleep quality, affecting factors and sleep problems, if any, in pregnant women who applied to our outpatient clinic for follow-up.&#x0D; Materials and Methods: This study, which was designed in a descriptive style, was conducted on 256 pregnant women who applied to the outpatient clinic. The data form included personal information, factors affecting sleep quality, sleep problems and Pittsburg Sleep Quality Index. In addition to descriptive statistics, Mann-Whitney U and Kruskal Wallis tests were used to evaluate the data uploaded to the SPSS program. The error level was set to 0.05. &#x0D; Results: The mean age of the pregnant women was 28.55. It was observed that the mean total PUKI score was 6.27±3.94 (0-18) and the mean sleep duration was 7.5 hours (3-14). Sleep quality was poor in 49.6% of the pregnant women. It was found that the sleep quality of pregnant women was poor in younger than 35 years old (p=0.026), education level of high school and above (p=0.010), who has gender expectetion (p=0.041) and not socially supported (p=0.009). The median weight gain in the third trimester was higher in pregnant women with poor sleep quality (p=0.022). It was determined that musculoskeletal pain, discomfort, frequent urination, swelling in the feet, pain/cramp in the legs and burning in the stomach during pregnancy affected sleep quality negatively. In pregnant women with poor sleep quality; problems such as shortening of sleep duration, difficulty in falling asleep, frequent interruption of sleep, difficulty in falling asleep again, waking up tired in the morning and waking up too early involuntarily were observed more frequently.&#x0D; Conclusion: About half of the pregnant women have poor sleep quality; physical complaints are effective on sleep quality. Sleep quality should be evaluated in all pregnant women and recommendations should be made for sleep hygiene.

Evaluation of Sleep Quality, Depression, and Quality of Life in Patients with Breast Cancer Related Lymphedema.

Background: Breast cancer-related lymphedema (BCRL) is a serious health condition negatively affecting psychological state, sleep quality, and quality of life (QOL) of patients. These complications of BCRL can be overlooked in routine clinical practice. The aim of this study is to evaluate sleep quality, depression, and QOL in patients with different stages of BCRL. Materials and Methods: This cross-sectional study included 111 consecutive women patients with BCRL attending to lymphedema unit of Physical Medicine and Rehabilitation Hospital in Ankara City Hospital. Demographical and clinical data of patients were noted. Sleep quality was assessed with Pittsburgh Sleep Quality Index, day-time sleepiness was assessed with Epworth Sleepiness Scale, depression was assessed with Beck Depression Questionnaire, and QOL was assessed with Lymphedema Quality of Life Questionnaire-arm. Results: Median age of patients was 57 (49-63) (25%-75% interquartile range). Nearly 58.8% of the patients had sleep disturbances, and 29.7% of the patients had depression. Presence of both sleep disturbance and depression was associated with increased age. Patients with sleep disturbance were found to be more depressive and vice versa, (p < 0.001, p < 0.001, respectively). Sleep disturbance, depression and day-time sleepiness, and higher body mass index were all associated with lower QOL scores. Conclusions: Presence of sleep disturbances and depression should be evaluated in every patient with BCRL with special attention to elderly. Rehabilitative management of BCRL should include psychiatric evaluation and interventions. Future studies should intend to assess the risk factors that affect psychological state, sleep quality, and QOL in patients with BCRL.

Post-COVID Pain Is Not Associated with Inflammatory Polymorphisms in People Who Had Been Hospitalized by COVID-19.

Our aim was to assess the association between four inflammatory polymorphisms with the development of post-COVID pain and to associate these polymorphisms with the clinical pain phenotype in individuals who had been hospitalized by COVID-19. Three potential genotypes of IL-6 (rs1800796), IL-10 (rs1800896), TNF-α (rs1800629), and IFITM3 (rs12252) single nucleotide polymorphisms (SNPs) were obtained from no-stimulated saliva samples from 293 (49.5% female, mean age: 55.6 ± 12.9 years) previously hospitalized COVID-19 survivors by polymerase chain reactions. Pain phenotyping consisted of the evaluation of pain features, sensitization-associated symptoms, anxiety levels, depressive levels, sleep quality, catastrophizing, and kinesiophobia levels in patients with post-COVID pain. Analyses were conducted to associate clinical features with genotypes. One hundred and seventeen (39.9%) patients experienced post-COVID pain 17.8 ± 5.2 months after hospital discharge. No significant differences in the distribution of the genotype variants of any SNPs were identified between COVID-19 survivors with and without post-COVID pain (all, p > 0.47). Similarly, the clinical pain phenotype was not significantly different between patients with and without post-COVID pain since no differences in any variable were observed for any SNPs. In conclusion, four SNPs associated with inflammatory and immune responses did not appear to be associated with post-COVID pain in previously hospitalized COVID-19 survivors. Further, neither of the SNPs were involved in the phenotyping features of post-COVID pain.

Evaluation of sleep quality and duration using wearable sensors in shift laborers of construction industry: A public health perspective.

Approximately 21% of the workers in developing and developed countries are shift laborers. The laborer's work shifts can affect personal life and sleep standards, adversely impacting laborers and their manage. This study assesses the impact of various shift plans (seven evenings/7 days, fixed-night or fixed-day, and backup shifts) on shift laborers, considering four shift schedules. Most laborers were on rotational shifts, whereas others were on a permanent day, permanent night, and standby shifts. In a cross-sectional study, 45 development laborers from the National Construction firm were enlisted. Bio-wearable sensors were provided to monitor sleep. Participants were approached and asked to complete a survey bundle comprising the Pittsburgh sleep quality index (PSQI) and Epworth sleepiness scale (ESS). Differences in sleep models were estimated using a Fitbit watch at various shift schedules. The average age of laborers who participated in the study was 37.5 years, and their average experience in the construction company was 6.5 years. The average total sleep time was 346 ± 46 min. The rotational shift laborers yielded the minimum total sleep time compared to the average PSQI and ESS scores of 7.66 ± 1.3 and 6.94 ± 3.4, respectively. Fifteen shift laborers (33.33%) were affected by a sleeping disorder in the present experimental investigation, and 30 participants had inadequate standards of sleep based on the PSQI scores. Poor sleep quality and duration among construction shift laborers decrease productivity at work. Additional studies are expected to assess sleep-related issues affecting construction shift laborers.