Distinguishing sleep from wake with a radar sensor A contact-free real-time sleep monitor.
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ABSTRACT:
SUBMITTER: Heglum HSA
PROVIDER: S-EPMC8361351 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundDifferentiating nonwear time from sleep and wake times is essential for the estimation of sleep duration based on actigraphy data. To efficiently analyze large-scale data sets, an automatic method of identifying these three different states is required. Therefore, we developed a classification algorithm to determine nonwear, sleep and wake periods from accelerometer data. Our work aimed to (I) develop a new pattern recognition algorithm for identifying nonwear periods from actigraphy data based on the influence of respiration rate on the power spectrum of the acceleration signal and implement it in an automatic classification algorithm for nonwear/sleep/wake states; (II) address motion artifacts that occur during nonwear periods and are known to cause misclassification of these periods; (III) adjust the algorithm depending on the sensor position (wrist, chest); and (IV) validate the algorithm on both healthy individuals and patients with sleep disorders.MethodsThe study involved 98 participants who wore wrist and chest acceleration sensors for one day of measurements. They spent one night in the sleep laboratory and continued to wear the sensors outside of the laboratory for the remainder of the day. The results of the classification algorithm were compared to those of the reference source: polysomnography for wake/sleep and manual annotations for nonwear/wear classification.ResultsThe median kappa values for the two locations were 0.83 (wrist) and 0.84 (chest). The level of agreement did not vary significantly by sleep health (good sleepers vs. subjects with sleep disorders) (p = 0.348, p = 0.118) or by sex (p = 0.442, p = 0.456). The intraclass correlation coefficients of nonwear total time between the reference and the algorithm were 0.92 and 0.97 with the outliers and 0.95 and 0.98 after the outliers were removed for the wrist and chest, respectively. There was no evidence of an association between the mean difference (and 95% limits of agreement) and the mean of the two methods for either sensor position (wrist p = 0.110, chest p = 0.164), and the mean differences (algorithm minus reference) were 5.11 [95% LoA -15.4-25.7] and 1.32 [95% LoA -9.59-12.24] min/day, respectively, after the outliers were removed.DiscussionWe studied the influence of the respiration wave on the power spectrum of the acceleration signal for the differentiation of nonwear periods from sleep and wake periods. The algorithm combined both spectral analysis of the acceleration signal and rescoring. Based on the Bland-Altman analysis, the chest-worn accelerometer showed better results than the wrist-worn accelerometer.
| S-EPMC6942683 | biostudies-literature
Project description:A capacitive sensor was developed to analyze the presence and enzymatic activity of a model protease from standard solutions by following the degradation of the substrate in real time. The enzyme was chosen based on its specific digestion of the hinge region of immunoglobulin G (IgG). Real-time enzyme activity was monitored by measuring the change in capacitance (∆C) based on the release of IgG fragments after enzymatic digestion by the enzyme. The results indicated that the developed capacitive system might be used successfully for label-free and real-time monitoring of enzymatic activity of different enzymes in a sensitive, rapid, and inexpensive manner in biotechnological, environmental, and clinical applications.
| S-EPMC6754820 | biostudies-literature
Project description:We discovered that impulse-radio ultra-wideband (IR-UWB) radar could recognize cardiac motions in a non-contact fashion. Therefore, we measured the heart rate (HR) and rhythms using an IR-UWB radar sensor and evaluated the validity and reliability of the measurements in comparison to electrocardiography. The heart beats were measured in 6 healthy volunteers (18 samples) with normal sinus rhythm (NSR) and 16 patients (36 samples) with atrial fibrillation (AF) using both an IR-UWB radar sensor and electrocardiography simultaneously. The participants hold their breath for 20?seconds during the data acquisition. In subjects with NSR, there was excellent agreement of HR (intraclass correlation coefficient [ICC] 0.856), average R-R interval (ICC 0.997) and individual R-R intervals between the two methods (ICC 0.803). In subjects with AF, HR (ICC 0.871) and average R-R interval (ICC 0.925) from the radar sensor also agreed well with those from electrocardiography, though there was a small disagreement in the individual R-R intervals between the two methods (ICC 0.697). The rhythms computed by the signal-processing algorithm showed good agreement between the two methods (Cohen's Kappa 0.922). The IR-UWB radar sensor is precise and accurate for assessing HR and rhythms in a non-contact fashion.
| S-EPMC6115337 | biostudies-literature
Project description:While full-night polysomnography is the gold standard for the diagnosis of obstructive sleep apnea, its limitations include a high cost and first-night effects. This study developed an algorithm for the detection of respiratory events based on impulse-radio ultra-wideband radar and verified its feasibility for the diagnosis of obstructive sleep apnea. A total of 94 subjects were enrolled in this study (23 controls and 24, 14, and 33 with mild, moderate, and severe obstructive sleep apnea, respectively). Abnormal breathing detected by impulse-radio ultra-wideband radar was defined as a drop in the peak radar signal by ?30% from that in the pre-event baseline. We compared the abnormal breathing index obtained from impulse-radio ultra-wideband radar and apnea-hypopnea index (AHI) measured from polysomnography. There was an excellent agreement between the Abnormal Breathing Index and AHI (intraclass correlation coefficient?=?0.927). The overall agreements of the impulse-radio ultra-wideband radar were 0.93 for Model 1 (AHI???5), 0.91 for Model 2 (AHI???15), and 1 for Model 3 (AHI???30). Impulse-radio ultra-wideband radar accurately detected respiratory events (apneas and hypopneas) during sleep without subject contact. Therefore, impulse-radio ultra-wideband radar may be used as a screening tool for obstructive sleep apnea.
| S-EPMC7093464 | biostudies-literature
Project description:We demonstrate an electrochemical sensor for detection of unlabeled single-stranded DNA using peptide nucleic acid (PNA) probes coupled to the field-effect transistor (FET) gate. The label-free detection relies on the intrinsic charge of the DNA backbone. Similar detection schemes have mainly concentrated on sensitivity improvement with an emphasis on new sensor structures. Our approach focuses on using an extended-gate that separates the FET and the sensing electrode yielding a simple and mass fabricable device. We used PNA probes for efficient hybridization in low salt conditions that is required to avoid the counter ion screening. As a result, significant part of the target DNA lies within the screening length of the sensor. With this, we achieved a wash-free detection where typical gate potential shifts are more than 70?mV with 1?µM target DNA. We routinely obtained a real-time, label- and wash-free specific detection of target DNA in nanomolar concentration with low-cost electronics and the responses were achieved within minutes after introducing targets to the solution. Furthermore, the results suggest that the sensor performance is limited by specificity rather than by sensitivity and using low-cost electronics does not limit the sensor performance in the presented sensor configuration.
| S-EPMC5691077 | biostudies-literature
Project description:STUDY OBJECTIVES:To develop and validate a novel non-contact system for whole-night sleep evaluation using breathing sounds analysis (BSA). DESIGN:Whole-night breathing sounds (using ambient microphone) and polysomnography (PSG) were simultaneously collected at a sleep laboratory (mean recording time 7.1 hours). A set of acoustic features quantifying breathing pattern were developed to distinguish between sleep and wake epochs (30 sec segments). Epochs (n = 59,108 design study and n = 68,560 validation study) were classified using AdaBoost classifier and validated epoch-by-epoch for sensitivity, specificity, positive and negative predictive values, accuracy, and Cohen's kappa. Sleep quality parameters were calculated based on the sleep/wake classifications and compared with PSG for validity. SETTING:University affiliated sleep-wake disorder center and biomedical signal processing laboratory. PATIENTS:One hundred and fifty patients (age 54.0±14.8 years, BMI 31.6±5.5 kg/m2, m/f 97/53) referred for PSG were prospectively and consecutively recruited. The system was trained (design study) on 80 subjects; validation study was blindly performed on the additional 70 subjects. MEASUREMENTS AND RESULTS:Epoch-by-epoch accuracy rate for the validation study was 83.3% with sensitivity of 92.2% (sleep as sleep), specificity of 56.6% (awake as awake), and Cohen's kappa of 0.508. Comparing sleep quality parameters of BSA and PSG demonstrate average error of sleep latency, total sleep time, wake after sleep onset, and sleep efficiency of 16.6 min, 35.8 min, and 29.6 min, and 8%, respectively. CONCLUSIONS:This study provides evidence that sleep-wake activity and sleep quality parameters can be reliably estimated solely using breathing sound analysis. This study highlights the potential of this innovative approach to measure sleep in research and clinical circumstances.
| S-EPMC4339734 | biostudies-literature
Project description:A wearable monitor that can reliably, accurately, and continuously measure personal exposure levels of various toxicants would not only accelerate the current environmental and occupational health and safety studies, but also enable new studies that are not possible with the current monitoring technology. Developing such a monitor has been a difficult challenge, and requires innovative sensing science and creative engineering. We have developed, built, and tested a wearable monitor for real-time detection of toxic hydrocarbons and acids in the environment. The monitor is low-cost, accurate, and user friendly. In addition, it can communicate wirelessly with a cell phone in which the monitoring results can be processed, displayed, stored, and transmitted to a designated computer. We have validated the functions and performance of the monitor, and carried out field tests with workers involving waste management, fire overhaul, and floor-cleaning activities, as well as with first- and second-hand smokers. The averaged exposure levels are in agreement with those determined by the standard NIOSH methods. The monitor provides accurate and real-time exposure assessment for the workers involving different activities. The real-time and continuous monitoring capability makes it possible to correlate the exposure levels with different activities and changes in the microenvironments. The monitor provides unprecedented real-time information that will help advance occupational safety and environmental health studies. It may also be used to better protect workers from occupational overexposure to toxic molecules.
| S-EPMC3721732 | biostudies-literature
Project description:Study objectivesThe diagnosis of insomnia rests on self-report of difficulty initiating or maintaining sleep. However, subjective reports may be unreliable, and possibly may vary by the method of inquiry. We investigated this possibility by comparing within-individual response to direct versus indirect time queries after overnight polysomnography.MethodsWe obtained self-reported sleep-wake times via morning questionnaires in 879 consecutive adult diagnostic polysomnograms. Responses were compared within subjects (direct versus indirect query) and across groups defined by apnea-hypopnea index and by self-reported insomnia symptoms in pre-sleep questionnaires. Direct queries required a time duration response, while indirect queries required clock times from which we calculated time durations.ResultsDirect and indirect queries of sleep latency were the same in only 41% of cases, and total sleep time queries matched in only 5.4%. For both latency and total sleep, the most common discrepancy involved the indirect value being larger than the direct response. The discrepancy between direct and indirect queries was not related to objective sleep metrics. The degree of discrepancy was not related to the presence of insomnia symptoms, although patients reporting insomnia symptoms showed underestimation of total sleep duration by direct response.ConclusionsSelf-reported sleep latency and total sleep time are often internally inconsistent when comparing direct and indirect survey queries of each measure. These discrepancies represent substantive challenges to effective clinical practice, particularly when diagnosis and management depends on self-reported sleep patterns, as with insomnia. Although self-reported sleep-wake times remains fundamental to clinical practice, objective measures provide clinically relevant adjunctive information.
| S-EPMC4298769 | biostudies-literature
Project description:People with diabetes are more likely to experience sleep disturbance than those without. Sleep disturbance can cause daytime sleepiness in diabetic patients, which may impair their daytime performance or even lead to workplace injuries. Therefore, restoring the normal sleep-wake cycle is critical for diabetic patients who experience daytime sleepiness. Previous data on a diabetic mouse model, the db/db mice, have demonstrated that the total sleep time and sleep fragmentation are increased and the daily rhythm of the sleep-wake cycle is attenuated. Accumulating evidence has shown that active time-restricted feeding (ATRF), in which the timing of food availability is restricted to the active-phase, is beneficial to metabolic health. However, it is unknown whether ATRF restores the normal sleep-wake cycle in diabetes. To test that, we used a non-invasive piezoelectric system to monitor the sleep-wake profile in the db/db mice with ad libitum feeding (ALF) as a baseline and then followed with ATRF. The results showed that at baseline, db/db mice exhibited abnormal sleep-wake patterns: the sleep time percent during the light-phase was decreased, while during the dark-phase it was increased with unusual cycling compared to control mice. In addition, the sleep bout length during both the light-phase and the full 24-h period was shortened in db/db mice. Analysis of the sleep-wake circadian rhythm showed that ATRF effectively restored the circadian but suppressed the ultradian oscillations of the sleep-wake cycle in the db/db mice. In conclusion, ATRF may serve as a novel strategy for treating diabetes-induced irregularity of the sleep-wake cycle.
| S-EPMC6763589 | biostudies-literature
Project description:Underwater sensor networks represent an important and promising field of research due to the large diversity of underwater ubiquitous applications that can be supported by these networks, e.g., systems that deliver tsunami and oil spill warnings, or monitor submarine ecosystems. Most of these monitoring and warning systems require real-time communication in wide area networks that have a low density of nodes. The underwater communication medium involved in these networks is very harsh and imposes strong restrictions to the communication process. In this scenario, the real-time transmission of information is done mainly using acoustic signals, since the network nodes are not physically close. The features of the communication scenario and the requirements of the communication process represent major challenges for designers of both, communication protocols and monitoring and warning systems. The lack of models to represent these networks is the main stumbling block for the proliferation of underwater ubiquitous systems. This paper presents a real-time communication model for underwater acoustic sensor networks (UW-ASN) that are designed to cover wide areas with a low density of nodes, using any-to-any communication. This model is analytic, considers two solution approaches for scheduling the real-time messages, and provides a time-constraint analysis for the network performance. Using this model, the designers of protocols and underwater ubiquitous systems can quickly prototype and evaluate their solutions in an evolving way, in order to determine the best solution to the problem being addressed. The suitability of the proposal is illustrated with a case study that shows the performance of a UW-ASN under several initial conditions. This is the first analytic model for representing real-time communication in this type of network, and therefore, it opens the door for the development of underwater ubiquitous systems for several application scenarios.
| S-EPMC5539683 | biostudies-other