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Background Although electrocardiography is the gold standard for heart rate (HR) recording in clinical trials, the increasing availability of smartwatch-based HR monitors opens up possibilities for drug development studies. Smartwatches allow for inexpensive, unobtrusive, and continuous HR estimation for potential detection of treatment effects outside the clinic, during daily life. Objective The aim of this study is to evaluate the repeatability and sensitivity of smartwatch-based HR estimates collected during a randomized clinical trial. Methods The data were collected as part of a multiple-dose, investigator-blinded, randomized, placebo-controlled, parallel-group study of 12 patients with Parkinson disease. After a 6-day baseline period, 4 and 8 patients were treated for 7 days with an ascending dose of placebo and clenbuterol, respectively. Throughout the study, the smartwatch provided HR and sleep state estimates. The HR estimates were quantified as the 2.5th, 50th, and 97.5th percentiles within awake and asleep segments. Linear mixed models were used to calculate the following: (1) the intraclass correlation coefficient (ICC) of estimated sleep durations, (2) the ICC and minimum detectable effect (MDE) of the HR estimates, and (3) the effect sizes of the HR estimates. Results Sleep duration was moderately repeatable (ICC=0.64) and was not significantly affected by study day (P=.83), clenbuterol (P=.43), and study day by clenbuterol (P=.73). Clenbuterol-induced changes were detected in the asleep HR as of the first night (+3.79 beats per minute [bpm], P=.04) and in the awake HR as of the third day (+8.79 bpm, P=.001). The median HR while asleep had the highest repeatability (ICC=0.70). The MDE (N=12) was found to be smaller when patients were asleep (6.8 bpm to 11.7 bpm) than while awake (10.7 bpm to 22.1 bpm). Overall, the effect sizes for clenbuterol-induced changes were higher while asleep (0.49 to 2.75) than while awake (0.08 to 1.94). Conclusions We demonstrated the feasibility of using smartwatch-based HR estimates to detect clenbuterol-induced changes during clinical trials. The asleep HR estimates were most repeatable and sensitive to treatment effects. We conclude that smartwatch-based HR estimates obtained during daily living in a clinical trial can be used to detect and track treatment effects. Trial Registration Netherlands Trials Register NL8002; https://www.trialregister.nl/trial/8002

Abstract Nonvolatile large-scale integrated circuits (NV-LSIs) with a power-gating (PG) technique can drastically reduce the wasted static power consumption, which is an attractive feature in Internet-of-Things (IoT) edge devices. However, the issues of inrush current and voltage fluctuation due to PG-state transitions are preventing their advancement. This paper describes a technique for stabilizing the operation of NV-LSIs during PG by minimizing inrush current effects and voltage fluctuations. In the proposed technique, several PG switch configurations are prepared and one of them are dynamically selected in accordance with the expected operation conditions, which could minimize inrush current and voltage fluctuations in the power supply. This technique is applied to sub-array-level PG of a spin-transfer torque magneto-resistive random-access memory (STT-MRAM). As a result, inrush current level and the recovery time of the power supply from a sleep state are reduced by up to 83.8% and 68.7%, respectively, while satisfying given performance requirements.

PurposeThe purpose of this paper is to design an enhanced routing protocol to minimize energy consumed and extend network lifetime in sensor network (WSN).Design/methodology/approachWith the use of appropriate routing protocols, data collected by sensor nodes reache the BS. The entire network lifetime can be extended well beyond that of its single nodes by putting the nodes in sleep state when they are not in use, and make active just a single node at a time within a given area of interest. So that, the lowest-cost routing arises by minimizing the communication cost. This paper proposes an enhanced adaptive geographic fidelity (E-GAF) routing protocol based on theory of graphs approach to improve the discovery phase, select the optimal path, reduce the energy used by nodes and therefore extend the network lifetime. Following the simulations established by varying the number of grids and tests, a comparison is made between the E-GAF and basic GAF (B-GAF) based on the number of dead nodes and energy consumption.FindingsThe results obtained show that E-GAF is better than the existing basic GAF protocol in terms of energy efficiency and network lifetime.Originality/valueThis paper adopts the latest optimization algorithm know as E-GAF, which is used to solve the problem of energy and improve the network lifetime in a WSN. This is the first work that utilizes network lifetime in WSN.

AbstractInsomnia disorder (ID) is a heterogeneous disorder with proposed subtypes based on objective sleep duration. We speculated that insomnia subtyping with additional power spectral analysis and measurement of response to acute sleep restriction may be informative in overall assessment of ID. To explore alternative classifications of ID subtypes, insomnia patients (n = 99) underwent two consecutive overnight sleep studies: (i) habitual sleep opportunity (polysomnography, PSG) and, (ii) two hours less sleep opportunity (electroencephalography, EEG), with the first night compared to healthy controls (n = 25). ID subtypes were derived from data-driven classification of PSG, EEG spectral power and interhemispheric EEG asymmetry index. Three insomnia subtypes with different sleep duration and NREM spectral power were identified. One subtype (n = 26) had shorter sleep duration and lower NREM delta power than healthy controls (short-sleep delta-deficient; SSDD), the second subtype (n = 51) had normal sleep duration but lower NREM delta power than healthy controls (normal-sleep delta-deficient; NSDD) and a third subtype showed (n = 22) no difference in sleep duration or delta power from healthy controls (normal neurophysiological sleep; NNS). Acute sleep restriction improved multiple objective sleep measures across all insomnia subtypes including increased delta power in SSDD and NSDD, and improvements in subjective sleep quality for SSDD (p = 0.03), with a trend observed for NSDD (p = 0.057). These exploratory results suggest evidence of novel neurophysiological insomnia subtypes that may inform sleep state misperception in ID and with further research, may provide pathways for personalised care.

Background: Sleep state misperception (SSM) is seen among patients with obstructive sleep apnea (OSA) as well as those having insomnia. Moreover, OSA and insomnia can also be comorbid. This study aims at finding the proportion of SSM and “Comorbid Insomnia with OSA” (COMISA) among patients of OSA and chronic insomnia. Macroachitecture of sleep was also compared across groups. Methods: This study utilized the retrospective laboratory and medical records of two groups of patients: chronic insomnia and OSA. Sleep disorders were diagnosed according to standard criteria. Daytime sleepiness was examined using the Epworth Sleepiness Scale. Diagnosis of SSM was based on the difference between subjective and objective sleep onset latency (Subjective SOL > 1.5 × Objective SOL). Results: Sixteen adult subjects were included in each group. Based on the difference between subjective and objective sleep onset latency, SSM was reported by 62.5% subjects of chronic insomnia and 56.25% subjects having OSA (OR = 1.29; 95% CI = 0.31–5.33; P = 0.79). The proportion of COMISA in subjects with chronic insomnia was 18% and among subjects with OSA, it was 43%. Effect size for the proportion was calculated as odds ratio (33.96; 95% CI = 7.48–154.01; P < 0.0002). Thus, the odds for COMISA were higher among subjects with OSA than those with chronic Insomnia. The three groups (OSA, COMISA and Chronic Insomnia) were comparable with regard to the macro-architecture of sleep. Conclusion: SSM is common among subjects with OSA and chronic insomnia. COMISA was commoner among patients with OSA compared to those with chronic insomnia. Macro-architecture of sleep is comparable among groups.

Background: Some accident victims report poorer sleep during the months after the trauma, which may double the risk for and is a mediator of the development of a PTSD. Furthermore, subjective and objective sleep measures are often discrepant in PTSD-patients, which is why a ‘sleep state misperception’ of PTSD patients is often hypothesized. Objective: The goal of this study is to assess differences in sleep quality in victims of a traffic accident compared to healthy participants without an accident history as well as differences between objective and subjective sleep quality measures. Methods: We recruited 25 hospitalized accident victims within ten days of an accident and 31 age and sex-matched controls without an accident history. Three months later, participants were given a structured clinical interview (SCID), they completed the Pittsburg Sleep Quality Index (PSQI) for the previous two weeks, wore a wrist actigraph, and kept a sleep log for two consecutive nights. Results: At the three-month follow-up, none of the victims met the criteria for any kind of mental disorder, but scored higher on the Posttraumatic Diagnostic Scale. On the PSQI they reported slightly worse sleep than controls for the previous two weeks, although sleep log and actigraphy measures on the two recording nights showed no group differences. Actigraphy measures showed shorter sleep onset latencies compared to log measures. Conclusions: The accident victims suffered only minimal sleep disturbances three months later. The assumption of a ‘sleep state misperception’ in traffic accident victims is questioned by these results.

Abstract The progression of animal development from embryonic to juvenile life depends on the coordination of organism-wide responses with environmental conditions. We found that two transcription factors that function in interneuron differentiation in Caenorhabditis elegans, fax-1 and unc-42, are required for arousal and progression from embryogenesis to larval life by potentiating insulin signaling. The combination of mutations in either transcription factor and a mutation in daf-2 insulin receptor results in a novel peri-hatching arrest phenotype; embryos are fully-developed but inactive, often remaining trapped within the eggshell, and fail to initiate pharyngeal pumping. This pathway is opposed by an osmotic sensory response pathway that promotes developmental arrest and a sleep state at the end of embryogenesis in response to elevated salt concentration. The quiescent state induced by loss of insulin signaling or by osmotic stress can be reversed by mutations in genes that are required for sleep. Therefore, countervailing signals regulate late embryonic arousal and developmental progression to larval life, mechanistically linking the two responses. Our findings demonstrate a role for insulin signaling in an arousal circuit, consistent with evidence that insulin-related regulation may function in control of sleep states in many animals. The opposing quiescent arrest state may serve as an adaptive response to the osmotic threat from high salinity environments.