Smoking remains a highly significant preventable global public health problem. In this context, digital interventions offer great advantages in terms of a lack of biological side effects, possibility of automatic delivery, and consequent human resource savings relative to traditional interventions. Such interventions have been studied in randomized controlled trials (RCTs) but have not been systematically reviewed with the inclusion of text-based and multiplatform-based interventions. In addition, this area has not been evaluated from the perspective of the psychological theoretical basis of intervention.
The aim of this paper is to assess the efficiency of digital interventions in RCT studies of smoking cessation and to evaluate the effectiveness of the strategies used for digital interventions.
An electronic search of RCTs was conducted using PubMed, Embase, and the Cochrane Library by June 30, 2021. Eligible studies had to compare automated digital intervention (ADI) to the use of a self-help guideline or no intervention. Participants were current smokers (aged 16 years or older). As the main outcome, abstinence after endpoint was extracted from the studies. Systematic review and meta-analysis were conducted to assess the efficiency of ADIs. Metaregressions were conducted to assess the relationship between intervention theory and effectiveness.
A total of 19 trials (15,472 participants) were included in the analysis. The overall abstinence rate (95% CI) at the endpoint was 17.8% (17.0-18.7). The overall risk ratio of the intervention group compared to the controls at the endpoint was 17.8% (17.0-18.7). Cochrane risk-of-bias tool for randomized trials (ROB 2) suggested that most of the studies had a low risk of bias (56.3%). Psychological theory-related constructs or predictors, which refer to other theory-based concepts (rather than only behavioral theory) such as craving or anxiety, are associated with effectiveness.
This study found that ADI had a clear positive effect compared to self-help guidelines or to no intervention, and effectiveness was associated with theory-related constructs or predictors. ADIs should be promoted by policy makers and clinical practitioners to address the huge gap between the need for smoking cessation and availability of traditional treatment resources. Possible increases in ADI efficiency may be achieved by optimally integrating psychotherapeutic theories and techniques.
PROSPERO CRD42021256593; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=256593.

OBJECTIVE: Approximately 6.3% of the worldwide population has type 2 diabetes mellitus (T2DM), and the number of people requiring insulin is increasing. Automated insulin delivery (AID) systems integrate continuous subcutaneous insulin infusion and continuous glucose monitoring with a predictive control algorithm to provide more physiologic glycemic control. Personalized glycemic targets are recommended in T2DM owing to the heterogeneity of the disease. Based on the success of hybrid closed-loop systems in improving glycemic control and safety in type 1 diabetes mellitus, there has been further interest in the use of these systems in people with T2DM.
METHODS: We performed a review of AID systems with a focus on the T2DM population.
RESULTS: In 5 randomized controlled trials, AID systems improve time in range and reduce glycemic variability, without increasing insulin requirements or the risk of hypoglycemia.
CONCLUSIONS: AID systems in T2DM are safe and effective in hospitalized and closely monitored settings. Home studies of longer duration are required to assess for long-term benefit and identify target populations of benefit.

Physiological Closed-Loop Controlled systems continue to take a growing part in clinical practice, offering possibilities of providing more accurate, goal-directed care while reducing clinicians\' cognitive and task load. These systems also provide a standardized approach for the clinical management of the patient, leading to a reduction in care variability across multiple dimensions. For fluid management and administration, the advantages of closed-loop technology are clear, especially in conditions that require precise care to improve outcomes, such as peri-operative care, trauma, and acute burn care. Controller design varies from simplistic to complex designs, based on detailed physiological models and adaptive properties that account for inter-patient and intra-patient variability; their maturity level ranges from theoretical models tested in silico to commercially available, FDA-approved products. This comprehensive scoping review was conducted in order to assess the current technological landscape of this field, describe the systems currently available or under development, and suggest further advancements that may unfold in the coming years. Ten distinct systems were identified and discussed.

To provide dental practitioners and researchers with a comprehensive and transparent evidence-based overview of physical robot initiatives in all fields of dentistry.
Articles published since 1985 concerning primary data on physical robot technology in dentistry were selected. Characteristics of the papers were extracted such as the respective field of dentistry, year of publication as well as a description of its usage.
Bibliographic databases PubMed, Embase, and Scopus were searched. A hand search through reference lists of all included articles was performed.
The search timeline was between January 1985 and October 2020. All types of scientific literature in all languages were included concerning fields of dentistry ranging from student training to implantology. Robot technology solely for the purpose of research and maxillofacial surgery were excluded. In total, 94 articles were included in this systematic review.
This study provides a systematic overview of initiatives using robot technology in dentistry since its very beginning. While there were many interesting robot initiatives reported, the overall quality of the literature, in terms of clinical validation, is low. Scientific evidence regarding the benefits, results and cost-efficiency of commercially available robotic solutions in dentistry is lacking. The rise in availability of open source control systems, compliant robot systems and the design of dentistry-specific robot technology might facilitate the process of technological development in the near future. The authors are confident that robotics will provide useful solutions in the future but, strongly, encourage an evidence-based approach when adapting to new (robot) technology.

To provide dental practitioners and researchers with a comprehensive and transparent evidence-based overview of the characteristics of literature regarding initiatives of robot technology in dentistry.
All articles in which robot technology in dentistry is described, except for non-scientific articles and articles containing secondary data (reviews). Amongst others, the following data were extracted: type of study, level of technological readiness, authors\' professional background and the subject of interaction with the robot.
Bibliographic databases PubMed, Embase, and Scopus were surveyed. A reference search was conducted. The search timeline was between January 1985 and October 2020.
A total of 911 articles were screened on title and abstract of which 161 deemed eligible for inclusion. Another 71 articles were excluded mainly because of unavailability of full texts or the sole use of secondary data (reviews). Four articles were included after hand searching the reference lists. In total, 94 articles were included for analysis.
Since 2013 an average of six articles per year concern robot initiatives in dentistry, mostly originating from East Asia (57%). The vast majority of research was categorized as either basic theoretical or basic applied research (80%). Technology readiness levels did not reach higher than three (proof of concept) in 55% of all articles. In 84%, the first author of the included articles had a technical background and in 36%, none of the authors had a dental or medical background. The overall quality of literature, especially in terms of clinical validation, should be considered as low.

Investigations of behavior and control of voluntary stereotyped rhythmic movement contribute to the enhancement of motor function and performance of disabled, sick, injured, healthy, and exercising humans. The present article presents examples of unprompted alteration of freely chosen movement rate during voluntary stereotyped rhythmic movements. The examples, in the form of both increases and decreases of movement rate, are taken from activities of cycling, finger tapping, and locomotion. It is described that, for example, strength training, changed power output, repeated bouts, and changed locomotion speed can elicit an unprompted alteration of freely chosen movement rate. The discussion of the examples is based on a tripartite interplay between descending drive, rhythm-generating spinal neural networks, and sensory feedback, as well as terminology from dynamic systems theory.

Until recently, animal behavior has been studied through close and extensive observation of individual animals and has relied on subjective assessments. Wearable technologies that allow the automation of dairy cow behavior recording currently dominate the precision dairy technology market. Wearable accelerometers provide new opportunities in animal ethology using quantitative measures of dairy cow behavior. Recent research developments indicate that quantitative measures of behavior may provide new objective on-farm measures to assist producers in predicting, diagnosing, and managing disease or injury on farms and allowing producers to monitor cow comfort and estrus behavior. These recent research developments and a large increase in the availability of wearable accelerometers have led to growing interest of both researchers and producers in this technology. This review aimed to summarize the studies that have validated lying behavior derived from accelerometers and to describe the factors that should be considered when using leg-attached accelerometers and neck-worn collars to describe lying behavior (e.g., lying time and lying bouts) in dairy cows for research purposes. Specifically, we describe accelerometer technology, including the instrument properties and methods for recording motion; the raw data output from accelerometers; and methods developed for the transformation of raw data into meaningful and interpretable information. We highlight differences in validation study outcomes for researchers to consider when developing their own experimental methodology for the use of accelerometers to record lying behaviors in dairy cows. Finally, we discuss several factors that may influence the data recorded by accelerometers and highlight gaps in the literature. We conclude that researchers using accelerometers to record lying behaviors in dairy cattle should (1) select an accelerometer device that, based on device attachment and sampling rate, is appropriate to record the behavior of interest; (2) account for cow-, farm-, and management-related factors that could affect the lying behaviors recorded; (3) determine the appropriate editing criteria for the accurate interpretation of their data; (4) support their chosen method of recording, editing, and interpreting the data by referencing an appropriately designed and accurate validation study published in the literature; and (5) report, in detail, their methodology to ensure others can decipher how the data were captured and understand potential limitations of their methodology. We recommend that standardized protocols be developed for collecting, analyzing, and reporting lying behavior data recorded using wearable accelerometers for dairy cattle.

Locomotion scoring is time consuming and is not commonly completed on farms. Farmers also underestimate their herds\' lameness prevalence, a knowledge gap that impedes lameness management. Automation of lameness detection could address this knowledge gap and facilitate improved lameness management. The literature pertinent to adding lameness detection to accelerometers is reviewed in this paper. Options for lameness detection systems are examined including the choice of sensor, raw data collected, variables extracted, and statistical classification methods used. Two categories of variables derived from accelerometer-based systems are examined. These categories are behavior measures such as lying and measures of gait. For example, one measure of gait is the time a leg is swinging during a gait cycle. Some behavior-focused studies have reported accuracy levels of greater than 80%. Cow gait measures have been investigated to a lesser extent than behavior. However, classification accuracies as high as 91% using gait measures have been reported with hardware likely to be practical for commercial farms. The need for even higher accuracy and potential barriers to adoption are discussed. Significant progress is still required to realize a system with sufficient specificity and sensitivity. Lameness detection systems using 1 accelerometer per cow and a resolution lower than 100 Hz with gait measurement functions are suggested to balance cost and data requirements. However, gait measurement using accelerometers is rather underdeveloped. Therefore, a high priority should be given to the development of novel gait measures and testing their ability to differentiate lame from nonlame cows.

Pneumonia is the leading infectious cause of death in children worldwide, with most deaths occurring in developing countries. Measuring respiratory rate is critical to the World Health Organization\'s guidelines for diagnosing childhood pneumonia in low-resource settings, yet it is difficult to accurately measure. We conducted a systematic review to landscape existing respiratory rate measurement technologies. We searched PubMed, Embase, and Compendex for studies published through September 2017 assessing the accuracy of respiratory rate measurement technologies in children. We identified 16 studies: 2 describing manual devices and 14 describing automated devices. Although both studies describing manual devices took place in low-resource settings, all studies describing automated devices were conducted in well-resourced settings. Direct comparison between studies was complicated by small sample size, absence of a consistent reference standard, and variations in comparison methodology. There is an urgent need for affordable and appropriate innovations that can reliably measure a child\'s respiratory rate in low-resource settings. Accelerating development or scale-up of these technologies could have the potential to advance childhood pneumonia diagnosis worldwide.

B-mode ultrasound imaging is used extensively in medicine. Hence, there is a need to have efficient segmentation tools to aid in computer-aided diagnosis, image-guided interventions, and therapy. This paper presents a comprehensive review on automated localization and segmentation techniques for B-mode ultrasound images. The paper first describes the general characteristics of B-mode ultrasound images. Then insight on the localization and segmentation of tissues is provided, both in the case in which the organ/tissue localization provides the final segmentation and in the case in which a two-step segmentation process is needed, due to the desired boundaries being too fine to locate from within the entire ultrasound frame. Subsequenly, examples of some main techniques found in literature are shown, including but not limited to shape priors, superpixel and classification, local pixel statistics, active contours, edge-tracking, dynamic programming, and data mining. Ten selected applications (abdomen/kidney, breast, cardiology, thyroid, liver, vascular, musculoskeletal, obstetrics, gynecology, prostate) are then investigated in depth, and the performances of a few specific applications are compared. In conclusion, future perspectives for B-mode based segmentation, such as the integration of RF information, the employment of higher frequency probes when possible, the focus on completely automatic algorithms, and the increase in available data are discussed.