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Objective: Goal of the study was to systematically review competitive advantages of medical devices for glucose monitoring in diabetic patients. Method: The review is done systematically according to SALSA criteria and PRISMA guidelines. The search for eligible articles was held from February 16th 2023 to March 1st 2023 in Russian and English languages. The results were synthesized narratively, tabularly, and visually. The search was conducted in the following databases of scientific literature: PubMed, IEEE Xplore, Google Scholar, CyberLeninka, and eLibrary. Results: Twenty-two out of fifty-two manuscripts met the inclusion criteria. The most promising and advantageous characteristics of the evaluated devices, as identified by researchers, include the following: the capability for noninvasive examination; features that facilitate use by patients with fine motor, hearing, and visual impairments; add-ons and software designed to improve patient compliance, including in pediatric populations; and device attributes that enhance the speed and accuracy of analysis while being free of iatrogenic effects. Conclusions: With increasing prevalence of diabetes, glycemic control is crucial for preventing complications. The market offers numerous glucose monitoring devices (GMDs) with varying features, making selection challenging. Our study systematically categorized the strengths of each GMD model for diabetic patients, aiding informed device selection.

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Background: Children and adolescents who are overweight and obese represent a growing public health issue. The use of step-monitoring devices as an intervention tool may be a simple, cost-effective, and easily replicable solution for addressing obesity in children and adolescents. No prior systematic reviews have evaluated the effectiveness of utilizing step-monitoring devices as an intervention method for obesity in children and adolescents. Methods: Previous studies on using step-monitoring devices to prevent and treat obesity in children and adolescents were identified in the following databases: Web of Science, EMBASE, PubMed, Cochrane Library, SPORTDiscus, and SCOPUS. The search period for each database ranged from the year of their inception to 8 March 2023 (updated in June 2024). Meta-analyses were performed for mean differences (MDs) in body mass index (BMI), BMI z-score (BMI-Z), body fat, waist circumference, and body weight. Results: From 12,907 relevant records, 23 studies were included in this meta-analysis. The included studies were mainly at low risk of bias, except for blinding. Step-monitoring device-based interventions had significant effects in reducing BMI-Z (MD -0.06; 95% CI -0.10 to -0.02), body fat (MD -0.95%; 95% CI -1.35 to -0.54), and body weight (MD -1.23 kg; 95% CI -2.36 to -0.10). However, there was no significant effect on BMI (MD -0.16 kg/m2; 95% CI -0.55 to 0.22) and waist circumference (MD -0.33 cm; 95% CI -1.23 to 0.58). Subgroup analyses indicated that participants who were overweight or obese showed greater intervention effects on BMI and BMI-Z compared to participants with normal weight. The programs with an intervention duration of ≤6 months presented a greater intervention effect on BMI-Z than those with an intervention duration of more than 6 months. The programs that established goals had a greater intervention effect on body fat than those that did not. Conclusions: Step-monitoring devices may be an effective and generalizable intervention tool for the prevention and treatment of obesity in children and adolescents. Future studies should further explore how to set step goals and the duration of interventions to achieve better intervention effects.

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BACKGROUND: The use of wearable monitoring devices (WMDs), such as smartwatches, is advancing support and care for community-dwelling older adults across the globe. Despite existing evidence of the importance of WMDs in preventing problems and promoting health, significant concerns remain about the decline in use after a period of time, which warrant an understanding of how older adults experience the devices. OBJECTIVE: This study aims to explore and describe the experiences of community-dwelling older adults after receiving our interventional program, which included the use of a smartwatch with support from a community health workers, nurses, and social workers, including the challenges that they experienced while using the device, the perceived benefits, and strategies to promote their sustained use of the device. METHODS: We used a qualitative descriptive approach in this study. Older adults who had taken part in an interventional study involving the use of smartwatches and who were receiving regular health and social support were invited to participate in focus group discussions at the end of the trial. Purposive sampling was used to recruit potential participants. Older adults who agreed to participate were assigned to focus groups based on their community. The focus group discussions were facilitated and moderated by 2 members of the research team. All discussions were recorded and transcribed verbatim. We used the constant comparison analytical approach to analyze the focus group data. RESULTS: A total of 22 participants assigned to 6 focus groups participated in the study. The experiences of community-dwelling older adults emerged as (1) challenges associated with the use of WMDs, (2) the perceived benefits of using the WMDs, and (3) strategies to promote the use of WMDs. In addition, the findings also demonstrate a hierarchical pattern of health-seeking behaviors by older adults: seeking assistance first from older adult volunteers, then from social workers, and finally from nurses. CONCLUSIONS: Ongoing use of the WMDs is potentially possible, but it is important to ensure the availability of technical support, maintain active professional follow-ups by nurses and social workers, and include older adult volunteers to support other older adults in such programs.

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Background: The delivery channels and approaches related to cardiac rehabilitation (CR), such as eHealth, mHealth, and telehealth, are evolving. Several studies have identified their effects on patients with coronary heart disease, although no studies have focused on all the approaches collectively. Methods: Randomized controlled trials have investigated lipid profiles, through systolic blood pressure (SBP), diastolic blood pressure (DBP), and body mass index (BMI). Stata software was used for analysis, while Egger's linear regression test and Begg's funnel plot were also applied. Results: Technology-based home CR revealed significantly lower total cholesterol (TC) levels (standardized mean difference (SMD) = -0.19; 95% confidence interval [CI]: [-0.27, -0.11]); triglyceride (TG) levels (SMD = -0.26; 95% CI: [-0.35, 0.17]); low-density lipoprotein (LDL) levels (SMD = -0.18; 95% CI: [ -0.25, -0.11]); SBP (SMD = -0.26; 95% CI: [-0.33, -0.19]); DBP (SMD = -0.24; 95% CI: [-0.32, -0.16]); BMI (SMD = -0.12; 95% CI: [-0.18, -0.05]), and improved high-density lipoprotein (HDL) levels (SMD = 0.22; 95% CI: [0.14, 0.31]). Conclusions: Technology-based home CR can be used to lower TC, TG, and LDL levels, alongside the BMI, SBP, and DBP indexes, while also raising HDL levels; thus, its use should be widely promoted.

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BACKGROUND: Despite the well-documented health benefits associated with wearable monitoring devices (WMDs), adherence among community-dwelling older adults remains low. By providing guidance on the purpose and benefits of using WMDs, facilitating goal-setting aligned with the device's features, promoting comprehension of the health data captured by the device, and assisting in overcoming technological challenges, peers and health care professionals can potentially enhance older adults' adherence to WMDs. However, the effectiveness of such support mechanisms in promoting adherence to WMDs among older adults remains poorly understood. OBJECTIVE: The aims of this systematic review were to examine the effects of peer- or professional-led intervention programs designed to improve adherence to WMDs among community-dwelling older adults and to identify the intervention components that may positively influence the effects of the intervention. METHODS: We conducted a comprehensive search across 7 electronic databases (Cochrane Central Register of Controlled Trials [CENTRAL], PubMed, EMBASE, PsycINFO, British Nursing Index, Web of Science, and CINAHL) to identify articles published between January 1, 2010, and June 26, 2023. We specifically targeted randomized controlled trials that examined the impact of peer- or professional-led interventions on enhancing adherence to WMDs among individuals aged 60 years and older residing in the community. Two independent reviewers extracted data from the included studies and assessed the potential risk of bias in accordance with the Cochrane Risk of Bias tool for randomized trials, version 2. RESULTS: A total of 10,511 studies were identified through the database search. Eventually, we included 3 randomized controlled trials involving 154 community-dwelling older adults. The participants had a mean age of 65 years. Our review revealed that increasing awareness of being monitored and implementing the SystemCHANGE approach, a habit change tool focusing on personal goals and feedback, were effective strategies for enhancing adherence to WMDs among older adults. All of the included studies exhibited a low risk of bias. CONCLUSIONS: By collaboratively designing specific goals related to WMDs with health care professionals, including nurses and physicians, older adults exhibited a higher likelihood of adhering to the prescribed use of WMDs. These goal-setting tools provided a framework for structure and motivation, facilitating the seamless integration of WMDs into their daily routines. Researchers should prioritize interventions that target awareness and goal-setting as effective approaches to enhance adherence to WMDs among older adults, thereby maximizing the realization of associated health benefits.

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Shoulder pain represents the most frequently reported musculoskeletal disorder, often leading to significant functional impairment and pain, impacting quality of life. Home-based rehabilitation programs offer a more accessible and convenient solution for an effective shoulder disorder treatment, addressing logistical and financial constraints associated with traditional physiotherapy. The aim of this systematic review is to report the monitoring devices currently proposed and tested for shoulder rehabilitation in home settings. The research question was formulated using the PICO approach, and the PRISMA guidelines were applied to ensure a transparent methodology for the systematic review process. A comprehensive search of PubMed and Scopus was conducted, and the results were included from 2014 up to 2023. Three different tools (i.e., the Rob 2 version of the Cochrane risk-of-bias tool, the Joanna Briggs Institute (JBI) Critical Appraisal tool, and the ROBINS-I tool) were used to assess the risk of bias. Fifteen studies were included as they fulfilled the inclusion criteria. The results showed that wearable systems represent a promising solution as remote monitoring technologies, offering quantitative and clinically meaningful insights into the progress of individuals within a rehabilitation pathway. Recent trends indicate a growing use of low-cost, non-intrusive visual tracking devices, such as camera-based monitoring systems, within the domain of tele-rehabilitation. The integration of home-based monitoring devices alongside traditional rehabilitation methods is acquiring significant attention, offering broader access to high-quality care, and potentially reducing healthcare costs associated with in-person therapy.

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Blood glucose monitoring constitutes a pivotal element in the clinical management of Type 1 diabetes (T1D), a globally escalating metabolic disorder. Continuous glucose monitoring (CGM) devices have demonstrated efficacy in optimizing glycemic control, mitigating adverse health outcomes, and augmenting the overall quality of life for individuals afflicted with T1D. Recent progress in the field encompasses the refinement of electrochemical sensors, which enhances the effectiveness of blood glucose monitoring. This progress empowers patients to assume greater control over their health, alleviating the burdens associated with their condition, and contributing to the overall alleviation of the healthcare system. The introduction of novel medical devices, whether derived from existing prototypes or originating as innovative creations, necessitates adherence to a rigorous approval process regulated by the Food and Drug Administration (FDA). Diverse device classifications, stratified by their associated risks, dictate distinct approval pathways, each characterized by varying timelines. This review underscores recent advancements in blood glucose monitoring devices primarily based on electrochemical sensors and elucidates their regulatory journey towards FDA approval. The advent of innovative, non-invasive blood glucose monitoring devices holds promise for maintaining stringent glycemic control, thereby preventing T1D-associated comorbidities, and extending the life expectancy of affected individuals.

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Cardiovascular complications are a major cause of morbidity and mortality after surgery, necessitating adequate and thorough preoperative risk stratification and screening. Several technological advances in cardiac remote monitoring have improved the assessment and diagnosis of cardiovascular disease in patients before and after surgery. These devices perform measurements of physiological function, including vital signs, and more advanced functions, such as electrocardiograms and heart sound recordings. Some of the currently available devices include Fitbit® (Google LLC, Mountain View, CA, USA), BodyGuardian® (Preventive Inc., Rochester, MN, USA), ZephyrTM Performance Systems (Zephyr Inc., Annapolis, MD, USA), Sensium® (The Surgical Company, Amersfoort, UT, The Netherlands), KardiaMobile® (AliveCor, Mountain View, CA, USA), Coala® Heart Monitor (Coala Life Inc., Uppsala, Sweden), Smartex® Wearable Wellness System (Smartex, Porto, LX, Portugal), Eko® CORE and DUO (Eko Health, Emeryville, CA, USA), and TytoCareTM (TytoCare Ltd., New York, USA). Early studies have applied these devices to asymptomatic individuals and those with known cardiovascular disease with good sensitivity and specificity for electrophysiologic diagnosis. These devices carry several technical and other limitations, somewhat restricting the generalization of their use to all patients. However, information gathered from these devices can further guide anesthetic technique, operative timing, and postoperative follow-up, among other variables. As telehealth becomes more prevalent and comprehensive, it is paramount for the perioperative physician to be familiar with the available cardiac remote monitoring technologies.

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The fertility tracking of menstrual cycles during perimenopause with a quantitative hormone monitor is a novel undertaking. Women in regular menstrual cycles have been tracking their fertility using different biomarkers since the 1960's. Presently, there are newer electronic hormonal devices used to track fertility that provide more exact and objective data to help delineate the fertile time frame of a woman's cycle. These devices measure quantitative levels of estrogen, the luteinizing hormone, progesterone, and follicle-stimulating hormone, all of which occur at varying levels during the menstrual cycle. As women advance toward menopause, their cycles vary in length, and their hormones fluctuate. In this retrospective analysis, forty-two women aged 40 to 50 tracked their cycles over time, and eight of these forty-two women used the quantitative hormonal device. With the use of this device, the perimenopausal period has revealed distinct hormonal cycle characteristics that are unique to this group of women. It is the purpose of this paper to discuss these cycle's characteristics during perimenopause, which were found with the use of the quantitative hormonal device.

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Standard pulse oximeters estimate arterial blood saturation (SaO2) non-invasively by emitting and detecting light of a specific wavelength through a cutaneous vascular bed, such as a digit or the ear lobe. The quantity measured at these peripheral sites is designated as oxygen saturation (SpO2). Most reliable pulse oximeters are calibrated from measurements of healthy volunteers using some form of oxygen desaturation method. As the degree of inducible hypoxemia is limited, the calibration below achievable desaturation levels is usually extrapolated, leading to potential measurement error at low SaO2 values, especially in highly pigmented skin. Such skin color-related errors (SCRE) are the topic of this scoping review. Specifically, this study aimed to identify the combined impact of skin color and reduced SaO2 on the non-invasive assessment of SpO2 and report the consequences of potential inaccuracies. Three databases were searched (Cumulated Index to Nursing and Allied Health Literature (CINAHL), PubMed, and Web of Science) for peer-reviewed prospective and retrospective studies published in English between 2000 and 2022 involving human patients with hypoxemia that included a measure of skin color (Fitzpatrick scale or race/ethnicity). Ten studies met the criteria and were included in the final review. Eight of these studies reported statistically significant higher pulse oximeter readings in darker-skinned patients with hypoxia compared to their arterial blood gas measurements. Occult hypoxia was more prevalent in Black and Hispanic patients than in White patients. Minority patients overall (Black, Asian, and American Indian) were more likely to have a SaO2 < 88% that was not detected by pulse oximetry (occult hypoxemia) during hospitalization. With greater levels of hypoxemia, the differences between SpO2 and SaO2 were greater. If SaO2 was < 90%, then SpO2 was overestimated in all ethnicities but worse in minorities. In conclusion, the bias found in pulse oximeter readings in the skin of color broadly impacts patients with hypoxemia. The failure of SpO2 measuring devices to detect occult hypoxemia can delay the delivery of life-saving treatment to critically ill patients requiring respiratory rehabilitation and supplemental oxygen therapy. This may lead to adverse health outcomes, increased in-hospital mortality, and complications such as organ dysfunction. An improvement in pulse oximeter detection mechanisms that would include all skin pigmentations is therefore much desired to optimize individual healthcare status and minimize disparities in treatment.

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OBJECTIVE: Invent a simulator which provides a simulation of heart rate and respiratory rate to the intelligent sleep monitoring devices based on precision pressure sensors. METHODS: The simulator was composed of control part and simulated silicone doll. The simulated silicone doll contains heartbeat simulator and breathing simulation airbag. Heartbeat and breathing combination pressure signal can be produced according to frequency set values. Frequencies of pressure signal of the simulator were compared with the monitoring results of intelligent sleep monitoring devices with known accuracy to verify the frequency accuracy of pressure signal of the simulator. Verified the repeatability and stability of the simulator with a stopwatch. RESULTS: The heart rate of the simulator was with in ±2 beats per minute of the monitoring results of intelligent sleep monitoring devices and the respiratory rate of the simulator was with in ±2 times per minute of the monitoring results. The repeatability and stability of the simulator was better than ±5% according to results with a stopwatch. CONCLUSIONS: It's practicable to use the simulator which provides a simulation of heart rate and respiratory rate to the accuracy test of the intelligent sleep monitoring devices based on precision pressure sensor.

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BACKGROUND: The detection of subclinical/silent atrial fibrillation (SAF) in the general population is of the utmost importance, given its potential adverse consequences. Incident AF has been observed in 30% to 70% of patients with implanted devices, but its prevalence may indeed be lower in the general population. The prospective, multicentric, observational Silent Atrial Fibrillation ANCE Research Initiative (SAFARI) study aimed at assessing the SAF prevalence in a real-world outpatient setting by the means of a small, wearable, prolonged ECG Holter monitoring (>5 days) device (CGM HI 3-Lead ECG; CGM TELEMEDICINE, Piacenza, Italy). METHODS: Patients ≥ 55 years of age at risk for AF were screened according to the inclusion criteria to undergo prolonged 3-lead ECG Holter monitoring. SAF episodes were classified as follows: Class A, <30 s; Class B, 30 to 299 s; and Class C, ≥300 s. RESULTS: In total, 119 patients were enrolled (64 men; median age 71 (IQR 55-85) years). At a median of 13.5 (IQR 5-21) days of monitoring, SAF episodes were found in 19 patients (16%). A total of 10,552 arrhythmic episodes were registered, 6901 in Class A (n = 7 patients), 2927 in Class B (n = 3), and 724 in Class C (n = 9), (Class A vs. B and C, p < 0.001). This latter group had multiple (all-class) episodes, and two patients had >1000 episodes. There were no clinical, echocardiographic, or laboratory findings able to discriminate patients with SAF from those in sinus rhythm in univariate and multivariable analyses; of note is that the Class C patients showed a higher diastolic blood pressure, resting heart rate, and indexed LA volume. CONCLUSIONS: Over a median of 13 days of Holter monitoring, the SAFARI study confirmed the usefulness of small wearable devices in detecting SAF episodes in real-world outpatients at risk for, but with no prior history of, AF.

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Introduction: Various neurological conditions can impair hand function. Affected individuals cannot fully participate in activities of daily living due to the lack of fine motor control. Neurorehabilitation emphasizes repetitive movement and subjective clinical assessments that require clinical experience to administer. Methods: Here, we perform a review of literature focused on the use of hand-worn devices for rehabilitation and assessment of hand function. We paid particular attention to protocols that involve brain-computer interfaces (BCIs) since BCIs are gaining ground as a means for detecting volitional signals as the basis for interactive motor training protocols to augment recovery. All devices reviewed either monitor, assist, stimulate, or support hand and finger movement. Results: A majority of studies reviewed here test or validate devices through clinical trials, especially for stroke. Even though sensor gloves are the most commonly employed type of device in this domain, they have certain limitations. Many such gloves use bend or inertial sensors to monitor the movement of individual digits, but few monitor both movement and applied pressure. The use of such devices in BCI protocols is also uncommon. Discussion: We conclude that hand-worn devices that monitor both flexion and grip will benefit both clinical diagnostic assessment of function during treatment and closed-loop BCI protocols aimed at rehabilitation.

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INTRODUCTION: Patients with periodontitis are significantly more likely to have undetected diabetes mellitus (DM). Self­monitoring devices like glucometers provide a simple method for rapid monitoring of the glucose level in blood by utilizing a blood sample from the finger, but this method requires puncturing to obtain blood. Bleeding from the gingival sulcus, obtained during oral hygiene examination, can be utilized for screening DM patients. Therefore, this study was performed with the aim of determining the efficacy of gingival crevicular blood as a non-invasive screening method for DM patients, as well as correlating and comparing gingival crevicular blood glucose (GCBG) levels with finger capillary blood glucose (FCBG) and fasting blood glucose (FBG) among non-diabetic and diabetic group patients. METHODS: In this cross-sectional comparative study, a total of 120 participants having moderate to severe gingivitis/periodontitis with an age range of 40 to 65 years were divided into two groups on the basis of FBG range taken from an antecubital vein: non-diabetic (≤126, n=60) and diabetic (≥126, n=60) groups. Blood oozing during the routine periodontal examination from the periodontal pocket was recorded using a test strip of a glucose self-monitoring device (AccuSure®Simple) as GCBG. Concomitantly FCBG was collected from the fingertip. These three parameters were statistically analyzed using the Student's t-test and the one-way ANOVA test and correlated with Pearson's correlation coefficient for both groups. RESULTS: The mean and standard deviation for the three parameters GCBG, FBG, and FCBG were 93.78±12.03, 89.98±13.22, and 93.08±15.56, respectively, for the non-diabetic group and 154.52±45.05, 159±47.00, and 162.23±50.60 subsequently for the diabetic group. Comparing glucose level parameters among the non-diabetic and diabetic groups suggests a significant difference with the p-value <0.001*(inter-group). ANOVA test was done for both groups suggesting no significant difference among these three methods of measuring blood glucose level, where the p-value found was 0.272 for the non-diabetic and 0.665 for the diabetic group (intra-group comparison). Pearson's correlation values suggested a good positive correlation for the non-diabetic group, with parameters GCBG and FBG (r=0.864), GCBG and FCBG (r=0.936), and FBG and FCBG (r=0.837). The diabetic group's Pearson's correlation suggested a highly significant positive correlation between three different methods in which GCBG and FBG (r=0.978), GCBG and FBG (r=0.977), and FBG and FCBG (r= 0.982). CONCLUSION: Blood oozing from the periodontal pocket during routine oral hygiene examination can be utilized by dental healthcare professionals to screen pre-diabetic patients which can be used as a simple and less invasive method for DM patients.

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BACKGROUND: Artificial intelligence (AI) enables remote patient monitoring (RPM) which reduces costs by triaging patients to optimize hospitalization and avoid complications. The FDA regulates AI in medical devices and aims to ensure patient safety, effectiveness, and transparent AI solutions. OBJECTIVES: Identify and summarize FDA approved RPM devices to provide information for the US medical device industry based on previous approvals and the markets' needs. METHODS: We searched publicly available databases on FDA-approved RPM devices. Selection criteria were established to classify a solution as AI. Technical information was analyzed on pre-identified 16 parameters for the qualified solutions. RESULTS: A total of 47 RPM devices were reviewed, among which 12.8% were classified as a De Novo product and the remaining devices fell under the 510(K) FDA category. The cardiovascular (74%) AI RPM solutions dominated the US market, followed by ECG-based arrhythmia detection algorithms (59.4%), and Hemodynamics and Vital Sign monitoring algorithms (21.9%). The trend observed in the FDA rejected devices was their inability to be classified into clinically relevant categories (Criteria 2 and 3). CONCLUSION: The market needs more innovative RPM solutions under the De Novo category, as there are very few. The transparency is low on the technical aspect of AI algorithms. The market needs AI algorithms that can effectively classify patients rather than merely improve device functionality.

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A lot of mileage has been made recently on the long and winding road toward seizure forecasting. Here we briefly review some selected milestones passed along the way, which were discussed at the International Conference for Technology and Analysis of Seizures-ICTALS 2022-convened at the University of Bern, Switzerland. Major impetus was gained recently from wearable and implantable devices that record not only electroencephalography, but also data on motor behavior, acoustic signals, and various signals of the autonomic nervous system. This multimodal monitoring can be performed for ultralong timescales covering months or years. Accordingly, features and metrics extracted from these data now assess seizure dynamics with a greater degree of completeness. Most prominently, this has allowed the confirmation of the long-suspected cyclical nature of interictal epileptiform activity, seizure risk, and seizures. The timescales cover daily, multi-day, and yearly cycles. Progress has also been fueled by approaches originating from the interdisciplinary field of network science. Considering epilepsy as a large-scale network disorder yielded novel perspectives on the pre-ictal dynamics of the evolving epileptic brain. In addition to discrete predictions that a seizure will take place in a specified prediction horizon, the community broadened the scope to probabilistic forecasts of a seizure risk evolving continuously in time. This shift of gears triggered the incorporation of additional metrics to quantify the performance of forecasting algorithms, which should be compared to the chance performance of constrained stochastic null models. An imminent task of utmost importance is to find optimal ways to communicate the output of seizure-forecasting algorithms to patients, caretakers, and clinicians, so that they can have socioeconomic impact and improve patients' well-being.

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