Principles Of Theory Research Articles

Exploring Web-Based Support for Suicidal Ideation in the Scottish Population: Usability Study.

Suicide is a global health concern. In the United Kingdom, Scotland has the highest suicide rate. Lived experience and suicide prevention stakeholders in Scotland have identified a key gap in suicide prevention activities: the lack of 24-hour peer-driven web-based support for people who are suicidal. This usability study aimed to evaluate the feasibility, acceptability, utility, and reach of a suicide prevention website (Surviving Suicidal Thoughts) specifically designed to support residents in Scotland who are experiencing suicidal thoughts themselves or suspect or know someone who is experiencing suicidal thoughts. Intended support was delivered through the provision of personal testimony videos of individuals with lived experience. A peer-driven website was developed specifically to support residents of Scotland experiencing suicidal thoughts. The website included resources (eg, videos from lived experience and written guidance about how to respond to someone who may be experiencing suicidal thoughts) to help reduce distress, normalize experiences, and challenge distressing thoughts. The website was promoted via leading web-based social media channels and Google Ads. Evaluation of the website was based on website engagement, marketing strategy, and direct web user feedback via a cross-sectional survey. Data were collected for 41 weeks (June 2022 to February 2023) spanning the launch of the website and the conclusion of the second marketing campaign. On average, the website received 99.9 visitors per day. A total of 56% (n=14,439) of visitors were female, ages ranged from younger than 18 years to older than 70 years (commonly between 25 and 34 years) and originated from all regions of Scotland. According to Google Search terms of Scottish residents, of the individuals indicated to be experiencing suicidal thoughts but not looking for help, 5.3% (n=920) engaged with the website compared to 10.5% (n=2898) who were indicated to be looking for help for themselves. Based on participant responses to the evaluation survey (n=101), the website was associated with a significant reduction in suicidal thoughts (P=.03). Reasons for visiting the website varied. Marketing data implied that people were more likely to engage with advertisements, which they felt were more personal, and visitors to the website were more likely to engage with videos, which corresponded to their age. A peer-led website may help residents of Scotland who are experiencing suicidal thoughts. Web-based interventions may have considerable reach in Scotland both in terms of age and geographic area. Engagement with the website was similar to other self-help websites for suicidal ideation; however, more nuanced methods of analyzing website engagement for help-seeking behavior are recommended. Future work would benefit from exploring the effectiveness of this website based on a larger participant sample with website modifications guided by the principles of social learning theory.

Chiral and Quantum Plasmonic Sensors: New Frontiers in Selective and Ultra-Sensitive Sensing.

Surface Plasmon Polaritons (SPPs) and Localized Surface Plasmon Resonances (LSPRs) are fundamental phenomena in plasmonics that enable the confinement of electromagnetic waves beyond the diffraction limit. This confinement results in a significant enhancement of the electric field, making this phenomenon particularly beneficial for sensitive detection applications. However, conventional plasmonic sensors face several challenges, notably their difficulty in distinguishing chiral molecules, which are vital in drug development. Furthermore, these sensors exhibit sensitivity issues and energy losses, leading to broader resonance peaks and diminished signal-to-noise ratios. Recent research has concentrated on integrating chirality and quantum effects in plasmonics to overcome these limitations. Particularly, the development of plasmonic sensors with exceptional sensitivity and precision at scales smaller than the diffraction limit. This review assesses the latest advancements in chiral and quantum plasmonic sensing technologies. The first section details the theory and operational principles of conventional sensors based on SPPs and LSPRs. The second section discusses recent developments in chiral plasmonic sensors, while the third section focuses on plasmonic quantum sensing, highlighting contemporary findings. Specifically, this section emphasizes quantum-enhanced sensing techniques that mitigate shot noise, a significant barrier to single-molecule detection. The concluding section summarizes the review and identifies potential future research directions.

Supporting vision-language model few-shot inference with confounder-pruned knowledge prompt.

Vision-language models are pre-trained by aligning image-text pairs in a common space to deal with open-set visual concepts. Recent works adopt fixed or learnable prompts, i.e., classification weights are synthesized from natural language descriptions of task-relevant categories, to reduce the gap between tasks during the pre-training and inference phases. However, how and what prompts can improve inference performance remains unclear. In this paper, we explicitly clarify the importance of incorporating semantic information into prompts, while existing prompting methods generate prompts without sufficiently exploring the semantic information of textual labels. Manually constructing prompts with rich semantics requires domain expertise and is extremely time-consuming. To cope with this issue, we propose a knowledge-aware prompt learning method, namely Confounder-pruned Knowledge Prompt (CPKP), which retrieves an ontology knowledge graph by treating the textual label as a query to extract task-relevant semantic information. CPKP further introduces a double-tier confounder-pruning procedure to refine the derived semantic information. Adhering to the individual causal effect principle, the graph-tier confounders are gradually identified and phased out. The feature-tier confounders are eliminated by following the maximum entropy principle in information theory. Empirically, the evaluations demonstrate the effectiveness of CPKP in few-shot inference, e.g., with only two shots, CPKP outperforms the manual-prompt method by 4.64% and the learnable-prompt method by 1.09% on average.

Bringing Historical Management Theories to Life: An Experiential Exercise Using Generative AI

Foundational management theories, such as the Principles of Scientific Management, Bureaucratic Management, or Systems Theory, provide frameworks for understanding and organizing the extensive body of management knowledge. Despite their significance, students often find it difficult to grasp and apply historical concepts in today’s workplace. In this experiential exercise, we use generative artificial intelligence (AI) to create an interactive chatbot through which students “interview” historical figures. Through this exercise, students achieve four key learning objectives: (a) demonstrating a critical understanding of historical management frameworks; (b) analyzing how historical, social, and economic contexts influenced management thinking; (c) evaluating the applicability of historical management frameworks to contemporary business settings; and (d) critically analyzing and interpreting information generated by AI tools to enhance AI literacy. The activity includes tailored open-access chatbots and resources to assist these learning outcomes across various class formats.

Bayes Theorem in Machine Learning: A Literature Review

In the era of big data and articial intelligence, machine learning has become a crucial tool for extracting insights and making predictions across various domains. Bayes theorem, a fundamental principle in probability theory, has emerged as a cornerstone in many machine learning algorithms. This literature review explores the main applications of Bayes theorem in machine learning, focusing on its role in classication, Natural Language Processing (NLP), and other emerging elds. The study aims to provide an overview of how Bayesian principles enhance learning algorithms, improve decision-making processes, and address complex problems in articial intelligence. Through a systematic review of academic papers from Google Scholar, this research synthesizes current knowledge on Bayesian methods in machine learning. The methodology involves dening the research scope, conducting a literature search using specic keywords, screening relevant studies, and analyzing the collected data. By examining diverse applications ranging from disease prediction to sentiment analysis, this review highlights the versatility and signicance of Bayes theorem in advancing machine learning techniques and their real-world implementations.

Perceptions of Fairness of Support Between Older Parents and Adult Children

Increased life expectancy and reduced fertility mean more generations are living simultaneously but with fewer members. There is also a growing group of older people (aged 80 and over) who need care and support. This impacts mutual support within families and the care provided by public or private care organisations. Across OECD countries, on average, 60% of people aged 65 years and older in 2020 reported receiving support from family members, friends and people in their social network, living inside or outside their household but not care organisations. European research shows that when older persons do not have a partner (anymore), they rely on their adult children for care and support. Given that adult children frequently serve as primary providers of informal care, our study examines their perspectives and motivations to provide future care alongside the demands and expectations of their old parents. Our study adopts a multi-actor interview approach and simultaneously looks at the perspective of 40 adult children and one of their older aged parents (65 years or older). We apply the distributive justice theory to understand how children and parents assess the expectation and fairness of support. This paper contributes to the existing literature about support behaviour between parents and children, expanding insights about the fairness of support, expectations and willingness from a multi-actor approach. Through the lens of child–parent dyads, it is seen that the principles of the distributive justice theory can be perceived as not so strict, and within family relationships, one or more principles can coexist and have underlying mechanisms. This study shows the complexity and often ambivalence of family solidarity by adopting a multi-actor approach. One of the main findings is that contrasting dyads who reject the reciprocal act of support experience feelings of guilt or misunderstanding, resulting in stress and worry. A child may not follow the expected support pattern from the parent due to competing demands such as work or the prioritisation of young children, which can reduce the support given to the older parent. Besides general contrasts and similarities between child–parent support perspectives, the analysis looked into differences regarding gender and legal relationships. Our findings only found gendered care expectations. Future research should entangle this by looking into feelings of closeness, emotional connection and considering the dynamic character of filial support over time, especially between siblings.

From Newcomer to Educator: A Journey of Transformative Onboarding

The paper delves into the transformative onboarding practices essential for successfully integrating new teachers into higher education institutions. Integration of the principles of organizational socialization and transformative learning theories underscores the significance of a structured and supportive onboarding process. The paper argues that a comprehensive approach, including mentorship, targeted professional development, and a culture that encourages reflection and dialogue, is vital for new teachers’ professional growth and institutional engagement. It concludes that effective onboarding not only facilitates a smooth transition for new teachers but also enriches the academic environment, fostering a community of continuous learning and innovation.

A Structured, Anatomy-Based Chest CT Interpretation Curriculum for Pulmonary Fellows Covering the Main Patterns of Parenchymal Lung Disease.

Chest computed tomography (CT) interpretation is a key competency for pulmonary fellows, with many resources intended for radiologists but very few for this specific group. We endeavored to create a curriculum to teach chest CT interpretation to first-year pulmonary fellows. We assembled a team of two pulmonologists, one radiologist, and a fellow with computer drafting software experience. We reviewed the literature, used principles of cognitive load theory to outline the content of our curriculum, collected original CT images exemplifying key patterns of disease, created original illustrations using computer drafting programs, and outlined frameworks to identify chest CT patterns and build differential diagnoses. We divided the material into five short videos and provided 18 practice cases to be reviewed asynchronously. We then organized a 1-hour in-person review session facilitated by a chest radiologist. We created a survey to assess our curriculum. The material presented here has been delivered to three consecutive classes of first-year pulmonary and critical care medicine fellows at our institution. Nineteen fellows in three cohorts reviewed the curriculum. Twelve fellows (63% response rate) completed the postcurriculum survey. Overall, there was a significant improvement in comfort, with the calculated paired sample t test showing a mean comfort of 3.2 precurriculum and a mean comfort of 4.5 postcurriculum (p < .001). This self-guided, interactive curriculum provides a structured approach connecting key lung anatomy to patterns of disease and is an effective way to teach chest CT interpretation to pulmonary fellows.

برنامج إرشادي قائم على النظرية السلوكية لخفض مستوى السلوك العدواني لدى أطفال الروضة

The study aimed to investigate the effectiveness of a counseling program based on behavioral theory in reducing aggressive behavior among preschool children. To achieve this, a quasi-experimental approach was employed. The study sample consisted of 30 children from kindergarten 36, affiliated with Primary School 213 in Jeddah. The participants were randomly divided into two groups: 15 children in the experimental group and 15 in the control group. The Aggressive Behavior Scale for Children, developed by Eman Maher Abdel Fattah (2023), was applied. Using standard statistical methods, the study revealed significant findings, most notably the effectiveness of the counseling program in reducing aggressive behavior. Statistically significant differences were observed at the level of 0.05 between the pre-test and post-test mean scores of the experimental group, favoring the post-test. Additionally, statistically significant differences at the level of 0.05 were found between the post-test mean scores of the experimental and control groups, favoring the experimental group.Based on these findings, it was recommended to conduct training workshops for teachers on utilizing behavioral theory principles to manage aggressive behavior. Furthermore, it was suggested to implement the program regularly and expand its application to various geographical areas and cultural contexts to ensure sustainable positive outcomes. The study also recommended the development of similar programs targeting other behaviors to promote positive behavior among preschool children, particularly after integrating them with early childhood stages.

Developing and testing the feasibility of a theory-based brief counseling intervention to promote physical activity in breast cancer survivors enrolled in the PAC-WOMAN trial

BackgroundDespite the benefits of physical activity (PA), cancer survivors report engagement barriers, and existing interventions often lack comprehensive solutions. Theory-based interventions using evidence-based behavior change techniques (BCTs) have been shown to be effective in promoting PA for breast cancer survivors, although their feasibility and acceptability lack evidence. The PAC-WOMAN trial is a three-arm randomized controlled trial aimed at promoting short- and long-term PA and improving the quality of life of breast cancer survivors. This study describes the development of a brief counseling theory-based motivational intervention from the PAC-WOMAN trial, assessing its feasibility and acceptability.MethodsA broad search of theory-based interventions for people with chronic diseases was conducted. Key strategies from each intervention helped shape the main components and BCTs used in the eight bimonthly sessions of the PAC-WOMAN brief counseling intervention, which was based on self-determination theory principles and aimed at empowering participants to develop self-regulation resources for PA through basic psychological needs satisfaction. A toolkit and manuals for intervention facilitators and participants were developed. A feasibility study was conducted to monitor implementation fidelity, acceptability, adherence, and participants’ experiences (via a focus group).ResultsTwelve women (mean age 55.9 ± 6.7 years) participated. Implementation monitoring indicated that the intervention was feasible. The attrition rate was 25%. Focus-group discussion suggested that weekly sessions would increase attendance, highlighted the helpfulness of self-monitoring and the importance of role models for PA, and identified the session on safely exercising at home as key in improving PA levels.ConclusionsThis research aims to enhance systematic reporting in intervention development by detailing the specific BCTs used, translating them into implementation strategies, providing comprehensive resources for facilitators/participants, and supporting the implementation, dissemination, and adoption of a theory-based intervention informed by previous research. Feasibility testing suggests that the intervention was well accepted by participants and feasible, although it could benefit from adjustments in format to increase compliance.Trial registrationNCT05860621, registered 20 April 2023 — retrospectively registered, https://clinicaltrials.gov/study/NCT05860621. Registered 21 April 2023 — retrospectively registered, https://doi.org/10.17605/OSF.IO/ZAQ9N. UMIN000050945, registered 27 April 2023 — retrospectively registered, https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000058070.

The Role of Algal Symbiont Growth in Driving the Thermal Responses of a Widespread Photosymbiotic Ciliate

Understanding the impacts of climate change on ecosystems remains a major contemporary research theme in the biosciences. However, the role of mixotrophs, organisms that combine autotrophic and heterotrophic processes to grow and reproduce, as important determinants of the thermal responses of ecosystems and their services is largely unresolved. In particular, photosymbioses, ubiquitous mixotrophic associations in which autotrophs reside within heterotrophic hosts, are known to play key roles in global biodiversity and carbon cycling. While specific impacts, particularly in the coral-zooxanthellae interaction, are thoroughly documented, ecologists lack a general theoretical framework describing the impacts of temperature change on photosymbiotic interactions. Here, I apply principles of the metabolic theory of ecology to assess the metabolic basis of the temperature-induced disruption of photosymbiosis in the microbial &lt;i&gt;Paramecium bursaria - Chlorella&lt;/i&gt; spp. association. In contrast to the general prediction that net autotrophy should decrease with temperature, this microbial photosymbiosis harboured larger algal symbiont populations and consumed fewer prey with warming, suggestive of increased net autotrophy with warming - a pattern that held across strains isolated from three different continents. This observation appeared to be a simple consequence of the response of symbiont growth rate. I conclude that a metabolic framework for photosymbiosis may prove insightful, but the ecological dynamics of the associations (e.g. mixotrophic strategy) must be considered in tandem.

Free vibration and buckling analysis of axially functionally graded tapered Timoshenko beams using B-spline-based isogeometric analysis.

This study considers Timoshenko beam theory and the isogeometric analysis method to investigate the free vibration and buckling of axially functionally graded (AFG) tapered beams. The governing equations are obtained from the kinematic assumptions of Timoshenko beam theory and Hamilton's principle. The isogeometric analysis approach is implemented to solve the motion equations. One-dimensional B-spline basis functions are used to estimate the displacement field, describe the geometry, and illustrate the deformed shapes of the beam. Due to suffering the isogeometric approach from the shear locking phenomenon, the selectively reduced integration is applied. It is shown that this method can mitigate the effect of shear locking. In this attempt, the effect of material non-homogeneity parameters, mass density, Young's modulus, and taper ratio on the critical buckling loads and natural frequencies are considered for various boundary conditions. Several numerical examples show the accuracy and reliability of this method. The obtained results are in accord with the ones in the related articles and can be adopted as future reference solutions.

Vanadium dioxide-based tunable broadband metamaterial absorber in the terahertz

Abstract This study presents a three-layer broadband absorber comprising a vanadium dioxide (VO2) layer at the top, a polytetrafluoroethylene layer in the middle, and a gold film at the bottom. Absorption curves were calculated using the multiple-reflection principle and impedance matching theory, and the obtained results were consistent with the simulation results. According to simulation results, within the range of controllable conductivity of VO2, the absorption rate of the as-developed structure varied from 1.5% to 99.8%, with the bandwidth extending from 0 THz to 5.19 THz. The metamaterial maintained &gt;75% absorption across the frequency band for incident angles up to 45°, with the absorption rate varying for different polarization angles. The as-developed metamaterial exhibited the characteristics of wide-angle incidence and polarization sensitivity and has excellent application prospects in the domains of medicine, military, and communication.

Coach Assist: Assessing Youth Basketball Coaches’ Feedback on Participation in an Acceptance and Commitment Therapy-Based Intervention Incorporating Self-Determination Theory Principles

This paper introduces a pioneering intervention program based mainly on Acceptance and Commitment Therapy, designed to address the multifaceted challenges faced by sports coaches. In order to provide a more comprehensive intervention that bolsters coaches’ intra- and interpersonal skills, principles from Self-Determination Theory have been integrated as a complementary framework. The program was nationally implemented across 32 youth basketball clubs, engaging 172 coaches. These coaches participated in a four-session series, focusing on diverse facets including value exploration, awareness of behavioral functions (“choice point”), self-regulation techniques, and strategies to meet athletes’ basic psychological needs. Out of these, 108 coaches from 26 participating clubs filled out the online feedback form at the end of the intervention, highlighting their experiences, benefits, and areas of improvement within the program. Coaches’ feedback indicated that the program furnished an effective framework for sports coaching, suggesting enhancements in coaches’ abilities to navigate their challenges. Practical recommendations have been administered based on the coaches’ feedback.

Existence and multiplicity results for non-autonomous second-order Hamiltonian systems

Abstract In this article, using the least action principle and minimax methods in critical point theory, some existence and multiplicity results for periodic solutions of second-order Hamiltonian systems are obtained.

A Study of Two-Wheel Self-Balancing Robot Dynamics for Control Systems Learning

The two-wheeled self-balancing robot (TWSBR), utilizing an inverted pendulum arrangement, exhibits dynamic stability while being statically unstable. Due to this behavior, the TWSBR system has been used to demonstrate fundamental principles of stability, nonlinear dynamics, and control theory. In this work, a computational study of the TWSBR was carried out to develop a mathematical model using Newtonian mechanics that serves as an educational tool in control education for demonstrating the impact of different control algorithms such as Proportional (P), ProportionalDerivative (PD), and Proportional-Integral-Derivative (PID) on system stability. The comparison of P, PD, and PID controllers was undertaken to demonstrate the practical advantages of each controller in improving the robot's stability and responsiveness. The PID controller was designed and optimized using the Root-locus techniques, with a damping ratio equal to 1 which exhibits a fast-settling time with minimum overshoots. When an impulse response was applied to the PID controller in the simulation environment it demonstrated system can reach a dynamic balance within 1.2 seconds demonstrating the effectiveness of the proposed PID controller. The optimal gain parameters K value and Kp, Ki, and Kd parameter values were determined using root-locus analysis, which allowed the system to operate with great stability and minimum settling time. These findings highlight the TWSBR's educational significance as a hands-on tool for teaching practical applications of control theory, as well as providing valuable insights into the design and optimization of control systems for dynamic balance tasks. This study emphasizes the relevance of control algorithms in achieving rapid and stable dynamic behaviors, making it a valuable learning resource for both students and instructors. Keywords: Two-wheeled self-balancing robot, Inverted pendulum, P, PD and PID controllers, Stability analysis, Control Education

Reviving functionalism: Applying translation-oriented text analysis to synthetic text (editing)

This paper investigates the potential application of translation-relevant text analysis. Rooted in the functionalist approach and Skopos theory, the translation-relevant text analysis is seen as instrumental in translation education for assessing the quality of synthetic text output for translation purposes (MT and/or AI) and improving (post-)editing performance relating to said output. Despite recent advancements in machine translation and the partially self-professed potential of AI models, accurately conveying the intended function of the target text remains a challenge in professional translation practices. This paper argues that salvaging functionalist theory can benefit both translator education and, ultimately, professional translation practices. To support this argument, three use cases are presented in which the key principles of functionalism and Skopos theory are applied to develop critical text analysis skills necessary for handling and editing synthetic text. Keywords: Functionalism, Translation Technology, Machine Translation, Generative Artificial Intelligence, Post-editing

Dynamic modeling of the Insulin-Glucose-Glucocorticoid impulsive control system

This paper introduces a class of insulin-glucose-glucocorticoid impulsive systems in the treatment of patients with diabetes to consider the effect of glucocorticoids. The existence and uniqueness of the positive periodic solution of the impulsive model at double fixed time is confirmed for type 1 diabetes mellitus (T1DM) using the function. Further, the global asymptotic stability of the positive periodic solution is achieved following Floquet multiplier theory and comparison principle. Additionally, the permanence of the system is confirmed in type 2 diabetes mellitus (T2DM) via the comparison theorem. Numerical analysis verifies the results of theoretical calculations and indicates that combining therapeutic strategies under hormonal interactions with the dose of exogenous insulin and glucocorticoid medicines within organisms provides more reasonable clinical strategies.

A qualitative exploration of the interaction between mental illness stigma and preparedness for practice in pharmacy students.

Mental illness stigma can result in discriminative practice in pharmacy, such as providing less pharmaceutical care to people living with mental illness (PMI) than those with physical illness. Pharmacy education should aim to reduce the impact of mental illness stigma on the pharmaceutical care of PMI. Whilst previous research has shown that some interventions can reduce stereotyping and prejudice in pharmacy students, the impact on subsequent discrimination is questionable and the reasons for successful and unsuccessful outcomes are unclear. This study aimed to explore pharmacy students' views on working with PMI and how these views might interact with mental illness stigma. Focus groups and semi-structured interviews with final year pharmacy students and recent graduates were conducted at one UK university. Question guides were developed based on the aim of the study and investigated participants' attitudes and beliefs about mental illness. Following transcription, data were analysed in line with the guiding principles of constructivist Grounded Theory. Three major categories were developed which accounted for the data: Knowing, Doing and Valuing. Participants reported that in common with the general public, pharmacy students possess insufficient knowledge about mental illness, which limits what can be done to help and support people living with it. Finally, participants reported that mental illness is ascribed insufficient value in the pharmacy curriculum, healthcare, and in wider society. Interactions between stigma and each of these categories were identified. The findings offer a novel, qualitative description and explanation of mental illness stigma among pharmacy students from one UK university. Further, the factors identified by pharmacy students as modifiers of preparedness for professional practice provide an evidence base for curriculum development with possible international relevance. This may help pharmacy educators to develop evidence-based strategies aimed at reducing the impact of mental illness stigma in future professional practice.

Algorithm for Detecting Reference Points on a Digital Electrocardiogram in Real Time

Relevance. The use of digital electrocardiographs and cardiac monitors with built-in algorithms for automatic processing, analysis and interpretation of electrocardiograms allows the doctor to effectively diagnose cardiac arrhythmias. It is known that in order to provide emergency care to a patient, the duration of arrhythmia diagnostics should not exceed several tens of seconds, which requires the emergence of new algorithms for detecting informative features indicating arrhythmia, operating in real time. The need to introduce new and effective technologies for diagnosing cardiovascular diseases is also reflected in public health development programmes.Research goal. Development and quality indicators analysis of the algorithm for reference points detection on a digital electrocardiogram, bearing informative signs for the procedure of arteries diagnosis.The methods used. The study is based on an analysis of existing approaches to the problem of reference points detection on digital electrocardiogram, as well as conducting a test of the proposed algorithms by mathematical modelling methods. The quality indicators of the algorithms defined in accordance with the principles of signal detection theory and diagnostic testing, at the junction of which the task of electrocardiogram reference point detection is located. The proposed algorithm was tested on materials of MIT-BIH Arrhythmia Database, which is widely used for verification and validation of real-time digital electrocardiogram signal processing algorithms.The results. The study proposes an algorithm for detecting reference points on a digital electrocardiogram that carry informative features for the arrhythmia diagnostic procedure. The proposed algorithm is based on digital signal filtering using a decision rule based on a three-step two-threshold principle of pre-processed electrocardiogram signal values comparison on a sliding window. An experiment on the materials of the open verified MIT-BIH Arrhythmia DB showed that the quality of the proposed algorithm for detecting reference points is higher than that of the algorithms used in modern digital electrocardiographs and cardiac monitors. The proposed algorithm based on digital signal filtering and the three-step two-threshold decision rule have elements of scientific novelty.The significance. The results of this work can be used in the development of digital heart rate monitors, cardiac devices and for automatic processing, analysis and real-time computer-assisted digital electrocardiogram signal interpretation.