Continuous Connectivity Research Articles

Assessing adherence to remote monitoring recommendations for cardiovascular implantable electronic devices: a retrospective analysis

Abstract Background The recently published Expert Consensus Statement on the Practical Management of Remote Device Clinic offers evidence-based recommendations for managing patients with cardiovascular implantable electronic devices (CIEDs). Purpose This study evaluates adherence to remote monitoring (RM) recommendations in current clinical practice using data from a RM database. Methods According to RM guidelines, patient connectivity should be maintained. If continuous connection is ensured, it is reasonable to schedule in-person visits every 24 months, with alert-based RM potentially replacing structured intermittent device follow-up. Data from 6553 CIED patients followed on the LATITUDE (Boston Scientific) remote network at 26 Italian centers between 2010 and 2023 were analyzed. Median RM duration was 40 months (25th-75th percentile: 23-67). Results Enrollment of patients at centers significantly increased over the observation period (Figure). As of the January 2024 data extraction, 4723 patients had transmitted data in the last 12 months. Among these, 639 (14%) were NOT MONITORED (i.e. interrupted connectivity), with no significant differences among CIED types (Pacemaker: 13%; ICD: 12%; CRT-P: 7%; CRT-D: 13%; S-ICD: 18%). Scheduled device transmissions occurred at least once every 3 months in 96% of patients. The volume of in-office device interrogations and remote transmissions is detailed in Figure. In 2023, among the 4084 MONITORED patients, 6600 in-office device interrogations were conducted, and 64296 remote transmissions were reviewed. Of these, 34267 (53%) were scheduled, 15091 (24%) were patient-initiated, and only 14938 (23%) were triggered by alerts. Conclusions In current clinical practice, RM adoption is increasing, alongside the volume of in-office and remote visits. Solutions must be implemented to ensure transmission continuity in a substantial percentage of patients. Additionally, there persists a significant reliance on frequent scheduled transmissions and in-office visits. Centers stand to gain from implementing the guideline-recommended alert-based RM strategy, reducing the considerable burden of nonactionable remote and in-office visits among patients with continuous connectivity.

Developed Internet of Vehicles Architecture: Communication, Big Data and Route Determination Perspectives

Internet of vehicles (IoV) has become an important research topic due to its direct effect on intelligent transportation systems (ITS) development. There are many challenges in the IoV environment, such as communication, big data and best route assigning. In this paper, an effective IoV architecture is proposed. This architecture has four main objectives. The first objective is to utilize a powerful communication scheme in which three tiers of coverage tools — Internet, satellite, high-altitude platform (HAP) — are utilized. Therefore, the vehicles maintain a continuous connection to the IoV environment everywhere. The second objective is to apply filtering and prioritization mechanisms to reduce the detrimental effects of IoV big data. The third objective is to assign the best route for a vehicle after determining its real-time priority. The fourth objective is to analyze the IoV data. The proposed architecture performance is measured using a simulation environment that is created by the NS-3 package. The simulation results proved that the proposed IoV architecture has a positive impact on the IoV environment according to the performance metrics: energy, success rate of route assignment, filtering effect, data loss, delay, usage of coverage tools and throughput.

Iowa Brain-Behavior Modeling Toolkit: An Open-Source MATLAB Tool for Inferential and Predictive Modeling of Imaging-Behavior and Lesion-Deficit Relationships.

The traditional analytical framework taken by neuroimaging studies in general, and lesion-behavior studies in particular, has been inferential in nature and has focused on identifying and interpreting statistically significant effects within the sample under study. While this framework is well-suited for hypothesis testing approaches, achieving the modern goal of precision medicine requires a different framework that is predictive in nature and that focuses on maximizing the predictive power of models and evaluating their ability to generalize beyond the data that were used to train them. However, few tools exist to support the development and evaluation of predictive models in the context of neuroimaging or lesion-behavior research, creating an obstacle to the widespread adoption of predictive modeling approaches in the field. Further, existing tools for lesion-behavior analysis are often unable to accommodate categorical outcome variables and often impose restrictions on the predictor data. Researchers therefore often must use different software packages and analytical approaches depending on whether they are addressing a classification vs. regression problem and on whether their predictor data correspond to binary lesion images, continuous lesion-network images, connectivity matrices, or other data modalities. To address these limitations, we have developed a MATLAB software toolkit that supports both inferential and predictive modeling frameworks, accommodates both classification and regression problems, and does not impose restrictions on the modality of the predictor data. The toolkit features both a graphical user interface and scripting interface, includes implementations of multiple mass-univariate, multivariate, and machine learning models, features built-in and customizable routines for hyper-parameter optimization, cross-validation, model stacking, and significance testing, and automatically generates text-based descriptions of key methodological details and modeling results to improve reproducibility and minimize errors in the reporting of methods and results. Here, we provide an overview and discussion of the toolkit features and demonstrate its functionality by applying it to the question of how expressive and receptive language impairments relate to lesion location, structural disconnection, and functional network disruption in a large sample of patients with left hemispheric brain lesions. We find that impairments in expressive vs. receptive language are most strongly associated with left lateral prefrontal and left posterior temporal/parietal damage, respectively. We also find that impairments in expressive vs. receptive language are associated with partially overlapping patterns of fronto-temporal structural disconnection, and that the associated functional networks are also similar. Importantly, we find that lesion location and lesion-derived network measures are highly predictive of both types of impairment, with predictions from models trained on these measures explaining ~30-40% of the variance on average when applied to data from patients not used to train the models. We have made the toolkit publicly available, and we have included a comprehensive set of tutorial notebooks to support new users in applying the toolkit in their studies.

A quantitative classification criterion for beam-to-column rigid connections in steel braced frames

As the key part of the force-transfer path in a steel frame, a reasonable modeling method of beam-to-column connections in the structural analysis model is crucial. From the designer’s perspective, a rational and accurate classification of beam-to-column connections is an invaluable basis for improving modeling efficiency and design accuracy. Although some investigations led by Eurocode 3 (EC3) have provided a systematic and quantitative approach for classifying beam-to-column connections, it is not sufficiently developed for general steel braced frames. In this paper, based on a modified analytical model of the beam-to-column connection substructure that accounts for the effect of braces, the rotational stiffness demand of the beam-to-column rigid connection is derived from the perspectives of structural lateral stiffness and stability. The quantitative relationship is established between the rotational stiffness demand and the relative stiffness of the braces. The accuracy and reasonability of the proposed analytical model and stiffness demand are verified using finite element models (FEMs) at both the story and structure levels. Particularly, the effect of the non-linear behavior of beam-to-column connections on the structural response under high-intensity earthquakes is further comparatively analyzed in the context of seismic design. The results demonstrate that, a beam-to-column connection can be modeled as a continuous rigid connection in non-linear analysis only if it simultaneously satisfies the following requirements: the rotational stiffness meets the demand proposed in this study, and the bending capacity is designed to be overstrength compared to the beam cross-section.

Celebrating the legacy and work of John Schulenberg: Answering the question "Does adolescence matter?"

Dr. John Schulenberg (1957-2023) was a brilliant and internationally recognized developmental scientist. In equal measure, he was an outstanding, dedicated, and generous mentor. Through his scholarship and mentorship, his impact on the fields of adolescent and substance use research will be deep and enduring. The overriding theme of his research was illuminating the importance of adolescence in the life course, which he referred to as "Taking the Long View" on adolescence. John's longstanding motivation for this was to answer the question: "Does adolescence matter?" This special issue, which (in addition to this introduction) includes 14 papers and 2 invited commentaries, is designed to honor his scholarship and impact. For this introduction to the special issue, we divide what it means to "Take the Long View" on adolescence into four major themes: (1) Turning points; (2) Developmental disturbances; (3) Continuity and long-term developmental connections; and (4) Heterogeneity in the age curve. We describe these four themes, consider how they connect with the overarching question "Does adolescence matter?," and discuss how the research papers included in this special issue are excellent examples of research inspired by these themes.

How do clients experience intensive EMDR for post-traumatic stress? An interpretative phenomenological analysis

BackgroundSeveral studies of the intensive delivery of Eye Movement Desensitization and Reprocessing (EMDR) have indicated it to be an effective treatment for Post-Traumatic Stress Disorder (PTSD), providing improved client experience, faster reduction in symptoms, greater symptom reduction, and reduced dropout rates as compared to non-intensive EMDR. However, there is a dearth of studies that describe this non-traditional approach to the delivery of EMDR psychotherapy from the patients’ perspective. ProcedureThis qualitative study explores the experiences of patients who undertook intensive EMDR for post-traumatic stress. Interviews were conducted with 10 participants and analysed using Interpretative Phenomenological Analysis (IPA). Main findingsThe data revealed two Personal Experiential Themes (PET) and four experiential statements. ‘The importance of psychological safety’ generated sub-themes of ‘A protected space’ and ‘The importance of a continued connection’. ‘The changing self’ generated two sub-themes of a ‘Wow! moment’, and ‘Living the way I always wanted’. ConclusionResults show that intensive EMDR can be experienced as safe, facilitating agency and engagement while affecting meaningful change.

Feasibility of a Cardiac Magnetic Resonance Protocol for "off-on" Cardiac Resynchronization Therapy Evaluation.

Cardiac resynchronization therapy (CRT) is a standard treatment for patients with heart failure and electrical dyssynchrony. Cardiac magnetic resonance (CMR) is the gold standard for assessing left ventricular (LV) function. However, the feasibility of using CMR with active CRT is still uncertain. To assess the feasibility of a CRT "off-on" protocol during CMR and measure the acute effects of CRT interruption on LV function. Patients underwent CMR before (pre-CRT) and 6 months after (post-CRT) an MR-conditional CRT defibrillator implantation. The post-CRT scan included two complete sets of cine images, one with inactive (post-CRTOFF) and one with active CRT (post-CRTON), maintaining a continuous connection between device and programmer. Out of 29 enrolled patients, 8 (28%) had complete and analyzable post-CRT data. Unsuccessful procedures were attributed to connection problems between the CRT device and the programmer (n = 10), poor image quality (n = 7), and lack of patient cooperation (n = 4). LV ejection fraction significantly increased between pre-CRT scan (28.1%) and both post-CRTOFF (37.9%; p = 0.046) and post-CRTON CMR (35.0%; p = 0.037), with a nonstatistically significant trend toward decreased LV volumes. No adverse events or significant changes in device electrical parameters (including battery level) were detected during the post-CMR scan period. A CRT "off-on" protocol during CMR studies can be safely executed in patients with an MR-conditional CRT defibrillator. However, technical improvements are needed to facilitate high-quality scans during active CRT. Favorable changes in LV function induced by CRT remodeling were not acutely reversed with the interruption of electrical therapy.

SAFERIDES: Application of decentralized control edge-computing to ridesharing monitoring services

Edge computing changed the face of many industries and services. Common edge computing models offload computing which is prone to security risks and privacy breach. However, advances in deep learning enabled Internet of Things (IoTs) to onload tasks and run cognitive tasks locally. This research introduces a decentralized-control edge model where computation and decision-making are moved to the IoT level. The model aims at decreasing communication and computation dependance on the edge which affect efficiency and latency. The model also limits data transfer to the edge to avoid security and privacy risks. Decentralized control is a key to many business applications that prioritizes safety, real-time response, and privacy such as ridesharing monitoring and industrial operations. To examine the model, we developed SAFERIDES, a scene-aware ridesharing monitoring system where smart phones are detecting violations at the runtime. Current monitoring systems require costly infrastructure and continuous network connectivity. However, SAFRIDES uses optimized deep learning models that run locally on IoTs to detect and record violations in ridesharing. The system achieved the lowest latency among current solution, while minimizing data sharing and maintaining privacy. Moreover, decentralized edge computing empowers IoTs and upgrades their functionality from sensing to independent decision-making.

Daughter Adjustment to Life Following the Death of Their Mother: Scoping Review

The objective of this scoping review was to assess and summarize existing literature on daughter adjustment to life following the death of their mother. The review examined factors that hinder and/or help daughter adjustment to mother loss, guided by the Joanna Briggs Institute (JBI) Manual for Evidence Synthesis. Included sources were published quantitative and qualitative primary research studies, and dissertations/theses. Sources referenced mother loss by death due to any cause, mother-bereaved daughters of any age and identification (e.g., biological, adopted, foster, step), and factors that hinder and/or help daughter adjustment to mother loss. MEDLINE Complete, APA PsycInfo, CINAHL, Embase, SCOPUS, and Web of Science were searched with no restrictions on language or date of publication. From 2774 sources retrieved, 30 were included for final review and data charting. A template thematic analysis was conducted on charted qualitative data. Findings indicate that many factors involved in daughter adjustment to mother loss are not categorically unhelpful or helpful; their utility is context-dependent. Safe, continued connections with mothers, growth mindsets and spiritual or religious beliefs are internal resources that may facilitate adjustment. External support from maternal figures and surviving parents, may have an especially salient influence, both positive and negative, on daughter adjustment, coping and development. Particularly helpful for mother-bereaved daughters may be activities that promote mindfulness, healthy self-expression, distraction, connection with others, and a sense of mastery or self-esteem. Research focused on identifying mother-bereaved daughter needs is required to inform social perceptions of mother loss, bereavement education, support, and policy.

How wet must a wetland be to have federal protections in post-Sackett US?

In 2023, the US Supreme Court's majority ruled in Sackett v. Environmental Protection Agency that only wetlands that are "indistinguishable" from federally protected waters "due to a continuous surface connection" are federally protected. This study estimates the potential impact of interpretations of the ruling on federal wetlands protections, using a qualitative measure of wetland "wetness" as a proxy for the new requirement. An estimated area ranging from ~17 million acres (19%) to nearly all 90 million acres of nontidal wetlands in the conterminous United States could be without federal protections, and variability in state protections creates hotspots of risk. The high-level estimates provided here represent a first step toward understanding the long-term impacts of Sackett v. Environmental Protection Agency on federal wetlands protections and highlight the uncertainty introduced by the ruling.

Automating insulin delivery through pump and continuous glucose monitoring connectivity: Maximizing opportunities to improve outcomes.

The development of automated insulin delivery (AID) systems, which connect continuous glucose monitoring (CGM) systems with algorithmic insulin delivery from an insulin pump (continuous subcutaneous insulin infusion, [CSII]), has led to improved glycaemia and quality of life benefits in those with insulin-treated diabetes. This review summarizes the benefits gained by the connectivity between insulin pumps and CGM devices. It details the technical requirements and advances that have enabled this, and highlights the clinical and user benefits of such systems. Clinical trials and real-world outcomes from the use of AID systems in people with type 1 diabetes (T1D)will be the focus of this article; outcomes in people with type 2 diabetes (T2D) and other diabetes subtypes will also be discussed. We also detail the limitations of current technological approaches for connectivity between insulin pumps and CGM devices. While recognizing the barriers, we discuss opportunities for the future.

Our Futures in Mind Uploading: Public Perceptions and Narratives

Advances in neurotechnology have immense potential but also pose significant ethical challenges. While the public is a key stakeholder, this audience is understudied. My research uses mind uploading as an exemplar for hypothetical future neurotechnology and contributes new data to an under researched field. To encourage participants to connect with mind uploading, I designed a novel data collection tool and method - a website that tells the stories of two fictional mind uploaded characters. My results showed that while awareness of mind uploading has remained relatively static over the last few years, favourability towards the concept has significantly increased, reflected in an increasing number of people who would upload if their physical body was dying and search for meaning in this new afterlife. However, while the public could identify several benefits for mind uploading, primarily a continued connection to loved ones, they were clearly concerned how neurotechnology, particularly that which would augment our existing capabilities, might develop. Public concerns reflected those of policymakers and scientists and confirmed the need for regulation to ensure neurotechnology is not discriminatory and does not create an even greater divide between the privileged and disadvantaged.

Enhancing 5G energy efficiency through digital twin networks: A comprehensive review

AbstractIn the era of 5G, seamless mobility handovers are critical in densely populated regions like Malaysia to mitigate disruptions and inefficiencies. 5G networks offer unprecedented data speeds and reliability, essential for advancing mobile communication and Internet of Things applications. However, ensuring continuous connectivity and service during mobility remains challenging, especially in urban settings. Digital twin technology presents a promising solution to enhance 5G handover mechanisms. A digital twin network (DTN) mirroring Malaysia's 5G infrastructure is proposed, utilising real‐time data and user behaviour insights to optimise energy consumption during handovers. The focus is on energy‐efficient protocols and algorithms, reviewed through a systematic literature review. The DTN aims to enhance mobility handover efficiency through predictive handovers and adaptive resource allocation, bolstered by sustainable practices such as edge computing. The potential of DTNs to optimise 5G handover processes is explored, starting with the foundational concepts of 5G mobility and digital twins, highlighting the need for improved strategies in high‐mobility scenarios. Methodologies leveraging digital twins to predict network conditions, simulate handover scenarios, and proactively manage decisions are examined, reducing latency and packet loss. Case studies demonstrate how digital twins adapt dynamically to network changes and user mobility, thereby improving quality of service and user experience. Malaysia's specific 5G mobility challenges are addressed with a tailored DTN emphasising energy efficiency, evaluated through practical applications. Evaluation criteria assess effectiveness with in‐depth analysis of methods, performance metrics, limitations, and recommendations for future research. Challenges and future directions including scalability, security, and real‐time data processing, are discussed, aiming to integrate digital twin technology with 5G networks for enhanced connectivity. This abstract provides a roadmap for leveraging digital twins to optimise 5G network performance sustainably, guiding future research and implementation strategies.

A new method for the prediction of vibration responses of thin plates coupled with discontinuous connections

Due to the limitation caused by the assumption of ideal continuous line junctions between plates or the high computation cost, the existing methods cannot provide reliable prediction solutions of vibration responses of coupled plates with real connections, such as bolts and corner irons. To this end, a discontinuous energy finite element analysis (dEFEA) method with high accuracy is proposed to predict the vibration responses of discontinuously connected plates, which can revert the real connection. This method developes the coupling loss factors (CLFs) on the steady-state energy flow technique to characterize vibration transmission between plates with different connections. In addition, a discontinuous energy finite element equation of coupled plates is established to obtain the vibration responses of those. The efficacy of the dEFEA method is demonstrated by experiments and the method can improve the prediction accuracy of vibration, which is verified by the comparison between discontinuous and ideal continuous connections. To sum up, vibration transmission of connected structures varies greatly depending on the way of connection and cannot be simplified to a line connection.

“He’s the Test(imony)”: Edward Gibbon and Virginia Woolf’s View of History

ABSTRACT This article examines Virginia Woolf’s view of history by taking Edward Gibbon as a locus of historical reflection and refiguration. Starting with a reinvestigation into the Gibbon episode in The Voyage Out, it argues that Woolf’s primary aim is to equate history as an act of reading and thereupon a sort of reader-oriented text. The reader’s powerful autonomy in historical reading foregrounds the textuality of history. This article turns then to explore the ways in which Woolf maneuvers the writing style of Gibbon and infuses it into her historical writing through the prism of imagination. The literary and reconstructive attributes of historical writing indicate the subjectivity of history. Finally, this article adumbrates the retrospective trajectory of Woolf’s mode of thinking in history. By virtue of Gibbon’s great doctrine of the continuity of history, Woolf forges a continuous connection between the present and the past as well as the future. Valorising Gibbon as both an allusion and an influencer, this article problematises the widely acknowledged nineteenth-century traditions or twentieth-century philosophies thought to be assimilated or anticipated by Woolf; instead, it defends Woolf’s receptive and revisionist stance vis-à-vis the eighteenth-century historian as a legacy and correspondingly outlines her triangulated view of history.

Identification of a stress-responsive subregion of the basolateral amygdala in male rats.

The basolateral amygdala (BLA) is reliably activated by psychological stress and hyperactive in conditions of pathological stress or trauma; however, subsets of BLA neurons are also readily activated by rewarding stimuli and can suppress fear and avoidance behaviours. The BLA is highly heterogeneous anatomically, exhibiting continuous molecular and connectivity gradients throughout the entire structure. A critical gap remains in understanding the anatomical specificity of amygdala subregions, circuits, and cell types explicitly activated by acute stress and how they are dynamically activated throughout stimulus exposure. Using a combination of topographical mapping for the activity-responsive protein FOS and fiber photometry to measure calcium transients in real-time, we sought to characterize the spatial and temporal patterns of BLA activation in response to a range of novel stressors (shock, swim, restraint, predator odour) and non-aversive, but novel stimuli (crackers, citral odour). We report four main findings: (1) the BLA exhibits clear spatial activation gradients in response to novel stimuli throughout the medial-lateral and dorsal-ventral axes, with aversive stimuli strongly biasing activation towards medial aspects of the BLA; (2) novel stimuli elicit distinct temporal activation patterns, with stressful stimuli exhibiting particularly enhanced or prolonged temporal activation patterns; (3) changes in BLA activity are associated with changes in behavioural state; and (4) norepinephrine enhances stress-induced activation of BLA neurons via the ß-noradrenergic receptor. Moving forward, it will be imperative to combine our understanding of activation gradients with molecular and circuit-specificity.

How smartphone addiction disrupts the positive relationship between self-regulation, self-efficacy and student engagement in distance education

Given that students maintain a continuous connection with their smartphones in their daily lives and rely on them for participating in distance education, it becomes imperative to explore the factors associated with student engagement, considering the mediating role of smartphone addiction in distance education programs. Although extensive research has been carried out on smartphone addiction, very little is known about it in the context of distance education. This study aims to explore the relationship between student engagement, smartphone addiction, self-regulation, and self-efficacy among distance education students in online learning environments. This cross-sectional study was conducted in Türkiye. Data were collected via an online questionnaire from 1514 university students (n = 842 females, n = 672 males; Mage = 33.11, SD = 10.09) enrolled in various distance education programs in Turkey, specifically those undertaking synchronous online courses, through an online questionnaire distributed via e-mail. Path analysis modelling was used to test the hypothesised model. Maximum Likelihood Estimation was used as a method for estimating parameters in path analysis. The findings of this study indicate that self-regulation had a positive impact on student engagement, while smartphone addiction had a negative influence. Importantly, smartphone addiction acted as a mediating factor, weakening the relationship between self-regulation and student engagement. No significant correlation was found between general self-efficacy and smartphone addiction. These results highlight the significance of interventions focusing on self-regulation skills and promoting healthy digital habits to enhance student engagement and addressing smartphone addiction is crucial for enhancing student engagement in distance learning environments.

Higher general intelligence is associated with stable, efficient, and typical dynamic functional brain connectivity patterns

Abstract General intelligence, referred to as g, is hypothesized to emerge from the capacity to dynamically and adaptively reorganize macroscale brain connectivity. Temporal reconfiguration can be assessed using dynamic functional connectivity (dFC), which captures the propensity of brain connectivity to transition between a recurring repertoire of distinct states. Conventional dFC metrics commonly focus on categorical state switching frequencies which do not fully assess individual variation in continuous connectivity reconfiguration. Here, we supplement frequency measures by quantifying within-state connectivity consistency, dissimilarity between connectivity across states, and conformity of individual connectivity to group-average state connectivity. We utilized resting-state functional magnetic resonance imaging (fMRI) data from the large-scale Human Connectome Project and applied data-driven multivariate Partial Least Squares Correlation to explore emergent associations between dynamic network properties and cognitive ability. Our findings reveal a positive association between g and the stable maintenance of states characterized by distinct connectivity between higher-order networks, efficient reconfiguration (i.e., minimal connectivity changes during transitions between similar states, large connectivity changes between dissimilar states), and ability to sustain connectivity close to group-average state connectivity. This hints at fundamental properties of brain–behavior organization, suggesting that general cognitive processing capacity may be supported by the ability to efficiently reconfigure between stable and population-typical connectivity patterns.

A coordinated active and reactive power optimization approach for multi-microgrids connected to distribution networks with multi-actor-attention-critic deep reinforcement learning

As a promising approach to managing distributed energy, the use of microgrids has attracted significant attention among those managing continuous connections to distribution networks. However, the barriers of the data sharing among different microgrids, the uncertainty of the distributed renewable sources and loads, and the nonlinear optimization of power flow make traditional model-based optimization methods difficult to be applied. In this paper, a data-driven coordinated active and reactive power optimization method is proposed for distribution networks with multi-microgrids. A multi-agent deep reinforcement learning (MADRL) method is used to protect the data privacy of each microgrids. Moreover, attention mechanism, which pays attention to crucial information, is presented to overcome the problem of slow convergence caused by the dimensionality explosion of the optimized variables. Two types of agents, controlling discrete action and continuous action devices, respectively, are formulated in coordinated optimization, which reduces voltage violations and improves the system operation efficiency. In addition, in order to improve the performance of the online agent model under variable operation conditions, the transfer learning is embedded in the training process of the MADRL. The proposed method is verified on a modified IEEE 33-bus distribution network with nine microgrids.

Influences of a Remote Monitoring Program of Home Nasogastric Tube Feeds on Transition from NICU to Home.

The transition from the neonatal intensive care unit (NICU) to the home is complex and multifaceted for families and infants, particularly those with ongoing medical needs. Our hospital utilizes a remote monitoring program called Growing @ Home (G@H) to support discharge from the NICU with continued nasogastric tube (NGT) feeds. We aim to describe the experience of the transition from NICU to home for families enrolled in G@H. Using a semistructured interviewing technique, parents of infants discharged on G@H were interviewed at NICU discharge, at 1 month, and at 6 months after NICU discharge. Interviews were recorded and transcribed into data analysis software. Conventional content analysis was used to analyze qualitative data. Codes were assigned to describe key elements of the interviews and used to identify major themes. Parents (n = 17) identified three major themes when discussing the effect of G@H on the transition to home. The program provided a means of escape from the NICU, allowing families to stop living split lives between their homes and the NICU. It acted as a middle ground between the restrictive yet supportive NICU environment, and the normal yet isolated home environment. G@H served as a safety net for families, providing a continued connection to the NICU for their still-fragile infants. G@H utilizes telehealth to positively support the complex transition from NICU to home for families and infants discharged with NGT feeds. · G@H program supported parents in their transition from NICU to home.. · G@H program provided a means of escape from the NICU.. · G@H program was a middle ground between the NICU and home.. · G@H program created a safety net after discharge.. · Follow-up with a consistent provider was essential to a positive parent experience..