Quantifying physical degradation alongside recording and stimulation performance of 980 intracortical microelectrodes chronically implanted in three humans for 956-2246 days

Motivation

The clinical success of brain-machine interfaces depends on overcoming both biological and material challenges to ensure a long-term stable connection for neural recording and stimulation. Therefore, there is a need to quantify any damage that microelectrodes sustain when they are chronically implanted in the human cortex.

Methods

Using scanning electron microscopy (SEM), we imaged 980 microelectrodes from Neuroport arrays chronically implanted in the cortex of three people with tetraplegia for 956-2246 days. We analyzed eleven multi-electrode arrays in total: eight arrays with platinum (Pt) electrode tips and three with sputtered iridium oxide tips (SIROF); one Pt array was left in sterile packaging, serving as a control. The arrays were implanted/explanted across three different clinical sites surgeries (Caltech/UCLA, Caltech/USC and APL/Johns Hopkins) in the anterior intraparietal area, Brodmann's area 5, motor cortex, and somatosensory cortex.Human experts rated the electron micrographs of electrodes with respect to five damage metrics: the loss of metal at the electrode tip, the amount of separation between the silicon shank and tip metal, tissue adherence or bio-material to the electrode, damage to the shank insulation and silicone shaft. These metrics were compared to functional outcomes (recording quality, noise, impedance and stimulation ability).

Results

Despite higher levels of physical degradation, SIROF electrodes were twice as likely to record neural activity than Pt electrodes (measured by SNR), at the time of explant. Additionally, 1 kHz impedance (measured in vivo prior to explant) significantly correlated with all physical damage metrics, recording, and stimulation performance for SIROF electrodes (but not Pt), suggesting a reliable measurement of in vivo degradation. We observed a new degradation type, primarily occurring on stimulated electrodes ("pockmarked" vs "cracked") electrodes; however, tip metalization damage was not significantly higher due to stimulation or amount of charge. Physical damage was centralized to specific regions of an array often with differences between outer and inner electrodes. This is consistent with degradation due to contact with the biologic milieu, influenced by variations in initial manufactured state. From our data, we hypothesize that erosion of the silicon shank often precedes damage to the tip metal, accelerating damage to the electrode / tissue interface.

Conclusions

These findings link quantitative measurements, such as impedance, to the physical condition of the microelectrodes and their capacity to record and stimulate. These data could lead to improved manufacturing or novel electrode designs to improve long-term performance of BMIs making them are vitally important as multi-year clinical trials of BMIs are becoming more common.

When Refreshable Tactile Displays Meet Conversational Agents: Investigating Accessible Data Presentation and Analysis with Touch and Speech

Despite the recent surge of research efforts to make data visualizations accessible to people who are blind or have low vision (BLV), how to support BLV people's data analysis remains an important and challenging question. As refreshable tactile displays (RTDs) become cheaper and conversational agents continue to improve, their combination provides a promising approach to support BLV people's interactive data exploration and analysis. To understand how BLV people would use and react to a system combining an RTD with a conversational agent, we conducted a Wizard-of-Oz study with 11 BLV participants, where they interacted with line charts, bar charts, and isarithmic maps. Our analysis of participants' interactions led to the identifcation of nine distinct patterns. We also learned that the choice of modalities depended on the type of task and prior experience with tactile graphics, and that participants strongly preferred the combination of RTD and speech to a single modality. In addition, participants with more tactile experience described how tactile images facilitated a deeper engagement with the data and supported independent interpretation. Our fndings will inform the design of interfaces for such interactive mixed-modality systems.

HLA-E and NKG2A Mediate Resistance to M. bovis BCG Immunotherapy in Non-Muscle-Invasive Bladder Cancer

Mycobacterium bovis Bacillus Calmette-Guerin (BCG) is the primary treatment for non-muscle-invasive bladder cancer (NMIBC), known to stimulate inflammatory cytokines, notably interferon (IFN)-γ. We observed that prolonged IFN-γ exposure fosters adaptive resistance in recurrent tumors, aiding immune evasion and tumor proliferation. We identify HLA-E and NKG2A, part of a novel NK and T cell checkpoint pathway, as key mediators of resistance in BCG-unresponsive NMIBC. IFN-γ enhances HLA-E and PD-L1 expression in recurrent tumors, with an enrichment of intra-tumoral NKG2A-expressing NK and CD8 T cells. CXCL9+ macrophages and dendritic cells and CXCL12-expressing stromal cells likely recruit CXCR3/CXCR4-expressing NK and T cells and CXCR7+ HLA-EHIGH tumor cells. NK and CD8 T cells remain functional within BCG-unresponsive tumors but are inhibited by HLA-E and PD-L1, providing a framework for combined NKG2A and PD-L1 blockade strategy for bladder-sparing treatment of BCG-unresponsive NMIBC.

Phylogeny, morphology, and behavior of the new ciliate species Stentor stipatus

The study of evolution at the cellular level traditionally has focused on the evolution of metabolic pathways, endomembrane systems, and genomes, but there has been increasing interest in evolution of more complex cellular structures and behaviors, particularly in the eukaryotes. Ciliates have major advantages for such studies due to their easily visible surface patterning and their dramatic and complex behaviors that can be easily analyzed. Among the ciliates, the genus Stentor epitomizes the features that are useful for studying evolution: they are widespread in freshwater environments, easy to visualize because of their large size, and capable of complex behaviors such as learning, decision-making, and phototaxis. Here, we introduce the discovery of a new species within this genus: Stentor stipatus, so named for their distinctive dark brown aggregates. We present morphological, phylogenetic, ecological, and behavioral characterizations of these cells. The S. stipatus clade has a bootstrap value of 93 and is phylogenetically distinct from S. amethystinus, the closest related species which shares a sequence similarity of 98.9%. S. stipatus is capable of phototaxis and can also habituate more quickly than S. coeruleus, the Stentor species in which most habituation studies have previously been conducted. These findings expand our understanding of Stentor species diversity, natural history, and demonstrate common principles of complex behavior that are present in single-celled organisms.

Early onset metastatic colorectal cancer in Australia

BACKGROUND

Colorectal cancer (CRC) incidence and mortality rates have been increasing among young patients (YP), for uncertain reasons. It is unclear whether YP have a distinct tumor biology or merit a different treatment approach to older patients (OP).

METHODS

We reviewed prospectively collected data from consecutive patients with metastatic CRC (MCRC) enrolled in the multi-site Treatment of Recurrent and Advanced Colorectal Cancer (TRACC) Australian registry. Clinicopathological features, treatment and survival outcomes were compared between YP (<50 years) and OP (≥50 years).

RESULTS

Of 3692 patients diagnosed August 2009 - March 2023, 14 % (513) were YP. YP were more likely than OP to be female (52% vs. 40 %, P < 0.0001), have ECOG performance status 0-1 (94% vs. 81 %, P < 0.0001), to have a left-sided primary (72% vs. 63 %, P = 0.0008) and to have fewer comorbidities (90% vs. 60 % Charleston score 0, P < 0.0001). There were no differences in the available molecular status, which was more complete in YP. YP were more likely to have de novo metastatic disease (71% vs. 57 %, P < 0.0001). YP were more likely to undergo curative hepatic resection (27% vs. 17 %, P < 0.0001), to receive any chemotherapy (93% vs. 78 % (P < 0.0001), and to receive 3+ lines of chemotherapy (30% vs. 24 % (P < 0.0034)). Median first-line progression free survival (10.2 versus 10.6 months) was similar for YP vs OP, but overall survival (32.1 versus 25.4 months, HR = 0.745, P < 0.0001) was longer in YP.

CONCLUSION

Known prognostic variables mostly favored YP versus OP with newly diagnosed mCRC, who were also more heavily treated. Consistent with this, overall survival outcomes were improved. This data does not support that CRC in YP represent a distinct subset of mCRC patients, or that a modified treatment approach is warranted.

WonderFlow: Narration-Centric Design of Animated Data Videos

Creating an animated data video with audio narration is a time-consuming and complex task that requires expertise. It involves designing complex animations, turning written scripts into audio narrations, and synchronizing visual changes with the narrations. This paper presents WonderFlow, an interactive authoring tool, that facilitates narration-centric design of animated data videos. WonderFlow allows authors to easily specify semantic links between text and the corresponding chart elements. Then it automatically generates audio narration by leveraging text-to-speech techniques and aligns the narration with an animation. WonderFlow provides a structure-aware animation library designed to ease chart animation creation, enabling authors to apply pre-designed animation effects to common visualization components. Additionally, authors can preview and refine their data videos within the same system, without having to switch between different creation tools. A series of evaluation results confirmed that WonderFlow is easy to use and simplifies the creation of data videos with narration-animation interplay.

Databiting: Lightweight, Transient, and Insight Rich Exploration of Personal Data

As mobile and wearable devices are becoming increasingly powerful, access to personal data is within reach anytime and anywhere. Currently, methods of data exploration while on-the-go and in-situ are, however, often limited to glanceable and micro visualizations, which provide narrow insight. In this article, we introduce the notion of databiting, the act of interacting with personal data to obtain richer insight through lightweight and transient exploration. We focus our discussion on conceptualizing databiting and arguing its potential values. We then discuss five research considerations that we deem important for enabling databiting: contextual factors, interaction modalities, the relationship between databiting and other forms of exploration, personalization, and evaluation challenges. We envision this line of work in databiting could enable people to easily gain meaningful personal insight from their data anytime and anywhere.

Mystique: Deconstructing SVG Charts for Layout Reuse

To facilitate the reuse of existing charts, previous research has examined how to obtain a semantic understanding of a chart by deconstructing its visual representation into reusable components, such as encodings. However, existing deconstruction approaches primarily focus on chart styles, handling only basic layouts. In this paper, we investigate how to deconstruct chart layouts, focusing on rectangle-based ones, as they cover not only 17 chart types but also advanced layouts (e.g., small multiples, nested layouts). We develop an interactive tool, called Mystique, adopting a mixed-initiative approach to extract the axes and legend, and deconstruct a chart's layout into four semantic components: mark groups, spatial relationships, data encodings, and graphical constraints. Mystique employs a wizard interface that guides chart authors through a series of steps to specify how the deconstructed components map to their own data. On 150 rectangle-based SVG charts, Mystique achieves above 85% accuracy for axis and legend extraction and 96% accuracy for layout deconstruction. In a chart reproduction study, participants could easily reuse existing charts on new datasets. We discuss the current limitations of Mystique and future research directions.

Data Formulator: AI-Powered Concept-Driven Visualization Authoring

With most modern visualization tools, authors need to transform their data into tidy formats to create visualizations they want. Because this requires experience with programming or separate data processing tools, data transformation remains a barrier in visualization authoring. To address this challenge, we present a new visualization paradigm, concept binding, that separates high-level visualization intents and low-level data transformation steps, leveraging an AI agent. We realize this paradigm in Data Formulator, an interactive visualization authoring tool. With Data Formulator, authors first define data concepts they plan to visualize using natural languages or examples, and then bind them to visual channels. Data Formulator then dispatches its AI-agent to automatically transform the input data to surface these concepts and generate desired visualizations. When presenting the results (transformed table and output visualizations) from the AI agent, Data Formulator provides feedback to help authors inspect and understand them. A user study with 10 participants shows that participants could learn and use Data Formulator to create visualizations that involve challenging data transformations, and presents interesting future research directions.

Screening, brief intervention, and referral to treatment for tobacco consumption, alcohol misuse, and physical inactivity: an equity-informed rapid review

OBJECTIVE

This rapid review systematically synthesizes evidence of the effectiveness of the Screening, Brief Intervention, and Referral (SBIR/T) approach for tobacco use, alcohol misuse, and physical inactivity.

STUDY DESIGN

This was a rapid review.

METHODS

We searched primary studies between 2012 and 2022 in seven electronic databases. The search strategy used concepts related to alcohol-related disorders, intoxication, cigarette, nicotine, physical activity, exercise, sedentary, screening, therapy, and referral. We reviewed both title/abstract and full-text using a priori set inclusion and exclusion criteria to identify the eligible studies. We appraised study quality, extracted data, and summarized the characteristics of the included studies. We applied health equity lenses in the synthesis.

RESULTS

Of the 44 included studies, most focused on alcohol misuse. SBIR/T improved patients' attitudes toward alcohol behavior change, improved readiness and referral initiation for change, and effectively reduced alcohol consumption. Few studies pertained to smoking and physical inactivity. Most studies on smoking demonstrated effectiveness pertaining to patients' acceptance of referral recommendations, improved readiness and attempts to quitting smoking, and reduced or cessation of smoking. Findings were mixed about the effectiveness of SBIR/T in improving physical activity. Minimal studies exist on the impacts of SBIR/T for these three risk factors on healthcare resource use or costs. Studies considering diverse population characteristics in the design and effectiveness assessment of the SBIR/T intervention are lacking.

CONCLUSIONS

More research on the impacts of SBIR/T on tobacco use, alcohol misuse, and physical inactivity is required to inform the planning and delivery of SBIR/T for general and disadvantaged populations.

Structure guided mutagenesis of Henipavirus Receptor Binding Proteins reveals molecular determinants of receptor usage and antibody binding epitopes

Nipah virus (NiV) is a highly lethal, zoonotic henipavirus (HNV) that causes respiratory and neurological signs and symptoms in humans. Similar to other paramyxoviruses, HNVs mediate entry into host cells through the concerted actions of two surface glycoproteins: a receptor binding protein (RBP) that mediates attachment and a fusion glycoprotein (F) that triggers fusion in an RBP-dependent manner. NiV uses ephrin-B2 (EFNB2) and ephrin-B3 (EFNB3) as entry receptors. Ghana virus (GhV), a novel HNV identified in a Ghanaian bat, use EFNB2 but not EFNB3. In this study, we employ a structure-informed approach to identify receptor interfacing residues and systematically introduce GhV-RBP residues into a NiV-RBP backbone to uncover the molecular determinants of EFNB3 usage. We reveal two regions that severely impair EFNB3 binding by NiV-RBP and EFNB3-mediated entry by NiV pseudotyped viral particles. Further analyses uncovered two point mutations (NiVN557SGhV and NiVY581TGhV) pivotal for this phenotype. Moreover, we identify NiV interaction with Y120 of EFNB3 as important for usage of this receptor. Beyond these EFNB3-related findings, we reveal two domains that restrict GhV binding of EFNB2, identify the HNV-head as an immunodominant target for polyclonal and monoclonal antibodies, and describe putative epitopes for GhV and NiV-specific monoclonal antibodies. Cumulatively, the work presented here generates useful reagents and tools that shed insight to residues important for NiV usage of EFNB3, reveals regions critical for GhV binding of EFNB2, and describes putative HNV antibody binding epitopes.

Integrating a Tool to Automatically Determine Necessity of Online Adaptive Replanning

PURPOSE/OBJECTIVE(S)

As online adaptive replanning (OLAR) is labor-intensive and time-consuming, it's desirable to determine when OLAR is necessary before OLAR is initiated. We have previously reported a novel method to automatically determine the necessity of OLAR using machine leaning algorithms based on the structural similarity maps (SSIM) and wavelet texture maps (WMT) extracted from the daily MRI during MR-guided adaptive radiation therapy (MRgART). This study aims to integrate this method into a commercial software platform that has been used during our routine MRgART.

MATERIALS/METHODS

The method of automatically determining the necessity of OLAR based on daily MRI was implemented and integrated into the software platform through a specifically developed workflow. The obtained workflow was tested using 25 daily MRI sets acquired from 5 patients with pancreatic cancer in the following procedure: 1) rigidly registering the daily and reference MRIs, 2) identifying the region enclosed by the 50-100% iso-dose surfaces on the daily MRI by transferring the iso-dose surfaces from the reference to the daily MRIs, 3) launching our in-house codes to calculate significant changes in textures extracted from SSIM and WMT maps, 4) inputting the feature values into the pre-trained classifier models for SSIM and WMT, and 5) outputting results considering the WMT based prediction as the primary indicator and the SSIM-based as the secondary (validation) indicator on whether OLAR is needed for the daily MRI.

RESULTS

The execution of the developed workflow was fast and can be used to streamline the process. It provides the ability to scroll through the images for better decision making while providing quantitative prediction within 30-38 seconds. Eighty percent of the daily MRIs required OLAR. The SSIM map displayed was able to successfully captured the areas of similarity between the reference and daily MRIs and the WMT prediction agreed with the prediction class.

CONCLUSION

The integration of the prediction method for automatically determining the necessity of OLAR based on two independent machine learning classifiers into a commercially available software is feasible and can be used to streamline the process of MRgART. With larger verification studies, this workflow-based tool may be developed into a generalized tool that assist in OLAR using different platforms.

Uncertainty in phosphorus fluxes and budgets across the U.S. long-term agroecosystem research network

Phosphorus (P) budgets can be useful tools for understanding nutrient cycling and quantifying the effectiveness of nutrient management planning and policies; however, uncertainties in agricultural nutrient budgets are not often quantitatively assessed. The objective of this study was to evaluate uncertainty in P fluxes (fertilizer/manure application, atmospheric deposition, irrigation, crop removal, surface runoff, leachate) and the propagation of these uncertainties to annual P budgets. Data from 56 cropping systems in the P-FLUX database, which spans diverse rotations and landscapes across the U.S. and Canada, were evaluated. Results showed that across cropping systems, average annual P budget was 22.4 kg P ha^-1 (range = -32.7 to 340.6 kg P ha^-1 ), with an average uncertainty of 13.1 kg P ha^-1 (range = 1.0 to 87.1 kg P ha^-1 ). Fertilizer/manure application and crop removal were the largest P fluxes across cropping systems and, as a result, accounted for the largest fraction of uncertainty in annual budgets (61 and 37%, respectively). Remaining fluxes individually accounted for <2% of the budget uncertainty. Uncertainties were large enough that determining whether P was increasing, decreasing, or not changing was inconclusive in 39% of the budgets evaluated. Findings indicate that more careful and/or direct measurements of inputs, outputs, and stocks are needed. Recommendations for minimizing uncertainty in P budgets based on the results of the study were developed. Quantifying, communicating, and constraining uncertainty in budgets among production systems and multiple geographies is critical for engaging stakeholders, developing local and national strategies for P reduction, and informing policy. This article is protected by copyright. All rights reserved.

Initial phase establishment of an in vitro method for developmental neurotoxicity test using Ki-67 in human neural progenitor cells

Building a precise alternative neurotoxicological test is of great importance to respond to societal and ethical requirements. In this study, a new developmental neurotoxicity test (DNT) was established with the human neural progenitor cell line. ReNcell CX cells were exposed to neurotoxic chemicals (aphidicolin, hydroxyurea, cytosine arabinoside, 5-fluorouracil, and ochratoxin A) or non-neurotoxic chemicals (sodium gluconate, sodium bicarbonate, penicillin G, and saccharin). Propidium iodide (PI) was used to evaluate cell viability. BrdU and Ki-76 were employed to determine cell proliferation. Based on the cell viability and proliferation, mathematical models were built by linear discriminant analysis. Furthermore, the neurotoxic-considered chemicals inhibited cell cycle progression at the protein level, supporting the biomolecular rationale for the predictive model. Overall, these results show that the new test method can be used to determine the potential developmental neurotoxicants or new drug candidates.

Integrating EM and Patch-seq data: Synaptic connectivity and target specificity of predicted Sst transcriptomic types

Neural circuit function is shaped both by the cell types that comprise the circuit and the connections between those cell types ¹ . Neural cell types have previously been defined by morphology ^{2, 3} , electrophysiology ^{4, 5} , transcriptomic expression ^6-8 , connectivity ^9-13 , or even a combination of such modalities ^14-16 . More recently, the Patch-seq technique has enabled the characterization of morphology (M), electrophysiology (E), and transcriptomic (T) properties from individual cells ^17-20 . Using this technique, these properties were integrated to define 28, inhibitory multimodal, MET-types in mouse primary visual cortex ²¹ . It is unknown how these MET-types connect within the broader cortical circuitry however. Here we show that we can predict the MET-type identity of inhibitory cells within a large-scale electron microscopy (EM) dataset and these MET-types have distinct ultrastructural features and synapse connectivity patterns. We found that EM Martinotti cells, a well defined morphological cell type ^{22, 23} known to be Somatostatin positive (Sst+) ^{24, 25} , were successfully predicted to belong to Sst+ MET-types. Each identified MET-type had distinct axon myelination patterns and synapsed onto specific excitatory targets. Our results demonstrate that morphological features can be used to link cell type identities across imaging modalities, which enables further comparison of connectivity in relation to transcriptomic or electrophysiological properties. Furthermore, our results show that MET-types have distinct connectivity patterns, supporting the use of MET-types and connectivity to meaningfully define cell types.

SizePairs: Achieving Stable and Balanced Temporal Treemaps using Hierarchical Size-based Pairing

We present SizePairs, a new technique to create stable and balanced treemap layouts that visualize values changing over time in hierarchical data. To achieve an overall high-quality result across all time steps in terms of stability and aspect ratio, SizePairs employs a new hierarchical size-based pairing algorithm that recursively pairs two nodes that complement their size changes over time and have similar sizes. SizePairs maximizes the visual quality and stability by optimizing the splitting orientation of each internal node and flipping leaf nodes, if necessary. We also present a comprehensive comparison of SizePairs against the state-of-the-art treemaps developed for visualizing time-dependent data. SizePairs outperforms existing techniques in both visual quality and stability, while being faster than the local moves technique.

Personal Health Data Tracking by Blind and Low-Vision People: A Survey Study (Preprint)

BACKGROUND

Personal health technologies, including wearable tracking devices and mobile apps, have great potential to equip the general population with the ability to monitor and manage their health. However, being designed for sighted people, much of their functionality is largely inaccessible to the blind and low-vision (BLV) population, threatening the equitable access to personal health data (PHD) and health care services.

OBJECTIVE

This study aims to understand why and how BLV people collect and use their PHD and the obstacles they face in doing so. Such knowledge can inform accessibility researchers and technology companies of the unique self-tracking needs and accessibility challenges that BLV people experience.

METHODS

We conducted a web-based and phone survey with 156 BLV people. We reported on quantitative and qualitative findings regarding their PHD tracking practices, needs, accessibility barriers, and work-arounds.

RESULTS

BLV respondents had strong desires and needs to track PHD, and many of them were already tracking their data despite many hurdles. Popular tracking items (ie, exercise, weight, sleep, and food) and the reasons for tracking were similar to those of sighted people. BLV people, however, face many accessibility challenges throughout all phases of self-tracking, from identifying tracking tools to reviewing data. The main barriers our respondents experienced included suboptimal tracking experiences and insufficient benefits against the extended burden for BLV people.

CONCLUSIONS

We reported the findings that contribute to an in-depth understanding of BLV people's motivations for PHD tracking, tracking practices, challenges, and work-arounds. Our findings suggest that various accessibility challenges hinder BLV individuals from effectively gaining the benefits of self-tracking technologies. On the basis of the findings, we discussed design opportunities and research areas to focus on making PHD tracking technologies accessible for all, including BLV people.

Stent expansion evaluated by optical coherence tomography and subsequent outcomes

Background

Regarding stent expansion indexes, previous optical coherence tomography (OCT) studies have shown minimal stent area (MSA) to be most predictive of adverse events.

Purpose

We sought to evaluate the impact of various stent expansion indexes by post-stent OCT on long-term clinical outcomes, and hence to find OCT-defined optimal stent expansion criteria.

Methods

Of the patients registered in the Yonsei OCT registry, a total of 1071 patients with 1123 native coronary artery lesions treated with new-generation drug-eluting stents under the OCT guidance and analyzable final post-stent OCT were included. Stent expansion indexes and different suboptimal stent expansion criteria were evaluated for their association with device-oriented clinical endpoints (DoCE) including cardiac death, target vessel-related myocardial infarction (TVMI) or stent thrombosis, and target lesion revascularization. Major safety events (MSE) included cardiac death, TVMI or stent thrombosis.

Results

The median follow-up period was 40.6 (interquartile range 22.0–50.0) months. As a continuous variable, MSA, adaptive volumetric stent expansion (stent volume/adaptive reference lumen volume) and overall volumetric stent expansion (stent volume/post-stent lumen volume) were significantly predictive of DoCE. As a categorical criteria, MSA &lt;5.0 mm2 (hazard ratio [HR] 3.80; 95% confidence interval [CI] 1.53–9.45), MSA/distal reference lumen area &lt;90% (HR 2.13; 95% CI 1.10–4.14), and overall volumetric stent expansion ≥96.6% (HR 2.38; 95% CI 1.09–5.22) were independently associated with DoCE after adjusting for confounders, and a total malapposition volume ≥7.0 mm3 (HR 3.38; 95% CI 1.05–10.93) was linked to MSE.

Conclusions

This OCT study highlights that sufficient stent expansion to achieve adequate absolute MSA and relative MSA by distal reference lumen area and alleviate significant malapposition is important to improve clinical outcome, but overall stent overexpansion may have deleterious effect.

Funding Acknowledgement

Type of funding sources: None.

Atrial fibrillation detection in ambulatory patients using a smart ring powered by deep learning analysis of continuous photoplethysmography monitoring

Background

Atrial fibrillation (AF) detection could be effective with photoplethysmography (PPG) signal monitoring by a wearable device.

Purpose

We aimed to validate the performance of AF detection among ambulatory patients who underwent electrical cardioversion for AF using a smart ring capable of continuous PPG monitoring and deep learning analysis.

Methods

In this prospective single-arm study, participants who underwent successful electrical cardioversion for AF were enrolled. The participants equipped a smart ring (CardioTracker, Sky Labs Inc., Seongnam, Republic of Korea) after the electrical cardioversion. The smart ring then continuously monitored PPG over 14 days to detect AF recurrence. The smart ring alarmed AF episodes based on deep learning analysis of PPG. The participants were asked to measure at least three daily ECGs using the smart ring to validate AF recurrence detected by PPG. All ECG snapshots were recorded along with lead I and saved with simultaneous PPG. ECG data were examined by the three cardiologists independently (SK, SRL, and EKC). The monitoring time, analyzable proportions of monitored signals, detection rates of AF episodes, and the diagnostic performance of PPG-based deep learning were evaluated. At the end of the monitoring, a survey on the use of the smart ring was performed.

Results

A total of 35 participants (mean age 58.9 years, male 74.3%) were enrolled. Figure 1 illustrates an example of PPG monitoring and PPG-ECG snapshots by the smart ring. The study participation period was a median of 14 days and the wearing time of the smart ring was a median of 9.2 days (IQR 7.1–11.5 days). Signal artifacts during daily activity decreased the analyzable proportions of monitored PPG by 68.5%. Irregular pulse episodes were detected by the smart ring in 29 (82.9%) participants after a median of 1 day from the cardioversion (Figure 2). A total of 2532 PPG-ECG snapshots were acquired and 1623 (64.1%) were interpretable by both the cardiologists (using ECG) and the deep learning analysis (using PPG). Comparing PPG by simultaneous ECG, the performance of AF detection by the smart ring was 98.7% for sensitivity, 97.8% for specificity, 2.2% for false positives, and 1.3% for false negatives (Figure 2). After using the smart ring, 76.9% of the participants responded that they had no discomfort in using the smart ring in daily activity and another 76.9% responded that it was helpful to monitor their disease.

Conclusion

Despite the signal artifacts during daily activity, AF detection with PPG monitoring by a smart ring could be effective for AF screening among ambulatory patients.

Funding Acknowledgement

Type of funding sources: Private company. Main funding source(s): This work was supported by Sky Labs Inc, Seongnam, Republic of Korea, and by the grant No. 0320202040 from the Seoul National University Hospital Research Fund.