Digital Biomarkers最新文献

{"title":"EVIDENCE Publication Checklist for Studies Evaluating Connected Sensor Technologies: Explanation and Elaboration.","authors":"Christine Manta,&nbsp;Nikhil Mahadevan,&nbsp;Jessie Bakker,&nbsp;Simal Ozen Irmak,&nbsp;Elena Izmailova,&nbsp;Siyeon Park,&nbsp;Jiat-Ling Poon,&nbsp;Santosh Shevade,&nbsp;Sarah Valentine,&nbsp;Benjamin Vandendriessche,&nbsp;Courtney Webster,&nbsp;Jennifer C Goldsack","doi":"10.1159/000515835","DOIUrl":"https://doi.org/10.1159/000515835","url":null,"abstract":"<p><p>The EVIDENCE (EValuatIng connecteD sENsor teChnologiEs) checklist was developed by a multidisciplinary group of content experts convened by the Digital Medicine Society, representing the clinical sciences, data management, technology development, and biostatistics. The aim of EVIDENCE is to promote high quality reporting in studies where the primary objective is an evaluation of a digital measurement product or its constituent parts. Here we use the terms digital measurement product and connected sensor technology interchangeably to refer to tools that process data captured by mobile sensors using algorithms to generate measures of behavioral and/or physiological function. EVIDENCE is applicable to 5 types of evaluations: (1) proof of concept; (2) verification, (3) analytical validation, and (4) clinical validation as defined by the V3 framework; and (5) utility and usability assessments. Using EVIDENCE, those preparing, reading, or reviewing studies evaluating digital measurement products will be better equipped to distinguish necessary reporting requirements to drive high-quality research. With broad adoption, the EVIDENCE checklist will serve as a much-needed guide to raise the bar for quality reporting in published literature evaluating digital measurements products.</p>","PeriodicalId":11242,"journal":{"name":"Digital Biomarkers","volume":"5 2","pages":"127-147"},"PeriodicalIF":0.0,"publicationDate":"2021-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1159/000515835","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39115370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Digital Neurologic Examination.","authors":"Adam B Cohen,&nbsp;Brain V Nahed","doi":"10.1159/000515577","DOIUrl":"https://doi.org/10.1159/000515577","url":null,"abstract":"<p><p>Digital health has been rapidly thrust into the forefront of care delivery. Poised to extend the clinician's reach, a new set of examination tools will redefine neurologic and neurosurgical care, serving as the basis for the <i>digital neurologic examination</i>. We describe its components and review specific technologies, which move beyond traditional video-based telemedicine encounters and include separate digital tools. A future suite of these clinical assessment technologies will blur the lines between history taking, examination, and remote monitoring. Prior to full-scale implementation, however, much more investigation is needed. Because of the nascent state of the technologies, researchers, clinicians, and developers should establish digital neurologic examination requirements in order to maximize its impact.</p>","PeriodicalId":11242,"journal":{"name":"Digital Biomarkers","volume":"5 1","pages":"114-126"},"PeriodicalIF":0.0,"publicationDate":"2021-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1159/000515577","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38966377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Remote Cardiac Safety Monitoring through the Lens of the FDA Biomarker Qualification Evidentiary Criteria Framework: A Case Study Analysis.","authors":"Elena S Izmailova,&nbsp;William A Wood,&nbsp;Qi Liu,&nbsp;Vadim Zipunnikov,&nbsp;Daniel Bloomfield,&nbsp;Jason Homsy,&nbsp;Steven C Hoffmann,&nbsp;John A Wagner,&nbsp;Joseph P Menetski","doi":"10.1159/000515110","DOIUrl":"https://doi.org/10.1159/000515110","url":null,"abstract":"<p><p>Clinical safety findings remain one of the reasons for attrition of drug candidates during clinical development. Cardiovascular liabilities are not consistently detected in early-stage clinical trials and often become apparent when drugs are administered chronically for extended periods of time. Vital sign data collection outside of the clinic offers an opportunity for deeper physiological characterization of drug candidates and earlier safety signal detection. A working group representing expertise from biopharmaceutical and technology sectors, US Food and Drug Administration (FDA) public-private partnerships, academia, and regulators discussed and presented a remote cardiac monitoring case study at the FNIH Biomarkers Consortium Remote Digital Monitoring for Medical Product Development workshop to examine applicability of the biomarker qualification evidentiary framework by the FDA. This use case examined the components of the framework, including the statement of need, the context of use, the state of the evidence, and the benefit/risk profile. Examination of results from 2 clinical trials deploying 510(k)-cleared devices for remote cardiac data collection demonstrated the need for analytical and clinical validity irrespectively of the regulatory status of a device of interest, emphasizing the importance of data collection method assessment in the context of intended use. Additionally, collection of large amounts of ambulatory data also highlighted the need for new statistical methods and contextual information to enable data interpretation. A wider adoption of this approach for drug development purposes will require collaborations across industry, academia, and regulatory agencies to establish methodologies and supportive data sets to enable data interpretation and decision-making.</p>","PeriodicalId":11242,"journal":{"name":"Digital Biomarkers","volume":"5 1","pages":"103-113"},"PeriodicalIF":0.0,"publicationDate":"2021-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1159/000515110","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38966375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wearable Devices: Current Status and Opportunities in Pain Assessment and Management.","authors":"Andrew Leroux, Rachael Rzasa-Lynn, Ciprian Crainiceanu, Tushar Sharma","doi":"10.1159/000515576","DOIUrl":"10.1159/000515576","url":null,"abstract":"<p><strong>Introduction: </strong>We investigated the possibilities and opportunities for using wearable devices that measure physical activity and physiometric signals in conjunction with ecological momentary assessment (EMA) data to improve the assessment and treatment of pain.</p><p><strong>Methods: </strong>We considered studies with cross-sectional and longitudinal designs as well as interventional or observational studies correlating pain scores with measures derived from wearable devices. A search was also performed on studies that investigated physical activity and physiometric signals among patients with pain.</p><p><strong>Results: </strong>Few studies have assessed the possibility of incorporating wearable devices as objective tools for contextualizing pain and physical function in free-living environments. Of the studies that have been conducted, most focus solely on physical activity and functional outcomes as measured by a wearable accelerometer. Several studies report promising correlations between pain scores and signals derived from wearable devices, objectively measured physical activity, and physical function. In addition, there is a known association between physiologic signals that can be measured by wearable devices and pain, though studies using wearable devices to measure these signals and associate them with pain in free-living environments are limited.</p><p><strong>Conclusion: </strong>There exists a great opportunity to study the complex interplay between physiometric signals, physical function, and pain in a real-time fashion in free-living environments. The literature supports the hypothesis that wearable devices can be used to develop reproducible biosignals that correlate with pain. The combination of wearable devices and EMA will likely lead to the development of clinically meaningful endpoints that will transform how we understand and treat pain patients.</p>","PeriodicalId":11242,"journal":{"name":"Digital Biomarkers","volume":"5 1","pages":"89-102"},"PeriodicalIF":0.0,"publicationDate":"2021-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8138140/pdf/dib-0005-0089.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38966378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Future of Digital Health: Meeting Report.","authors":"Priya Kumar,&nbsp;Ieuan Clay","doi":"10.1159/000515355","DOIUrl":"https://doi.org/10.1159/000515355","url":null,"abstract":"<p><p>At the end of 2020, Karger's <i>Digital Biomarkers</i>, together with Evidation Health, produced a special issue entitled \"The Future of Digital Health.\" This brief meeting report provides an overview of the expert panel and workshop that were held in early 2021 to explore key topics raised in the special issue.</p>","PeriodicalId":11242,"journal":{"name":"Digital Biomarkers","volume":"5 1","pages":"74-77"},"PeriodicalIF":0.0,"publicationDate":"2021-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1159/000515355","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38954761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Voice for Health: The Use of Vocal Biomarkers from Research to Clinical Practice.","authors":"Guy Fagherazzi, Aurélie Fischer, Muhannad Ismael, Vladimir Despotovic","doi":"10.1159/000515346","DOIUrl":"10.1159/000515346","url":null,"abstract":"<p><p>Diseases can affect organs such as the heart, lungs, brain, muscles, or vocal folds, which can then alter an individual's voice. Therefore, voice analysis using artificial intelligence opens new opportunities for healthcare. From using vocal biomarkers for diagnosis, risk prediction, and remote monitoring of various clinical outcomes and symptoms, we offer in this review an overview of the various applications of voice for health-related purposes. We discuss the potential of this rapidly evolving environment from a research, patient, and clinical perspective. We also discuss the key challenges to overcome in the near future for a substantial and efficient use of voice in healthcare.</p>","PeriodicalId":11242,"journal":{"name":"Digital Biomarkers","volume":"5 1","pages":"78-88"},"PeriodicalIF":0.0,"publicationDate":"2021-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8138221/pdf/dib-0005-0078.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38954762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Concurrent Validity of Inertially Sensed Measures during Voluntary Body Sway in Silence and while Exposed to a Rhythmic Acoustic Stimulus: A Pilot Study.","authors":"Analina Emmanouil,&nbsp;Elissavet Rousanoglou,&nbsp;Anastasia Georgaki,&nbsp;Konstantinos Boudolos","doi":"10.1159/000514325","DOIUrl":"https://doi.org/10.1159/000514325","url":null,"abstract":"<p><strong>Introduction: </strong>The effect of rhythmic acoustic stimuli on body sway is of increasing interest due to their positive contribution when training or restoring the control of movement. Inertial sensors show promise as a portable, easier, and more affordable method compared to the force plate \"gold standard\" concerning the evaluation of postural sway. This study examined the concurrent validity of inertially sensed measures of voluntary body sway against those obtained with a force plate, in silence and while exposed to a rhythmic acoustic stimulus.</p><p><strong>Methods: </strong>Temporal (sway duration and variability) and spatial (trajectory length, variability, range, velocity, and area) body sway variables were extracted using an inertial sensor (at L5) in synchronization with a force plate, during anteroposterior body sway in silence and while exposed to a rhythmic acoustic stimulus (<i>n</i> = 18 young women; two 70-s trials in each condition). Statistics included bivariate correlations between the inertially sensed and the force plate measures, separately, in silence and with a rhythmic acoustic stimulus, as well as for the effect of the rhythmic acoustic stimulus (percentage difference from silence) (<i>p</i> ≤ 0.05, SPSS v25.0).</p><p><strong>Results: </strong>The inertially sensed measures demonstrated good-to-excellent concurrent validity for all temporal and almost all spatial variables, both in silence and with rhythmic acoustic stimulus (<i>r</i> > 0.75, <i>p</i> = 0.000), as well as for the rhythmic acoustic-stimulus effect (<i>r</i> > 0.75, <i>p</i> ≤ 0.05).</p><p><strong>Conclusion: </strong>The inertially sensed measures of the voluntary anteroposterior body sway demonstrated an overall good-to-excellent concurrent validity against those obtained with the force plate \"gold standard,\" both in the silence and the rhythmic acoustic stimulus conditions, as well as for the rhythmic acoustic-stimulus effect. The findings of this pilot study allow the recommendation of inertial sensing for the evaluation of postural control alterations when exposed to rhythmic acoustic stimuli, a condition of increasing interest due to the positive contribution of such stimuli when training or restoring the control of movement.</p>","PeriodicalId":11242,"journal":{"name":"Digital Biomarkers","volume":"5 1","pages":"65-73"},"PeriodicalIF":0.0,"publicationDate":"2021-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1159/000514325","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38890760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation, Acceptance, and Qualification of Digital Measures: From Proof of Concept to Endpoint.","authors":"Jennifer C Goldsack,&nbsp;Ariel V Dowling,&nbsp;David Samuelson,&nbsp;Bray Patrick-Lake,&nbsp;Ieuan Clay","doi":"10.1159/000514730","DOIUrl":"https://doi.org/10.1159/000514730","url":null,"abstract":"<p><p>To support the successful adoption of digital measures into internal decision making and evidence generation for medical product development, we present a unified lexicon to aid communication throughout this process, and highlight key concepts including the critical role of participant engagement in development of digital measures. We detail the steps of bringing a successful proof of concept to scale, focusing on key decisions in the development of a new digital measure: asking the right question, optimized approaches to evaluating new measures, and whether and how to pursue qualification or acceptance. Building on the V3 framework for establishing verification and analytical and clinical validation, we discuss strategic and practical considerations for collecting this evidence, illustrated with concrete examples of trailblazing digital measures in the field.</p>","PeriodicalId":11242,"journal":{"name":"Digital Biomarkers","volume":"5 1","pages":"53-64"},"PeriodicalIF":0.0,"publicationDate":"2021-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1159/000514730","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38890758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detecting Mild Cognitive Impairment via Digital Biomarkers of Cognitive Performance Found in Klondike Solitaire: A Machine-Learning Study.","authors":"Karsten Gielis,&nbsp;Marie-Elena Vanden Abeele,&nbsp;Katrien Verbert,&nbsp;Jos Tournoy,&nbsp;Maarten De Vos,&nbsp;Vero Vanden Abeele","doi":"10.1159/000514105","DOIUrl":"https://doi.org/10.1159/000514105","url":null,"abstract":"<p><strong>Background: </strong>Mild cognitive impairment (MCI) is a condition that entails a slight yet noticeable decline in cognition that exceeds normal age-related changes. Older adults living with MCI have a higher chance of progressing to dementia, which warrants regular cognitive follow-up at memory clinics. However, due to time and resource constraints, this follow-up is conducted at separate moments in time with large intervals in between. Casual games, embedded into the daily life of older adults, may prove to be a less resource-intensive medium that yields continuous and rich data on a patient's cognition.</p><p><strong>Objective: </strong>To explore whether digital biomarkers of cognitive performance, found in the casual card game Klondike Solitaire, can be used to train machine-learning models to discern games played by older adults living with MCI from their healthy counterparts.</p><p><strong>Methods: </strong>Digital biomarkers of cognitive performance were captured from 23 healthy older adults and 23 older adults living with MCI, each playing 3 games of Solitaire with 3 different deck shuffles. These 3 deck shuffles were identical for each participant. Using a supervised stratified, 5-fold, cross-validated, machine-learning procedure, 19 different models were trained and optimized for F1 score.</p><p><strong>Results: </strong>The 3 best performing models, an Extra Trees model, a Gradient Boosting model, and a Nu-Support Vector Model, had a cross-validated F1 training score on the validation set of ≥0.792. The F1 score and AUC of the test set were, respectively, >0.811 and >0.877 for each of these models. These results indicate psychometric properties comparative to common cognitive screening tests.</p><p><strong>Conclusion: </strong>The results suggest that commercial card games, not developed to address specific mental processes, may be used for measuring cognition. The digital biomarkers derived from Klondike Solitaire show promise and may prove useful to fill the current blind spot between consultations.</p>","PeriodicalId":11242,"journal":{"name":"Digital Biomarkers","volume":"5 1","pages":"44-52"},"PeriodicalIF":0.0,"publicationDate":"2021-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1159/000514105","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25536957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-Time Digital Biometric Monitoring during Elite Athletic Competition: System Feasibility with a Wearable Medical-Grade Sensor.","authors":"Mark A Gorski,&nbsp;Stanley M Mimoto,&nbsp;Vivek Khare,&nbsp;Viprali Bhatkar,&nbsp;Arthur H Combs","doi":"10.1159/000513222","DOIUrl":"https://doi.org/10.1159/000513222","url":null,"abstract":"<p><strong>Introduction: </strong>Real-time digital heart rate (HR) monitoring in sports can provide unique physiological insights into athletic performance. However, most HR monitoring of elite athletes is limited to non-real-time, non-competition settings while utilizing sensors that are cumbersome. The present study was undertaken to test the feasibility of using small, wearable medical-grade sensors, paired with a novel technology system, to capture and process real-time HR data from elite athletes during professional competition.</p><p><strong>Methods: </strong>We examined the performance of the BioStamp nPoint® sensor compared to the Polar chest strap HR sensor in 15 Professional Squash Association (PSA) tournament matches in 2019-2020. Fourteen male professional squash players volunteered for the study (age = 23.8 ± 4.9 years; height = 177.9 ± 7.1 cm; weight = 71 ± 7.0 kg), which was approved by the PSA in accordance with their Code of General Conduct and Ethics. Algorithms developed by Sports Data Labs (SDL; Detroit, MI, USA) used proprietary data collection, transmission, and signal processing protocols to produce HR values in real-time during matches. We calculated the mean and maximum HR from both sensors and used widely accepted measures of agreement to compare their performance.</p><p><strong>Results: </strong>The system captured 99.8% of HR data across all matches (range 98.3-100%). The BioStamp's mean HR was 170.4 ± 20.3 bpm, while the Polar's mean HR was 169.4 ± 21.7 bpm. Maximum HR ranged from 182 to 202 bpm (Polar) and 185 to 203 bpm (BioStamp). Spearman's correlation coefficient (<i>r</i> _s) was 0.986 (<i>p</i> < 0.001), indicating a strong correlation between the 2 devices. The mean difference (<i>d</i>) in HR was 1.0 bpm, the mean absolute error was 2.2 bpm, and the percent difference was 0.72%, demonstrating high agreement between device measurements.</p><p><strong>Conclusions: </strong>It is feasible to accurately measure and monitor real-time HR in elite athletes during competition using BioStamp's and SDL's proprietary system. This system facilitates development and understanding of physiological digital biomarkers of athletic performance and physical and psychosocial demands in elite athletic competition.</p>","PeriodicalId":11242,"journal":{"name":"Digital Biomarkers","volume":"5 1","pages":"37-43"},"PeriodicalIF":0.0,"publicationDate":"2021-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1159/000513222","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25539052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}