The proposed observational study is to evaluate the feasibility of a novel ECG monitoring system leveraging concurrent AI and cloud technologies in long-term continuous monitoring (LTCM) in the clinical environment. It does not intend to use any data or information from the investigational solution to interfere,intervene or affect any clinical decisions made for the participants. Among nearly 2M per year syncope or TIA/stroke patients, 12-15% are cardiac-arrhythmia associated, which usually carries higher risk for long-term disability and even mortality than other-etiologies patients. Proper risk stratification and early initiation of appropriate preventative treatment can result in significant reduction of the cardiac related diseases and their associated mortality. Although LTCM has been proven to be able to detect arrhythmia with high diagnostic yield,the current standard of care has major market pains: 1) days-to-weeks of delay to deliver final report for offline extended Holter; 2) low accuracy in stream arrhythmia detection for online Mobile Cardiac Telemetry; and 3)physicians do not have access to patients' ECG data. ZB eats' solution is aiming to improve today's standard of care by addressing technology accessibility and affordability. ZBPro, ZBeats' alpha prototype was validated against our proprietary dataset as well as public datasets required in ANSI/AAMI EC57, demonstrating algorithms, data transmission and visualization work well as expected. In this Phase I study, the feasibility will be tested in the clinical environment by completing the following specific aims (SA): SA1: setup data collection systems and provide training to clinical personnel prior to recruitment. SA2: Conduct patients' acceptability evaluation by enrolling 60-75 patients to wear the device for up to 7 days. SA3: Evaluate the arrhythmia-capturing capability by conducting physician's satisfaction questionnaires after reviewing the reports generated from thestudy system. SA4: Conduct data analysis and start designing the protocol for Phase II study. This proposal willundergo collaboration among ZBeats, Stony Brook University Hospital and Lankenau Medical Center. The long-term goal is to dramatically improve the current standard of care in LTCM by reducing the time to detection of life-threatening arrhythmia from weeks to minutes for cardiac-related high-risk patients, increase the streaming detection accuracy and reducing the total costs by leveraging AI algorithms, cloud infrastructure and a low-cost flexible-material patch. This cost reduction will lead to more general medical use cases, such as telehealth &Remote Patient Monitoring (RPM) to benefit broader population.
Public Health Relevance Statement: PROJECT NARRATIVE. Proper risk stratification and early diagnosis for initiation of appropriate preventative treatment can result in significant reduction of the cardiac related diseases and their associated mortality. To date, no commercially available products can provide a timely, accurate and affordable way to enable early detection of arrhythmia/cardiac events. We propose a solution to address the technology accessibility and affordability issues to improve today's standard of care, and in the long term it may represent an effective way for remote patient monitoring to benefit broader population.
Project Terms: Affect; Algorithms; Arrhythmia; Cardiac Arrhythmia; Heart Arrhythmias; Award; Clinical Research; Clinical Study; Cost Analysis; Cost Analyses; assess cost; cost assessment; Data Analyses; Data Analysis; data interpretation; Data Collection; Statistical Data Interpretation; Statistical Data Analyses; Statistical Data Analysis; statistical analysis; Diagnosis; Disease; Disorder; Electrocardiogram; ECG; EKG; Electrocardiography; Holter Electrocardiography; Holter Monitoring; Holtmon; Environment; Future; Goals; Medicare; Health Insurance for Aged and Disabled, Title 18; Health Insurance for Disabled Title 18; Title 18; health insurance for disabled; Recording of previous events; History; Hospitalization; Hospital Admission; University Hospitals; Human; Modern Man; Informed Consent; Lead; Pb element; heavy metal Pb; heavy metal lead; Medicaid; mortality; Persons; NIH; National Institutes of Health; United States National Institutes of Health; Painful; Pain; Patients; Physicians; Questionnaires; Research; Risk; social role; Role; Cell Communication and Signaling; Cell Signaling; Intracellular Communication and Signaling; Signal Transduction Systems; Signaling; biological signal transduction; Signal Transduction; Apoplexy; Brain Vascular Accident; Cerebral Stroke; Cerebrovascular Apoplexy; Cerebrovascular Stroke; brain attack; cerebral vascular accident; cerebrovascular accident; Stroke; Survey Instrument; Surveys; Fainting; Syncope; Technology; Telemetries; Telemetry; Phone; Telephone; Testing; Time; Universities; Work; Businesses; Healthcare; health care; Data Set; Dataset; base; improved; Procedures; Clinical; Phase; Medical; Evaluation; Training; disability; Data Bases; data base; Databases; satisfaction; Sample Size; Collaborations; Phase 2 Clinical Trials; phase II protocol; Phase II Clinical Trials; tool; Diagnostic; Life; Adopted; Investigation; Event; Stream; Protocol; Protocols documentation; System; Test Result; Postdoc; Research Associate; post-doc; post-doctoral; Postdoctoral Fellow; Medical center; innovative technologies; early detection; Early Diagnosis; success; novel; Participant; Devices; Manpower; personnel; Human Resources; Reporting; Ischemic Stroke; Causality; causation; disease causation; Etiology; telehealth; Address; Symptoms; Data; Detection; Clinical Data; Enrollment; enroll; Observational Study; Observation research; Observation study; Observational research; Small Business Innovation Research Grant; SBIR; Small Business Innovation Research; Small Business Technology Transfer Research; STTR; Monitor; follow-up; Active Follow-up; active followup; follow up; followed up; followup; Cardiac; cost; design; designing; clinical research site; clinical site; Population; innovation; innovate; innovative; safety net; prototype; commercialization; high risk; standard of care; clinical practice; data exchange; data transfer; data transmission; flexibility; flexible; phase 1 study; Phase I Study; phase 2 study; phase II study; Cloud Computing; Cloud Infrastructure; cloud computer; cloud based; Emergency department visit; ED visit; ER visit; Emergency care visit; Emergency hospital visit; Emergency room visit; data visualization; Preventive treatment; Preventative treatment; risk stratification; stratify risk; recruit; wearable device; wearable electronics; wearable technology; stroke patient; remote patient monitoring; detection sensitivity; participant enrollment; patient enrollment; feasibility testing; artificial intelligence algorithm; AI algorithm
