Study Results
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View full resultsBasic Information
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COMPLETED
49 participants
OBSERVATIONAL
2025-01-01
2025-03-16
Brief Summary
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Detailed Description
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Informational data will be collected, such as P-wave amplitude and QRS amplitude and duration to note any morphological ECG signal changes. Human factors (HF) endpoints will be evaluated including: HCP placement according to IFU, subject demonstration of changing electrodes, dexterity for user to perform the task, electrode placement according to skin markings, and the ability of the user to remove and replace the mobiCARE™ device.
Conditions
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Study Design
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COHORT
PROSPECTIVE
Study Groups
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The study population will include adults who are asymptomatic or who may suffer from transient sympt
The study population will include adults who are asymptomatic or who may suffer from transient symptoms such as arrhythmias and/or palpitations, shortness of breath, dizziness, light headedness, pre-syncope, syncope, fatigue, chest pain and/or anxiety; ranging in age, ethnic group, BMI, educational level and gender.
Evaluation of the ECG signal in the nominal location and in three alternate positions
Evaluation of the ECG signal in the nominal location and in three alternate positions to determine if the three alternate positions are interpretable.
Interventions
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Evaluation of the ECG signal in the nominal location and in three alternate positions
Evaluation of the ECG signal in the nominal location and in three alternate positions to determine if the three alternate positions are interpretable.
Eligibility Criteria
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Inclusion Criteria
2. Willing and able to provide informed consent;
3. Able to speak and read English fluently;
4. Participant is ambulatory.
Exclusion Criteria
2. Patients with cardioverter defibrillator;
3. Patients with other implantable electric devices;
4. Currently or has a medical history of skin cancer, rash, skin disorder, keloid, and/or any injury in the chest area;
5. Patients with symptomatic episodes where variations in cardiac performance could result in immediate danger to the patient;
6. Patients with known history of life-threatening arrhythmias;
7. Use in combination with external cardiac defibrillators or high frequency surgical equipment near strong magnetic fields or devices such as MRI;
8. Patients with neuro-stimulator, as it may disrupt the quality of ECG data;
9. Critical care patients;
10. Chest pain at the time of presentation for the study.
18 Years
ALL
No
Sponsors
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Eminence Clinical Research, Inc.
INDUSTRY
Seers Technology Co., Ltd.
INDUSTRY
Responsible Party
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Locations
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MCB Clinical Research Centers, LLC
Colorado Springs, Colorado, United States
Countries
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References
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Kim C, Kim SH, Suh MR. Accuracy and Validity of Commercial Smart Bands for Heart Rate Measurements During Cardiopulmonary Exercise Test. Ann Rehabil Med. 2022 Aug;46(4):209-218. doi: 10.5535/arm.22050. Epub 2022 Aug 31.
Rosol M, Petelczyc M, Gasior JS, Mlynczak M. Prediction of peak oxygen consumption using cardiorespiratory parameters from warmup and submaximal stage of treadmill cardiopulmonary exercise test. PLoS One. 2024 Jan 10;19(1):e0291706. doi: 10.1371/journal.pone.0291706. eCollection 2024.
The Prediction of oxygen consumption during Cardiopulmonary exercise test using Wearable ECG (54th Annual Meeting of the Korean Society of Cardiovascular and Thoracic Surgeons 2022 (Alpensia Resort, Pyeongchang, Korea), 2022.11.03-05
Kwon S, Choi EK, Lee SR, Oh S, Song HS, Lee YS, Han SJ, Lim HE. Comparison of Novel Telemonitoring System Using the Single-lead Electrocardiogram Patch With Conventional Telemetry System. Korean Circ J. 2024 Mar;54(3):140-153. doi: 10.4070/kcj.2023.0252.
Lee KH, Kim YR, Yoon NS et al. Prediction of Atrial Fibrillation with Single-Lead Mobile ECG during Normal Sinus Rhythm using Deep Learning. e-Cardiology/Digital Health, Public Health, Health Economics, Research Methodology - e-Cardiology/Digital Health, Artificial Intelligence (Machine Learning, Deep Learning. 2024;26 (Supplement 1).
Ahn HJ, Choi EK, Lee SR, Kwon S, Song HS, Lee YS, Oh S. Three-Day Monitoring of Adhesive Single-Lead Electrocardiogram Patch for Premature Ventricular Complex: Prospective Study for Diagnosis Validation and Evaluation of Burden Fluctuation. J Med Internet Res. 2024 Mar 21;26:e46098. doi: 10.2196/46098.
Lee HA, Yu W, Choi JD, Lee YS, Park JW, Jung YJ, Sheen SS, Jung J, Haam S, Kim SH, Park JE. Development of Machine Learning Model for VO2max Estimation Using a Patch-Type Single-Lead ECG Monitoring Device in Lung Resection Candidates. Healthcare (Basel). 2023 Oct 30;11(21):2863. doi: 10.3390/healthcare11212863.
Kwon S, Lee SR, Choi EK, Ahn HJ, Song HS, Lee YS, Oh S, Lip GYH. Comparison Between the 24-hour Holter Test and 72-hour Single-Lead Electrocardiogram Monitoring With an Adhesive Patch-Type Device for Atrial Fibrillation Detection: Prospective Cohort Study. J Med Internet Res. 2022 May 9;24(5):e37970. doi: 10.2196/37970.
Kwon S, Lee SR, Choi EK, Ahn HJ, Song HS, Lee YS, Oh S. Validation of Adhesive Single-Lead ECG Device Compared with Holter Monitoring among Non-Atrial Fibrillation Patients. Sensors (Basel). 2021 Apr 30;21(9):3122. doi: 10.3390/s21093122.
Walsh JA 3rd, Topol EJ, Steinhubl SR. Novel wireless devices for cardiac monitoring. Circulation. 2014 Aug 12;130(7):573-81. doi: 10.1161/CIRCULATIONAHA.114.009024. No abstract available.
Provided Documents
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Document Type: Study Protocol and Statistical Analysis Plan
Other Identifiers
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SEER-CLIN-2024-01
Identifier Type: -
Identifier Source: org_study_id
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