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Completed

NCT Number: NCT05425342

iECG: Recording Chest Leads Using a Smartwatch With a Digital Image Processing Algorithm

The purpose of this study is to evaluate the feasibility of a new method for self-recordable ECGs using a smartwatch coupled with an image processing algorithm. The long-term goal of this project is to establish such a method and to potentially integrate it into telemedical care.

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Key information

Conditions

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Universitiy Hospital Basel

Basel, Canton of Basel-City, 4031, Switzerland

About this study

There is an increasing availability of smartwatches worldwide. Health-related features of these wearables such as heart rate and -rhythm analysis have become increasingly recognised. Some smartwatches are capable of recording an electrocardiogram (ECG) which yields important information about electrical heart activity. Recording a complete ECG with a smartwatch is challenging if the user has no prior medical experience. In this feasibility study we introduce a novel image processing tool that instructs the user to record an ECG using the front camera of an iPad. In a second step, a standard ECG will be recorded by medical staff. The ECGs will then be compared by two board certified cardiologists. The aim of the study is to evaluate the feasibility of self-recorded smartwatch ECGs. If this method can be established, it could markedly expand the diagnostic options for heart and vascular diseases.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Participant ≥ 18 years
  • Ability to record a smartwatch ECG
  • Written informed consent as documented by signature from the participant

Exclusion criteria

  • Smartwatch ECG or conventional ECG cannot be recorded due to comprehensible reasons (allergic reactions, wounds, etc.)
  • Unable or not willing to sign informed consent
  • Significant mental or cognitive impairment that could interfere with the measurements (e.g.

delirium, acute psychotic episode, etc., assessed by recruiting physician)

· Prior knowledge or experience in recording ECGs

Treatment and study plan

Smartwatch ECG

Device

Self-recorded 9-lead smartwatch ECGs

Primary outcomes

  1. Correctly recorded smartwatch ECG lead by patient

    Time frame: 1 hour

    The number of correctly recorded limb (I, II, III) and chest leads (bV1-bV6 where the letter "b" denotes bipolar chest leads) will be assessed. A correctly recorded lead is defined as a complete, 30-second long bipolar electrical signal obtained by the patient with the smartwatch afterpreviously being instructed. The number of correctly recorded smartwatch ECG leads is a measure to determine the feasibility of the method.

Secondary outcomes

  1. Correctly identified chest lead position (V1-V6 vs. bV1-bV6)

    Time frame: 1 hour

    Chest ECG leads obtained with a traditional ECG (V1-V6) will be compared with the ones recorded with a smartwatch (bV1-bV6). The percentage of correctly assigned chest leads will be assessed (e.g. V4 is expected to be assigned to bV4)

  2. Heart rhythm

    Time frame: 1 hour

    ECGs will be assessed for rhythm (eg. sinus rihythm, atrial fibrillation) by two board certified cardiologists

  3. Ventricular depolarisation abnormalities

    Time frame: 1 hour

    ECGs will be assessed for ventricular depolarisation abnormalities (eg. bandle branch blocks) by two board certified cardiologists

  4. Ventricular repolarisation abnormalities

    Time frame: 1 hour

    ECGs will be assessed for ventricular repolarisation abnormalities (eg. ST elevation) by two board certified cardiologists

Sponsors and collaborators

Lead sponsor

University Hospital, Basel, Switzerland

Other

Collaborators

  • University of Basel

Registry information

Official study title

iECG: A Feasibility Study for Recording Chest Leads Using a Smartwatch Coupled With a Digital Image Processing Algorithm

Acronym: iECG

Important dates

Study start
2020
Primary completion
2021
Study completion
2021
First posted
Jun 21, 2022
Registry last updated
Jun 21, 2022

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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