Millions of people around the world are living with arrhythmia or an abnormal heart rhythm, a condition where a person’s heart beats slower or faster than it should, impacting the flow of blood through the body and to the brain. People with arrhythmia are at increased risk of heart disease and stroke.
The good news is that new technologies and approaches are allowing people to actively monitor their heart rhythms. And medical grade innovation is allowing physicians to extend the reach of their practices, enabling high quality remote ECG monitoring and analysis.
Roughly the size of a smartphone, PocketECG is portable, lightweight and easy to use, making patient compliance more manageable. Three leads easily connect from the device to your patient’s chest to reliably provide a constant stream of ECG data. Electrodes can easily be removed and relocated to address any issues of skin sensitivity, without needing to end or restart the study. If a signal is not detected for a prolonged period of time, we will contact your patient to instruct him or her on how to properly reconnect the device.
PocketECG’s easy, single-device configuration eliminates the need for multiple battery packs and charging, as well as potential issues with Bluetooth connections between multiple device. We transmit every labeled beat directly from the ECG monitor to the mobile network.
Whether monitoring a patient for 24-48 hours or up to 30 days, PocketECG captures and streams every beat for a more precise arrhythmia diagnosis.
What do we mean when we say complete data? We asked ourselves, how do we ensure the highest quality statistical analysis? How can we better correlate symptoms and arrhythmia? How do we help physicians accurately distinguish between heart rate during physical activity and arrhythmia for a more complete picture? In creating our technology, we took all of these key considerations to heart.
- Full Disclosure Data
- Symptom Correlation
- Physical Activity Monitoring
Only PocketECG streams and records the full disclosure signal for up to 30 days, capturing every heartbeat to provide clinicians with the most complete data. Because complete data means better quality analysis and comprehensive reporting.
Other devices capture and report on intervals or snapshots in time for a limited time. An arrhythmia event may trigger a device to record a 30 second ECG sample. Only PocketECG captures the onset and offset of every arrhythmia and provides statistical analysis of the complete data set so you know you’re getting the full picture.
For years, patients using ECG holter devices to record their heart rhythm were also asked to keep a paper journal or diary noting any symptoms they might be experiencing – chest pain, dizziness or heart palpitations. Patients can now report a full range of symptoms directly on the touch screen of our monitoring device. PocketECG captures and time-codes symptoms to allow for direct correlation between symptoms and arrhythmia events.
Clinical guidelines recommend that cardiologists use resting heart rate as the baseline measure for determining the best course of therapy for patients with atrial fibrillation. With this in mind, PocketECG, in 2017 announced a new feature — a built-in accelerometer, an electrical device that measures the vibration and acceleration of movement or physical activity. With this built in accelerometer, we not only capture and report heart rhythm, but also heart rate during physical activity and at rest. Importantly, this allows a clinician to establish a true baseline resting rate and differentiate between rate changes due to physical activity and those resulting from an arrhythmia event.
Because PocketECG continuously tracks a patient’s activity the device is able to provide an accurate calculation of HR at rest as recommended. The measurements at rest are taken several minutes after the activity, which gives the heart enough time to recover so the physiological rate can be measured. By using PocketECG, clinicians are able to see burden for each arrhythmia type during activity, post-activity and inactivity, as well as better correlate symptoms with actual events.