Welcome To The Future of Holter Analysis

Precise, Timely,
& Life-Saving

No Detail overlooked, no Patient left waiting, and no life lost due to outdated technology

“The Neural Cloud Solutions team has developed a signal-processing algorithm to label electrocardiographic waveforms. This has created significant interest and activity amongst my cardiology/cardiac electrophysiology colleagues at St Paul's as it allows for more precise and automated analysis of large volumes of electrodiagnostics applied to patients over extended periods. This is critically important as cardiac wearables, including watches and clothing, become more ubiquitous and relevant in the clinical space.”
Dr. Alan Rabinowitz
Cardiologist at St. Paul’s Hospital, Vancouver

The ECG Labeling Neural Network

Our patent-pending, regulatory-pending ECG Labeling Neural Network can take raw 1-Lead and 3-Lead ECG data and output a beat-by-beat analysis and analytics report. The Neural Network understands what an ECG signal looks like and can isolate it from the noise in lengthy recordings. The beat-by-beat analysis includes 12 points of the heartbeat waveform, including onsets and offset of each PQRST peak.
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From this clean signal, the Neural Net can determine the health of that person’s heart. This includes the support in diagnosis of heart conditions, treatment of existing conditions, and metrics on overall heart performance.
The value of this lies in the quick analysis of long ECG files. It generates reports that highlights key features in minutes, rather than manually/semi-manually doing it.
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For Example, 200,000 heartbeats (2-days) takes about 5-6 days to manually go through before a cardiologist can make a diagnosis. Our neural net can get a report back to you within 5-10 minutes. The process shifts from physically doing the analysis and interpretation to confirming the Neural Net's findings.
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We developed this Neural Network platform to help in the analysis process of ECG data. The nature of this Neural Network is a signal processing algorithm that has undergone extensive training on ECGs. Typically, ECG software developers build software to recognize patterns, similar to matching photos. Our Neural Network learns what an ECG actually is through ECG signal processing.
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From this, it identifies irregularities and highlights any key events in the generated report. This in-depth & rapid analysis by our Neural Net speeds up the ECG data and Holter Monitor analysis process. This helps healthcare professionals diagnose and treat heart disease & conditions faster, ultimately benefiting the patients.
Meet The Neural Cloud

Our Team

Paul Duffy
CEO
Esmat Naikyar
President & CPO
Michael Feist
CTO
Talwinder Punni
COO

Origin Story: Revolutionizing Continuous ECG Monitoring

In the heart of the University of Alberta, a dedicated team of researchers were on a mission: to enhance the accuracy of continuous ECG monitoring using wearable technology.

With cardiovascular diseases affecting millions globally, the team recognized the urgent need for better cardiac monitoring solutions. Those that could operate in real-world conditions without compromising performance due to interference from noise.

The researchers delved into the realm of signal processing, focusing on the integration of accelerometers with ECG devices. They aimed to filter out the noise generated by everyday movements. This would ensure the continuous ECG data captured by wearables was as clean and reliable as possible.

However, as they honed their de-noising methodologies, they stumbled upon a surprising challenge. With the success of significant noise reduction, the process included inadvertent cancellation of some critical ECG signals.

This revelation was both a setback and a spark of inspiration. The team realized that they could not simply perform noise removal, they needed a more sophisticated approach. This needed to include understanding and retaining the vital information that ECGs provide. Inspired by these limitations, they began exploring innovative neural networks that could learn and adapt to the complexities of ECG signals.


After countless hours of research, experimentation, and collaboration, the team developed a groundbreaking algorithm tailored specifically for ECG analysis. Traditional methods rely on rigid templates and simple pattern recognition. They designed this neural network to train with the noise.

The network learned to differentiate between true ECG beats and various types of interference. It is able to ultimately recognize the subtleties of each heartbeat through signal isolation.

The breakthrough came when they successfully implemented a beat-by-beat analysis approach. This allows the algorithm to provide detailed insights into cardiac health. It meticulously analyzes each ECG signal and reveals crucial information. The signal cleaning filters out the noise allowing for heart rhythm analysis, variability, and detection of potential anomalies.

The researchers used innovative neural network technology to improve de-noising techniques and set a new standard for ECG analysis. Their solution offered a comprehensive understanding of heart function. This transforms how real-time ECG monitoring through wearables could be utilized in both clinical and everyday settings.

As they look to the future, the team is filled with excitement. They envision a world where wearables equipped with their advanced algorithms could provide real-time, actionable cardiac insights. This will help empower individuals to take control of their heart health. Through perseverance and innovation, they have taken a monumental step toward revolutionizing continuous ECG monitoring, and they are just getting started.
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Join Us in Revolutionizing ECG Analysis
The ECG labeling Neural Network makes analyzing ECG data significantly easier and more efficient compared to traditional methods. AI technology is revolutionizing the way Holter Monitor and ECG data is recorded and processed.
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Patent-Pending | Regulatory Pending