MaxYield is a proprietary neural-network intelligence layer that ingests raw ECG recordings from any device. It returns a clean, “neuralized” signal and a beat-by-beat PQRST data set. Our Neural Network understands what an ECG waveform looks like and can
isolate the signal from the noise, regardless of recording length. This beat-by-beat data wall includes P, QRS, & T wave onsets, offsets, & time-series intervals.
From this clean signal, MaxYield amplifies the analytical tools clinicians, researchers, and device manufacturers already use. 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. MaxYield™ can tabulate and highlights key features within minutes, rather than manually/semi-manually doing it.
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.
Traditional ECG software recognizes R-peaks or patterns - similar to matching photos. MaxYield sits beneath those algorithms and feeds them a structured data package. Our network learns and understands what an ECG wave actually looks like through ECG signal processing. From this, it is able to isolate the signal from the noise and label the P, QRS, and T Waves.
This in-depth & rapid analysis by our Neural Net helps to speed up the
ECG data and Holter Monitor analysis process. This supports healthcare professionals to diagnose, treat, & research heart disease faster, ultimately benefiting the patients.
MaxYield’s training methods have now been applied to other sensors expanding to PPG (photoplethysmogram) signals. We aim to explore correlations between bodily systems through multi-sensor "Neuralization" to discover new digital biomarkers.