NIHA (Expandable)
NIHA (Neural Intelligent Heart Analyzer) is an innovative software library
that identifies heart abnormalities by analyzing ECGs.
NIHA-HF
(Neural Intelligent Heart Analyzer-Heart Failure)
Detecting heart failure using 30-second lead I ECG
NIHA-HF is an Al-based, standalone software that helps detect heart failure using lead I electrocardiogram (ECG) data.
Note: NIHA-HF has not yet been approved by the FDA.
Heart failure is a complex clinical syndrome of cardiac dysfunction in which the heart is unable to pump blood efficiently to meet the body's needs due to other medical conditions. It is characterized by recurrent episodes and hospitalizations. Heart failure affects more than 64 million people worldwide and is a leading cause of mortality.
Early detection of heart failure is crucial for effective management and improved patient outcomes. However, traditional diagnostic methods can be time-consuming and require extensive clinical expertise.
Addressing these challenges by leveraging complex signal processing and deep learning.
The system was trained using more than 11,000 annotated ECGs by physicians. By analyzing a 30-second lead I ECG, NIHA-HF can detect the presence of heart failure.
Combining advanced signal processing with deep learning, NIHA-HF can be implemented in both standard 12-lead ECG devices and in lead I or similar wearable ECG products.
In the current diagnostic process, a clinician detects heart failure by interviewing patients and obtaining their electrocardiogram, echocardiogram, and laboratory test results. The process can be time-consuming and requires specialized knowledge. NIHA-HF technology is designed to automate the detection of heart failure, helping clinicians make faster and more informed decisions.
NIHA-AF
(NIHA Atrial Fibrillation)
Using a 30-second lead I ECG segment to detect AFib.
NIHA-AF is an Al-based software developed to detect atrial fibrillation (AFib) using lead I of ECG.
Note: NIHA-AF is not approved by FDA.
Atrial fibrillation (AFib) is a common heart rhythm disorder characterized by an irregular and often rapid heart rate. It can lead to serious complications such as stroke and heart failure if not detected and treated. Early and accurate detection of AFib is crucial for preventing these complications and managing the condition effectively.
Combining time-frequency analysis and a neural network, NIHA-AF outputs whether a 30-second ECG segment is indicative of AFib.
The system was trained using approximately 70,000 annotated ECGs from physicians and around 6,000 ECGs from a portable electrocardiograph. By including various arrhythmias in addition to AFib, NIHA-AF detects AFib even with portable and wearable devices. This software can be used with pre-recorded ECGs as well as for daily AFib monitoring.
Stress Index (SI)
Estimating and quantifying stress levels.
SI is an objective indicator to estimate and quantify stress levels using ECGs or pulse signals. SI also provides a solution for stress level comparisons among individuals.
Stress resulting from physical or psychosocial stressors can influence the autonomous nervous system (ANS), where both the sympathetic and parasympathetic nervous systems are involved in the regulation of functions. Heart rate variability (HRV) is a reliable means to observe ANS, which can be an indirect biomarker for stress estimation.
SI is computed using the reciprocal of selected heart rate variability (HRV) indexes including time, frequency domain, and nonlinear features. This computation is designed to facilitate daily monitoring of stress levels for the prevention of lifestyle-related chronic diseases over the long term.
Chronic stress is linked to various health issues, including heart disease, hypertension, and mental health disorders. By providing an objective measure of stress, SI helps individuals and healthcare providers identify and manage stress more effectively.
Electrocardiogram (ECG) Biometric Authentication
Precise. Personalized. Secure.
SIMPLEX QUANTUM’s ECG Biometric Authentication is an AI-based software that uses single-lead ECG as a biometric for personal authentication.
Collaborating with the University of Aizu, SIMPLEX QUANTUM completed US patent registration of this technology designed to accurately authenticate an individual’s ECG waveform data and protect data integrity.
Authentication is essential to protect an individual’s identity, the integrity of sensitive personal data, and the ECG technology that produces the data. Biometrics have shown promise as a next-generation authentication tool because they are difficult to circumvent. ECG signals are especially conducive because they are highly personalized and challenging to counterfeit.
3 heartbeats in 3 seconds.
Our ECG Biometric Authentication software provides rapid and precise identity verification using only 3 heartbeats, approximately 3 seconds for authentication.
For a population of 90 individuals, the accuracy of identification using lead I ECG is as follows:
1-to-1 Authentication: The false rejection rate (FRR, the probability of rejecting the correct individual) is approximately 2%, while the false acceptance rate (FAR, the probability of accepting an incorrect individual) is about 10%.
1-to-N Identification: The accuracy rate of uniquely matching the correct individual is over 92%.
This performance improves in smaller cohorts (fewer than 30 subjects), with both FAR and FRR below 5%. It is possible to adjust the FAR and FRR to suit specific usage conditions.