How to Accurately measure Arterial Stiffness and Endothelial Dysfunction Accurately with Proven Smartphone Technology Under 3 Minutes.
Category: 🎓Lyfas Publications
All the peer-reviewed scientific research of Lyfas was published in various conference proceedings and scientific and medical journals. This section presents the dissemination of knowledge and clinical wisdom Acculi Lab’s Lyfas team has put up. Most of our journals are open-access and you can download the publications.

Validating Lyfas as a Reliable Mental Health Screening and Monitoring Instrument: a Step Towards Mobile Health Application During COVID-19 PandemicValidating Lyfas as a Reliable Mental Health Screening and Monitoring Instrument: a Step Towards Mobile Health Application During COVID-19 Pandemic
Problem with Questionnaire-Based Existing Mental Health Instruments Mental Health assessments have been performed so far by various mental health instruments(as you can find in our validated free instrument for self-assessment).

Towards Cardiac Risk Monitoring of Duchene Muscular Dystrophy using LyfasTowards Cardiac Risk Monitoring of Duchene Muscular Dystrophy using Lyfas
Learn how Lyfas detects the cardiac risk in Genetic Duchene Muscular Dystrophy disorder

Comparing Heart Rate Variability with Polar H10 Sensor and Pulse Rate Variability with LYFAS: A Novel StudyComparing Heart Rate Variability with Polar H10 Sensor and Pulse Rate Variability with LYFAS: A Novel Study
Read the detailed methodology of validating Lyfas Mobile Application(LMA) against the gold-standard HRV polar-10 belt.

Towards Grading Chest X-rays of COVID-19 Patients Using A Dynamic Radial Basis Function Network ClassifierTowards Grading Chest X-rays of COVID-19 Patients Using A Dynamic Radial Basis Function Network Classifier
Lyfarn about about machine learning tool for grading the X-ray images to detect COVID-19 Pneumonia

Predicting Case Fatality of Dengue Epidemic: Statistical Machine Learning Towards a Virtual DoctorPredicting Case Fatality of Dengue Epidemic: Statistical Machine Learning Towards a Virtual Doctor
Learn how fatality can be measured using simple techniques with our Dengue paper

VIRDOCD: A VIRtual DOCtor to predict dengue fatalityVIRDOCD: A VIRtual DOCtor to predict dengue fatality
Learn how Lyfas Clinical head developed a simple Heuristic based system to classify Dengue severity and then predict the fatality in the dengue cases.

CHAR: A Novel Cloud-Based Live Health Augmented Reality FrameworkCHAR: A Novel Cloud-Based Live Health Augmented Reality Framework
Learn how Lyfas detects vitals by detecting the change in the color around the face with 91% accuracy from camera.

Lyfas® In Enabling Early Detection Of Covid-19 Infection Among Asymptomatic IndividualsLyfas® In Enabling Early Detection Of Covid-19 Infection Among Asymptomatic Individuals
Learn how Lyfas Mobile Application(LMA) detects COVID 19 in Asymptomatic patients with its patent pending technology

A Novel Framework for Prediction and Detection of Myocardial Ischemia with Single Lead ECG and PATA Novel Framework for Prediction and Detection of Myocardial Ischemia with Single Lead ECG and PAT
The Heart Rate Variability and Pulse Arrival Time are combined using a single lead ECG and simultaneous capture of the arterial pulse. The test procedure is carried out on 75

Hrudyalysis: A Novel Cloud-Based ECG Analytics MethodHrudyalysis: A Novel Cloud-Based ECG Analytics Method
Learn how Lyfas Consumer grade handheld ECG can help you detect risks of MI from our hand-held Lyfas ECG device.

Cardiac Risk Assessment for COPD patients from Lyfas, A Clinically Validated Smartphone ApplicationCardiac Risk Assessment for COPD patients from Lyfas, A Clinically Validated Smartphone Application
Lyfas monitors cardiac risks in the COPD patients using non invasive smartphone application and gives timely alert for hospitalization. A Research publication with title "Statistical Validation of Cardiovascular Digital Biomarkers

Lyfas, A Smartphone-Based Subclinical Depression Tracker ISSN 2641-4317Lyfas, A Smartphone-Based Subclinical Depression Tracker ISSN 2641-4317
The study found that 77% of the subjects (84% females and 72% males) showed traces of Subclinical depression, further validated by a senior psychiatrist through a series of consultations. ‘Insomnia’