Firefly algorithm and DNN for improved contactless heart rate measurement from videos

Rupinder Saini ¹, Pooja Sharma ¹, Saurabh Kumar ²

⁰Rayat Bahra University, Mohali, Kharar, Punjab, India.

Scientific Reports +

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January 6, 2026

View abstract on PubMed

Summary

This study introduces a novel contactless heart rate monitoring system using facial video analysis and a Deep Neural Network with Firefly optimization. This non-invasive method achieves high accuracy for heart rate classification in healthcare and fitness applications.

Area Of Science

Biomedical Engineering
Computer Science
Artificial Intelligence

Background

Contactless heart rate monitoring is crucial for non-invasive health assessment.
Existing methods for facial-based heart rate detection face challenges in accuracy and feature selection.
Deep learning approaches offer potential for improved physiological signal analysis.

Purpose Of The Study

To develop a novel, accurate, and non-invasive system for heart rate measurement using facial video analysis.
To enhance feature selection and classification accuracy for heart rate detection.
To integrate Firefly optimization with a Deep Neural Network (DNN) for superior performance.

Main Methods

Utilized facial video analysis for contactless heart rate measurement.
Implemented a Deep Neural Network (DNN) architecture.
Employed Firefly optimization for feature selection and model optimization.
Evaluated performance using precision, recall, F-measure, and accuracy metrics.

Main Results

Achieved a precision score of 90.22% and a recall score of 94.46%.
Outperformed existing state-of-the-art methods by up to 2.1% in precision, 1.5% in recall, and 2.2% in F-measure.
Demonstrated superior performance in classifying clinically meaningful heart rate categories.

Conclusions

The proposed Firefly optimization-integrated DNN offers a dependable and accurate technique for non-contact heart rate measurement.
This advancement holds significant promise for applications in healthcare, fitness tracking, and stress management.
The method provides a clear advantage for non-contact heart rate classification compared to recent methodologies.

Keywords:

Contactless measurement Deep neural network Firefly optimisation Heart rate detection