Heart rate is one of the vital signs for monitoring health. Non-invasive, non-contact assessment of heart rate can lead to safe and potentially telemedicine based monitoring. Thermal videos as a modality for capturing heart rate has been underexplored. Regions with large vessels such as the face can capture the pulsatile change in temperature associated with the blood flow. The use of a machine learning-based approach to capture heart rate from continuous thermal videos is currently lacking. Our present clinical investigation comprises the continuous monitoring of heart rate from a smaller number of samples by using a combination of an efficient deep-learning-based segmentation followed by domain-knowledge-based feature calculation for estimating heart rate from 124 thermal imaging videos comprising 3,628,087 frames of 65 patients, admitted to the pediatric intensive care unit at AIIMS, New Delhi. We hypothesized that periodic fluctuations of thermal intensity over the face can capture heart rate. Frequency domain features for thermal time series were extracted followed by supervised learning using a battery of models. A random forest model yielded the best results with a root mean squared error of 24.54 and mean absolute percentage error of 16.129. Clinical profiling of the model showed a wide range of clinical conditions in the admitted children with acceptable model performance. Affordable and commercially available thermal cameras establish the feasibility and cost viability of exploring deployments for patient heart rate estimation in non-invasive and non-contact environments.

The authors have declared no competing interest.

This work was supported by the Wellcome Trust/DBT India Alliance Fellowship IA/CPHE/14/1/501504 awarded to Tavpritesh Sethi.

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The study was approved by the Institute Ethics Committee AIIMS, New Delhi (IEC/NP-211/08.05.2015) and involved no change in routine patient care.

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

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I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.

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All data produced in the present study are available upon reasonable request to the authors.