# Heart Rate Detection Using an Event Camera

arXiv: https://arxiv.org/abs/2309.11891 · HTML: https://mlsanity.com/paper/2309.11891/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 18 references that are in the map.
- First posted on arXiv 21 Sep 2023.

## Builds on (most cited first, 4 of 4)

- [Event-based Vision: A Survey](https://mlsanity.com/paper/1904.08405/) (2019)
- [Control and Evaluation of Event Cameras Output Sharpness via Bias](https://mlsanity.com/paper/2210.13929/) (2022)
- [Periodicity Intensity Reveals Insights into Time Series Data: Three Use Cases](https://mlsanity.com/paper/2302.09293/) (2023)
- [Neuromorphic Seatbelt State Detection for In-Cabin Monitoring with Event Cameras](https://mlsanity.com/paper/2308.07802/) (2023)

## Built on by (most cited first, 3 of 3)

- [EMPD: An Event-based Multimodal Physiological Dataset for Remote Pulse Wave Detection](https://mlsanity.com/paper/2603.26699/) (2026)
- [Contactless Cardiac Pulse Monitoring Using Event Cameras](https://mlsanity.com/paper/2505.09529/) (2025)
- [Fusion-E2Pulse: A Multimodal Event-RGB Fusion Network for Non-contact Pulse Wave Reconstruction](https://mlsanity.com/paper/2606.15597/) (2026)

## Abstract (arXiv)

Event cameras, also known as neuromorphic cameras, are an emerging technology that offer advantages over traditional shutter and frame-based cameras, including high temporal resolution, low power consumption, and selective data acquisition. In this study, we propose to harnesses the capabilities of event-based cameras to capture subtle changes in the surface of the skin caused by the pulsatile flow of blood in the wrist region. We investigate whether an event camera could be used for continuous noninvasive monitoring of heart rate (HR). Event camera video data from 25 participants, comprising varying age groups and skin colours, was collected and analysed. Ground-truth HR measurements obtained using conventional methods were used to evaluate of the accuracy of automatic detection of HR from event camera data. Our experimental results and comparison to the performance of other non-contact HR measurement methods demonstrate the feasibility of using event cameras for pulse detection. We also acknowledge the challenges and limitations of our method, such as light-induced flickering and the sub-conscious but naturally-occurring tremors of an individual during data capture.