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A highly efficient and reliable heart rate monitoring system using smartphone cameras

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Abstract

In the field of healthcare, a fundamental research topic includes the development of a vital signs monitoring system that allows people to monitor their health state so that they can control the same. Given that the heart is at the center of the human system, it is important to constantly monitor the heart beat rate. Hence, recently, heart rate monitoring systems or methods have started to use smartphones (and their built-in cameras) as computing and sensing platforms. These are ubiquitous devices. However, as most smartphones still have low computational power and as camera features differ across smartphones, smartphone-based heart rate computations can suffer from time-consuming processes. Hence, the results can be inaccurate or inconsistent. In this paper, we propose a highly efficient and reliable method to measure the heart rate from the smartphone camera images of fingertips. The method is composed of region of interest-based signal extraction, signal noise/bias reduction using an adaptive threshold scheme, and cycle miss/duplication handling using an iterative outlier elimination scheme. Existing methods require the real-time operation of high-speed processors and work properly on only specific smartphones. In contrast, the proposed method works consistently in real time with high accuracy on smartphones of any level. This is a very important factor because health-care facilities must be universally accessible, including to individuals who cannot afford buying excessively expensive high-performance smartphones.

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Notes

  1. Notice that the proposed signal extraction method can strengthen even the bias.

  2. In our experiments when the heart rates ranged from 60 to 110, each segment of 2.5 seconds length had three or four peaks or valleys. This was most suitable for estimating/offsetting the local bias variation with high precision and robustness.

  3. In the proposed method, signal enhancement similar to the smoothing differentiation has already been done in the previous step. Besides, it can amplify noise to apply only the signal differentiation as in [13]. Fixing the number of peaks may cause unstable heart rate results.

  4. Use of the frame-adaptive threshold [27] resulted in less reliable signals in the experiments with low frame resolutions.

  5. In preliminary experiments, the use of longer videos made little difference in accuracy. Specifically, when using 20 or 30 s long videos, the error rate in Eq. (5) was reduced by below 1 %. Furthermore, long measurement time (holding the finger over the camera lens for a long time) is not welcomed by users. Most existing systems used 5–15 s length [3, 5, 11, 13, 19].

  6. Some functionalities of the RenderScript [24] were not supported in low Anroid API levels and thus only the G3 was available.

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Acknowledgments

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2014R1A1A2059579).

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Authors and Affiliations

  1. Department of Electronic Engineering, Pukyong National University, Busan, 48513, Korea

    Jean-Pierre Lomaliza & Hanhoon Park

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  1. Jean-Pierre Lomaliza
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  2. Hanhoon Park
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Correspondence to Hanhoon Park.

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Lomaliza, JP., Park, H. A highly efficient and reliable heart rate monitoring system using smartphone cameras. Multimed Tools Appl 76, 21051–21071 (2017). https://doi.org/10.1007/s11042-016-4010-1

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  • DOI: https://doi.org/10.1007/s11042-016-4010-1

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