Video-Based Analysis of Heart Rate Applied to Falls
Falls are the number one cause of unintentional injuries and among the top-ten causes of deaths for older adults. An improved understanding of the causes of falls may lead to better approaches to prevention. Changes in blood pressure and heart rate can contribute to falls. Our goal is to develop tec...
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| Vydané v: | 2018 IEEE International Symposium on Medical Measurements and Applications (MeMeA) s. 1 - 5 |
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| Hlavní autori: | , , , , , , , |
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IEEE
01.06.2018
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| Abstract | Falls are the number one cause of unintentional injuries and among the top-ten causes of deaths for older adults. An improved understanding of the causes of falls may lead to better approaches to prevention. Changes in blood pressure and heart rate can contribute to falls. Our goal is to develop techniques for measuring these parameters during real-life falls. In this paper, we apply advanced video processing techniques to footage of real-life falls in long-term care facilities to measure the heart rate of individuals before, during and after falls. We use an object-tracking algorithm to track a region of interest (ROI), such as the face, neck, hands or legs. We then estimate the heart rate based on subtle color changes in the ROI, which correlate with arterial blood flow. To verify the performance of the videobased method an experiment was conducted where the subject was wearing a pulse oximeter to measure the heart rate while being videotaped. Our results demonstrate that the proposed video-based processing method can be used to accurately capture heart rate variations during a fall. We also evaluate how the accuracy of the heart rate estimation depends on the size of the selected ROI. The proposed system could be used for remote patient monitoring and health informatics for improved detection and identification of the causes of falls. |
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| AbstractList | Falls are the number one cause of unintentional injuries and among the top-ten causes of deaths for older adults. An improved understanding of the causes of falls may lead to better approaches to prevention. Changes in blood pressure and heart rate can contribute to falls. Our goal is to develop techniques for measuring these parameters during real-life falls. In this paper, we apply advanced video processing techniques to footage of real-life falls in long-term care facilities to measure the heart rate of individuals before, during and after falls. We use an object-tracking algorithm to track a region of interest (ROI), such as the face, neck, hands or legs. We then estimate the heart rate based on subtle color changes in the ROI, which correlate with arterial blood flow. To verify the performance of the videobased method an experiment was conducted where the subject was wearing a pulse oximeter to measure the heart rate while being videotaped. Our results demonstrate that the proposed video-based processing method can be used to accurately capture heart rate variations during a fall. We also evaluate how the accuracy of the heart rate estimation depends on the size of the selected ROI. The proposed system could be used for remote patient monitoring and health informatics for improved detection and identification of the causes of falls. |
| Author | Ejupi, Andreas Symes, Bobbi He, Xiaochuan Lo, Bryan Goubran, Rafik Bennett, Stephanie Knoefel, Frank Robinovitch, Stephen |
| Author_xml | – sequence: 1 givenname: Xiaochuan surname: He fullname: He, Xiaochuan organization: Department of Computer and Systems Engineering, Carleton University, Ottawa, Canada – sequence: 2 givenname: Rafik surname: Goubran fullname: Goubran, Rafik organization: Department of Computer and Systems Engineering, Carleton University, Ottawa, Canada – sequence: 3 givenname: Stephanie surname: Bennett fullname: Bennett, Stephanie organization: Department of Computer and Systems Engineering, Carleton University, Ottawa, Canada – sequence: 4 givenname: Stephen surname: Robinovitch fullname: Robinovitch, Stephen organization: Department of Biomedical Physiology and Kinesiology, Simon Fraser University – sequence: 5 givenname: Bobbi surname: Symes fullname: Symes, Bobbi organization: Department of Biomedical Physiology and Kinesiology, Simon Fraser University – sequence: 6 givenname: Bryan surname: Lo fullname: Lo, Bryan organization: Department of Biomedical Physiology and Kinesiology, Simon Fraser University – sequence: 7 givenname: Andreas surname: Ejupi fullname: Ejupi, Andreas organization: Department of Biomedical Physiology and Kinesiology, Simon Fraser University – sequence: 8 givenname: Frank surname: Knoefel fullname: Knoefel, Frank organization: Department of Computer and Systems Engineering, Carleton University, Ottawa, Canada |
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| Snippet | Falls are the number one cause of unintentional injuries and among the top-ten causes of deaths for older adults. An improved understanding of the causes of... |
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| SubjectTerms | Cameras fall analysis Heart rate Object tracking Pulse measurements remote patient monitoring Sociology Statistics Streaming media video analysis |
| Title | Video-Based Analysis of Heart Rate Applied to Falls |
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