Novel Fingertip Image-Based Heart Rate Detection Methods for a Smartphone
We hypothesize that our fingertip image-based heart rate detection methods using smartphone reliably detect the heart rhythm and rate of subjects. We propose fingertip curve line movement-based and fingertip image intensity-based detection methods, which both use the movement of successive fingertip...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2017-02-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/17/2/358 |
| _version_ | 1818016067774054400 |
|---|---|
| author | Rifat Zaman Chae Ho Cho Konrad Hartmann-Vaccarezza Tra Nguyen Phan Gwonchan Yoon Jo Woon Chong |
| author_facet | Rifat Zaman Chae Ho Cho Konrad Hartmann-Vaccarezza Tra Nguyen Phan Gwonchan Yoon Jo Woon Chong |
| author_sort | Rifat Zaman |
| collection | DOAJ |
| description | We hypothesize that our fingertip image-based heart rate detection methods using smartphone reliably detect the heart rhythm and rate of subjects. We propose fingertip curve line movement-based and fingertip image intensity-based detection methods, which both use the movement of successive fingertip images obtained from smartphone cameras. To investigate the performance of the proposed methods, heart rhythm and rate of the proposed methods are compared to those of the conventional method, which is based on average image pixel intensity. Using a smartphone, we collected 120 s pulsatile time series data from each recruited subject. The results show that the proposed fingertip curve line movement-based method detects heart rate with a maximum deviation of 0.0832 Hz and 0.124 Hz using time- and frequency-domain based estimation, respectively, compared to the conventional method. Moreover, another proposed fingertip image intensity-based method detects heart rate with a maximum deviation of 0.125 Hz and 0.03 Hz using time- and frequency-based estimation, respectively. |
| first_indexed | 2024-04-14T07:06:41Z |
| format | Article |
| id | doaj.art-1af7472f33244c09a70c758709b4b94e |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-14T07:06:41Z |
| publishDate | 2017-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-1af7472f33244c09a70c758709b4b94e2022-12-22T02:06:32ZengMDPI AGSensors1424-82202017-02-0117235810.3390/s17020358s17020358Novel Fingertip Image-Based Heart Rate Detection Methods for a SmartphoneRifat Zaman0Chae Ho Cho1Konrad Hartmann-Vaccarezza2Tra Nguyen Phan3Gwonchan Yoon4Jo Woon Chong5Department of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX 79409, USADepartment of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX 79409, USAInstituto de Ingenieria Biológica y Médica, Pontificia Universidad Católica de Chile, Santiago 7820436, ChileDepartment of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX 79409, USADepartment of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX 79409, USADepartment of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX 79409, USAWe hypothesize that our fingertip image-based heart rate detection methods using smartphone reliably detect the heart rhythm and rate of subjects. We propose fingertip curve line movement-based and fingertip image intensity-based detection methods, which both use the movement of successive fingertip images obtained from smartphone cameras. To investigate the performance of the proposed methods, heart rhythm and rate of the proposed methods are compared to those of the conventional method, which is based on average image pixel intensity. Using a smartphone, we collected 120 s pulsatile time series data from each recruited subject. The results show that the proposed fingertip curve line movement-based method detects heart rate with a maximum deviation of 0.0832 Hz and 0.124 Hz using time- and frequency-domain based estimation, respectively, compared to the conventional method. Moreover, another proposed fingertip image intensity-based method detects heart rate with a maximum deviation of 0.125 Hz and 0.03 Hz using time- and frequency-based estimation, respectively.http://www.mdpi.com/1424-8220/17/2/358heart rate detectionhealth monitoringsmartphone discipline |
| spellingShingle | Rifat Zaman Chae Ho Cho Konrad Hartmann-Vaccarezza Tra Nguyen Phan Gwonchan Yoon Jo Woon Chong Novel Fingertip Image-Based Heart Rate Detection Methods for a Smartphone Sensors heart rate detection health monitoring smartphone discipline |
| title | Novel Fingertip Image-Based Heart Rate Detection Methods for a Smartphone |
| title_full | Novel Fingertip Image-Based Heart Rate Detection Methods for a Smartphone |
| title_fullStr | Novel Fingertip Image-Based Heart Rate Detection Methods for a Smartphone |
| title_full_unstemmed | Novel Fingertip Image-Based Heart Rate Detection Methods for a Smartphone |
| title_short | Novel Fingertip Image-Based Heart Rate Detection Methods for a Smartphone |
| title_sort | novel fingertip image based heart rate detection methods for a smartphone |
| topic | heart rate detection health monitoring smartphone discipline |
| url | http://www.mdpi.com/1424-8220/17/2/358 |
| work_keys_str_mv | AT rifatzaman novelfingertipimagebasedheartratedetectionmethodsforasmartphone AT chaehocho novelfingertipimagebasedheartratedetectionmethodsforasmartphone AT konradhartmannvaccarezza novelfingertipimagebasedheartratedetectionmethodsforasmartphone AT tranguyenphan novelfingertipimagebasedheartratedetectionmethodsforasmartphone AT gwonchanyoon novelfingertipimagebasedheartratedetectionmethodsforasmartphone AT jowoonchong novelfingertipimagebasedheartratedetectionmethodsforasmartphone |