{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/specmar-fast-heart-rate-estimation-from-ppg","title":"SPECMAR: Fast Heart Rate Estimation from PPG Signal using a Modified Spectral Subtraction Scheme with Composite Motion Artifacts Reference Generation","arxiv_id":"1810.06196","date":"2018-10-15","proceeding":null,"authors":["Mohammad Tariqul Islam","Sk. Tanvir Ahmed","Celia Shahnaz","Shaikh Anowarul Fattah"],"abstract":"The task of heart rate estimation using photoplethysmographic (PPG) signal is\nchallenging due to the presence of various motion artifacts in the recorded\nsignals. In this paper, a fast algorithm for heart rate estimation based on\nmodified SPEctral subtraction scheme utilizing Composite Motion Artifacts\nReference generation (SPECMAR) is proposed using two-channel PPG and three-axis\naccelerometer signals. First, the preliminary noise reduction is obtained by\nfiltering unwanted frequency components from the recorded signals. Next, a\ncomposite motion artifacts reference generation method is developed to be\nemployed in the proposed SPECMAR algorithm for motion artifacts reduction. The\nheart rate is then computed from the noise and motion artifacts reduced PPG\nsignal. Finally, a heart rate tracking algorithm is proposed considering\nneighboring estimates. The performance of the SPECMAR algorithm has been tested\non publicly available PPG database. The average heart rate estimation error is\nfound to be 2.09 BPM on 23 recordings. The Pearson correlation is 0.9907. Due\nto low computational complexity, the method is faster than the comparing\nmethods. The low estimation error, smooth and fast heart rate tracking makes\nSPECMAR an ideal choice to be implemented in wearable devices.","url_abs":"http://arxiv.org/abs/1810.06196v2","url_pdf":"http://arxiv.org/pdf/1810.06196v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"specmar-fast-heart-rate-estimation-from-ppg","repo_url":"https://github.com/tariqul-islam/Photoplethysmographic-Signals","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"heart-rate-estimation","task_name":"Heart rate estimation"}],"methods":[{"method_slug":"ica","method_name":"ICA"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}