{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T22:25:35Z","timestamp":1765232735044,"version":"3.38.0"},"reference-count":42,"publisher":"SAGE Publications","issue":"14","license":[{"start":{"date-parts":[[2019,6,4]],"date-time":"2019-06-04T00:00:00Z","timestamp":1559606400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Transactions of the Institute of Measurement and Control"],"published-print":{"date-parts":[[2019,10]]},"abstract":"<jats:p> In this paper, we have analysed correlational studies between high frequency-heart rate variability (HF-HRV) band power and respiration frequency (RF) to identify an optimal narrower HF-HRV band capturing maximum information related to respiration-based heart rate variability. To get exclusive respiration related information, prospective narrower high frequency (HF) band of HRV has been defined with HF band centred around the RF. The RF and HF-HRV band power using fast Fourier transform (FFT) has been computed for all the subjects. The prospective narrower HF bands of HRV defined as [Respiration Frequency (RF) \u00b1\u03b4], with \u03b4 as bandwidth taken to be 0.04, 0.05, 0.06, 0.07, 0.08, 0.10 and 0.12 Hz, has been analysed in this research. Average negative correlation between RF and HF-HRV band power for standard HF band (0.12Hz to 0.4 Hz) with the prospective narrower HF bands has been compared. The results show that average negative correlation for HF band defined by (RF\u00b10.10) comes out to be -0.459278665 and for the standard HF band it comes out to be -0.315965889. This suggests that the narrower HF band defined by (RF\u00b10.10) captures maximum information related to respiration-based heart rate variability. This study may be used for detecting stress and anxiety conditions. The study may be further used to distinguish between normal sinus arrythmia (NSA) and non-NSA. It may further be used to extract respiration rate from electrocardiography (ECG) signal alone. <\/jats:p>","DOI":"10.1177\/0142331219849290","type":"journal-article","created":{"date-parts":[[2019,6,4]],"date-time":"2019-06-04T08:59:09Z","timestamp":1559638749000},"page":"4167-4175","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["Correlational analysis of heart rate variability band power and respiratory frequency to identify an optimal frequency band"],"prefix":"10.1177","volume":"41","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4706-8814","authenticated-orcid":false,"given":"Mahak","family":"Narang","sequence":"first","affiliation":[{"name":"Department of Electrical and Instrumentation Engineering, Thapar Institute of Engineering and Technology, India"}]},{"given":"Mandeep","family":"Singh","sequence":"additional","affiliation":[{"name":"Department of Electrical and Instrumentation Engineering, 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