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Lactate threshold heart rate and lactate threshold speed are commonly used but\n     require invasive, costly methods. Heart rate variability metrics offer a non-invasive\n     alternative by assessing autonomic nervous system activity. This study evaluated the validity\n     of various heart rate variability metrics in predicting the lactate threshold heart rate and\n     lactate threshold speed during indoor and outdoor graded exercise tests in 19 recreational\n     runners. Heart rate variability thresholds were determined using SD1, SD2, detrended\n     fluctuation analysis scaling exponent for short-term fluctuations, detrended fluctuation\n     analysis scaling exponent for long-term fluctuations, standard deviation of NN intervals, and\n     root mean square of successive RR intervals via the Dmax method, and are referred to as\n      HRVT1 to HRVT6. Indoor graded exercise test results showed that heart\n     rate at heart rate variability threshold often underestimated the lactate threshold heart rate,\n     with all heart rate variability thresholds, except speed at heart rate variability threshold\n     (detrended fluctuation analysis scaling exponent for long-term fluctuations, p=0.06),\n     showing significant differences from lactate threshold. Moderate correlations were observed for\n      HRVT5HR (standard deviation of NN intervals, r=0.66), HRVT2speed\n     (SD2, r=0.56), and HRVT3speed (detrended fluctuation analysis scaling\n     exponent for short-term fluctuations, r=0.70). Outdoor graded exercise tests showed no\n     significant differences between most heart rate variability thresholds and lactate threshold,\n     except HRVT6HR (root mean square of successive RR intervals, p=0.03). Speed\n     at heart rate variability threshold demonstrated moderate correlations (r=0.54\u20130.7) with\n     the lactate threshold speed. While the heart rate variability threshold and lactate threshold\n     may reflect different physiological thresholds, heart rate variability thresholds, particularly\n     those based on detrended fluctuation analysis scaling exponent for long-term fluctuations,\n     showed promise as non-invasive predictors of lactate threshold in recreational runners.<\/jats:p>","DOI":"10.1055\/a-2721-9979","type":"journal-article","created":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T23:00:45Z","timestamp":1760396445000},"page":"304-314","source":"Crossref","is-referenced-by-count":1,"title":["Estimation of Runners\u02bc Lactate Threshold Heart Rate and Speed by Heart Rate\n     Variability"],"prefix":"10.1055","volume":"47","author":[{"given":"Bingyu","family":"Pan","sequence":"first","affiliation":[{"name":"School of Sports Engineering, Beijing Sport University, Beijing,\n     China"},{"name":"China Sports Big Data Center, Beijing Sport University, Beijing,\n     China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanfei","family":"Shen","sequence":"first","affiliation":[{"name":"School of Sports Engineering, Beijing Sport University, Beijing,\n     China"},{"name":"Engineering Research Center of Strength and Conditioning Training\n     Key Core Technology Integrated System and Equipment, Ministry of Education of the People\u02bcs\n     Republic of China, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0017-3975","authenticated-orcid":false,"given":"Changda","family":"Lu","sequence":"additional","affiliation":[{"name":"School of Sport Science, Beijing Sport University, Beijing,\n     China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Siyu","family":"Lu","sequence":"additional","affiliation":[{"name":"School of Sports Engineering, Beijing Sport University, Beijing,\n     China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yiwei","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Sport Science, Beijing Sport University, Beijing,\n     China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qingjun","family":"Xing","sequence":"additional","affiliation":[{"name":"School of Sport Science, Beijing Sport University, Beijing,\n     China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"194","published-online":{"date-parts":[[2025,11,21]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"S2-9","DOI":"10.1123\/ijspp.2016-0403","article-title":"Quantification of training and competition loads in endurance sports: methods and\n     applications","volume":"12","author":"I Mujika","year":"2017","journal-title":"Int J Sports Physiol Perform"},{"issue":"02","key":"ref2","doi-asserted-by":"publisher","first-page":"299","DOI":"10.1139\/h03-023","article-title":"Anaerobic 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