{"doi":"10.3389/fcvm.2020.00120","title":"Changes in Continuous, Long-Term Heart Rate Variability and Individualized Physiological Responses to Wellness and Vacation Interventions Using a Wearable Sensor","abstract":"There are many approaches to maintaining wellness, including taking a simple vacation to attending highly structured wellness retreats, which typically regulate the attendee’s personal time and activities. In a healthy English-speaking cohort of 112 women and men (aged 30-80 years), this study examined the effects of participating in either a 6-day intensive wellness retreat based on Ayurvedic medicine principles or unstructured 6-day vacation at the same wellness center setting. Heart rate variability (HRV) was monitored continuously using a wearable ECG sensor patch for up to 7 days prior to, during, and one-month following participation in the interventions. Additionally, salivary cortisol levels were assessed for all participants at multiple times during the day. Continual HRV monitoring data in the real-world setting was seen to be associated with demographic (HRVALF:βAge =0.98[CI=0.96-0.98], FDR < .001) and physiological characteristics (HRVPLF:β=0.98[CI=0.98-1], FDR=.005) of participants. HRV features were also able to quantify known diurnal variations ( HRVLF/HF:βACT:night vs early-morning=2.69[SE=1.26], FDR < .001) along with notable inter- and intra- person heterogeneity in response to intervention. A statistically significant increase in HRVALF (β = 1.48 [SE=1.1], FDR < .001 ) was observed for all participants during the resort visit. Personalized HRV analysis at an individual level showed a distinct individualized response to intervention, further supporting the utility of using continuous real-world tracking of HRV at an individual level to objectively measure responses to potentially stressful or relaxing settings.","journal":"Frontiers in Cardiovascular Medicine","year":2020,"id":84149,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":10,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9554,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":232385,"name":"Steven R. Steinhubl","orcid":"0000-0002-9256-7914","position":1,"is_corresponding":false},{"id":12556,"name":"Elias Chaibub Neto","orcid":"0000-0002-9575-861X","position":2,"is_corresponding":false},{"id":432127,"name":"Stephan Wegerich","orcid":"0000-0002-0306-7265","position":3,"is_corresponding":false},{"id":432128,"name":"Christine Tara Peterson","orcid":"0000-0002-6951-5753","position":4,"is_corresponding":false},{"id":433166,"name":"Lizzy Weiss","orcid":null,"position":5,"is_corresponding":false},{"id":432129,"name":"Sheila V. Patel","orcid":"0000-0002-6508-8803","position":6,"is_corresponding":false},{"id":432130,"name":"Deepak Chopra","orcid":"0000-0001-5817-3551","position":7,"is_corresponding":false},{"id":361829,"name":"Paul J. Mills","orcid":"0000-0003-4263-7686","position":8,"is_corresponding":false},{"id":27474,"name":"Abhishek Pratap","orcid":"0000-0002-5289-6932","position":0,"is_corresponding":true}],"reference_count":61,"raw_metadata":null,"created_at":"2026-07-18T21:54:50.827092Z","pmid":"32850982","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}