These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
213 related articles for article (PubMed ID: 34516390)
1. Early Detection of Symptom Exacerbation in Patients With SARS-CoV-2 Infection Using the Fitbit Charge 3 (DEXTERITY): Pilot Evaluation. Yamagami K; Nomura A; Kometani M; Shimojima M; Sakata K; Usui S; Furukawa K; Takamura M; Okajima M; Watanabe K; Yoneda T JMIR Form Res; 2021 Sep; 5(9):e30819. PubMed ID: 34516390 [TBL] [Abstract][Full Text] [Related]
2. Harnessing wearable device data to improve state-level real-time surveillance of influenza-like illness in the USA: a population-based study. Radin JM; Wineinger NE; Topol EJ; Steinhubl SR Lancet Digit Health; 2020 Feb; 2(2):e85-e93. PubMed ID: 33334565 [TBL] [Abstract][Full Text] [Related]
3. Assessment of Stress and Well-Being of Japanese Employees Using Wearable Devices for Sleep Monitoring Combined With Ecological Momentary Assessment: Pilot Observational Study. Kinoshita S; Hanashiro S; Tsutsumi S; Shiga K; Kitazawa M; Wada Y; Inaishi J; Kashiwagi K; Fukami T; Mashimo Y; Minato K; Kishimoto T JMIR Form Res; 2024 May; 8():e49396. PubMed ID: 38696237 [TBL] [Abstract][Full Text] [Related]
4. Risk factors for severity on admission and the disease progression during hospitalisation in a large cohort of patients with COVID-19 in Japan. Terada M; Ohtsu H; Saito S; Hayakawa K; Tsuzuki S; Asai Y; Matsunaga N; Kutsuna S; Sugiura W; Ohmagari N BMJ Open; 2021 Jun; 11(6):e047007. PubMed ID: 34130961 [TBL] [Abstract][Full Text] [Related]
5. Internet-Based Individualized Cognitive Behavioral Therapy for Shift Work Sleep Disorder Empowered by Well-Being Prediction: Protocol for a Pilot Study. Ito-Masui A; Kawamoto E; Sakamoto R; Yu H; Sano A; Motomura E; Tanii H; Sakano S; Esumi R; Imai H; Shimaoka M JMIR Res Protoc; 2021 Mar; 10(3):e24799. PubMed ID: 33626497 [TBL] [Abstract][Full Text] [Related]
6. Use of Physiological Data From a Wearable Device to Identify SARS-CoV-2 Infection and Symptoms and Predict COVID-19 Diagnosis: Observational Study. Hirten RP; Danieletto M; Tomalin L; Choi KH; Zweig M; Golden E; Kaur S; Helmus D; Biello A; Pyzik R; Charney A; Miotto R; Glicksberg BS; Levin M; Nabeel I; Aberg J; Reich D; Charney D; Bottinger EP; Keefer L; Suarez-Farinas M; Nadkarni GN; Fayad ZA J Med Internet Res; 2021 Feb; 23(2):e26107. PubMed ID: 33529156 [TBL] [Abstract][Full Text] [Related]
7. Early Detection of COVID-19 in Female Athletes Using Wearable Technology. Rentería LI; Greenwalt CE; Johnson S; Kviatkovsky SA; Dupuit M; Angeles E; Narayanan S; Zeleny T; Ormsbee MJ Sports Health; 2024; 16(4):512-517. PubMed ID: 37401442 [TBL] [Abstract][Full Text] [Related]
8. Estimation of Symptom Severity During Chemotherapy From Passively Sensed Data: Exploratory Study. Low CA; Dey AK; Ferreira D; Kamarck T; Sun W; Bae S; Doryab A J Med Internet Res; 2017 Dec; 19(12):e420. PubMed ID: 29258977 [TBL] [Abstract][Full Text] [Related]
9. Clinical Feasibility of Monitoring Resting Heart Rate Using a Wearable Activity Tracker in Patients With Thyrotoxicosis: Prospective Longitudinal Observational Study. Lee JE; Lee DH; Oh TJ; Kim KM; Choi SH; Lim S; Park YJ; Park DJ; Jang HC; Moon JH JMIR Mhealth Uhealth; 2018 Jul; 6(7):e159. PubMed ID: 30006328 [TBL] [Abstract][Full Text] [Related]
10. Inter- and intraindividual variability in daily resting heart rate and its associations with age, sex, sleep, BMI, and time of year: Retrospective, longitudinal cohort study of 92,457 adults. Quer G; Gouda P; Galarnyk M; Topol EJ; Steinhubl SR PLoS One; 2020; 15(2):e0227709. PubMed ID: 32023264 [TBL] [Abstract][Full Text] [Related]
11. Measuring Heart Rate Accurately in Patients With Parkinson Disease During Intense Exercise: Usability Study of Fitbit Charge 4. Colonna G; Hoye J; de Laat B; Stanley G; Ibrahimy A; Tinaz S; Morris ED JMIR Biomed Eng; 2023 Dec; 8():e51515. PubMed ID: 38875680 [TBL] [Abstract][Full Text] [Related]
12. Effect of kaempferol ingestion on physical activity and sleep quality: a double-blind, placebo-controlled, randomized, crossover trial. Ikeda Y; Gotoh-Katoh A; Okada S; Handa S; Sato T; Mizokami T; Saito B Front Nutr; 2024; 11():1386389. PubMed ID: 39155930 [TBL] [Abstract][Full Text] [Related]
13. Accuracy of Consumer Wearable Heart Rate Measurement During an Ecologically Valid 24-Hour Period: Intraindividual Validation Study. Nelson BW; Allen NB JMIR Mhealth Uhealth; 2019 Mar; 7(3):e10828. PubMed ID: 30855232 [TBL] [Abstract][Full Text] [Related]
14. Physiologic Response to the Pfizer-BioNTech COVID-19 Vaccine Measured Using Wearable Devices: Prospective Observational Study. Hajduczok AG; DiJoseph KM; Bent B; Thorp AK; Mullholand JB; MacKay SA; Barik S; Coleman JJ; Paules CI; Tinsley A JMIR Form Res; 2021 Aug; 5(8):e28568. PubMed ID: 34236995 [TBL] [Abstract][Full Text] [Related]
15. Fitbit Usage in Patients With Breast Cancer Undergoing Chemotherapy. Dreher N; Hadeler EK; Hartman SJ; Wong EC; Acerbi I; Rugo HS; Majure MC; Chien AJ; Esserman LJ; Melisko ME Clin Breast Cancer; 2019 Dec; 19(6):443-449.e1. PubMed ID: 31285177 [TBL] [Abstract][Full Text] [Related]
16. Measurement of Heart Rate Using the Polar OH1 and Fitbit Charge 3 Wearable Devices in Healthy Adults During Light, Moderate, Vigorous, and Sprint-Based Exercise: Validation Study. Muggeridge DJ; Hickson K; Davies AV; Giggins OM; Megson IL; Gorely T; Crabtree DR JMIR Mhealth Uhealth; 2021 Mar; 9(3):e25313. PubMed ID: 33764310 [TBL] [Abstract][Full Text] [Related]
17. Clinometric Gait Analysis Using Smart Insoles in Patients With Hemiplegia After Stroke: Pilot Study. Seo M; Shin MJ; Park TS; Park JH JMIR Mhealth Uhealth; 2020 Sep; 8(9):e22208. PubMed ID: 32909949 [TBL] [Abstract][Full Text] [Related]
18. Measuring Daily Compliance With Physical Activity Tracking in Ambulatory Surgery Patients: Comparative Analysis of Five Compliance Criteria. Kelly R; Jones S; Price B; Katz D; McCormick C; Pearce O JMIR Mhealth Uhealth; 2021 Jan; 9(1):e22846. PubMed ID: 33496677 [TBL] [Abstract][Full Text] [Related]
19. Predicting Workers' Stress: Application of a High-Performance Algorithm Using Working-Style Characteristics. Iwamoto H; Nakano S; Tajima R; Kiguchi R; Yoshida Y; Kitanishi Y; Aoki Y JMIR AI; 2024 Aug; 3():e55840. PubMed ID: 39093604 [TBL] [Abstract][Full Text] [Related]
20. Acute Exacerbation of a Chronic Obstructive Pulmonary Disease Prediction System Using Wearable Device Data, Machine Learning, and Deep Learning: Development and Cohort Study. Wu CT; Li GH; Huang CT; Cheng YC; Chen CH; Chien JY; Kuo PH; Kuo LC; Lai F JMIR Mhealth Uhealth; 2021 May; 9(5):e22591. PubMed ID: 33955840 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]