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For: Arora A, Chakraborty P, Bhatia MPS. Analysis of Data from Wearable Sensors for Sleep Quality Estimation and Prediction Using Deep Learning. Arab J Sci Eng 2020. [DOI: 10.1007/s13369-020-04877-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Number Cited by Other Article(s)
1
Park KM, Lee SE, Lee C, Hwang HD, Yoon DH, Choi E, Lee E. Predicting sleep based on physical activity, light exposure, and Heart rate variability data using wearable devices. Ann Med 2024;56:2405077. [PMID: 39297306 DOI: 10.1080/07853890.2024.2405077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Revised: 07/29/2024] [Accepted: 08/29/2024] [Indexed: 09/21/2024]  Open
2
Oh S, Kweon YS, Shin GH, Lee SW. Association Between Sleep Quality and Deep Learning-Based Sleep Onset Latency Distribution Using an Electroencephalogram. IEEE Trans Neural Syst Rehabil Eng 2024;32:1806-1816. [PMID: 38696294 DOI: 10.1109/tnsre.2024.3396169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/04/2024]
3
Migovich M, Ullal A, Fu C, Peters SU, Sarkar N. Feasibility of wearable devices and machine learning for sleep classification in children with Rett syndrome: A pilot study. Digit Health 2023;9:20552076231191622. [PMID: 37545628 PMCID: PMC10399268 DOI: 10.1177/20552076231191622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2023] [Accepted: 07/13/2023] [Indexed: 08/08/2023]  Open
4
Depress-DCNF: A deep convolutional neuro-fuzzy model for detection of depression episodes using IoMT. Appl Soft Comput 2022. [DOI: 10.1016/j.asoc.2022.108863] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
5
Intervention of Wearables and Smartphones in Real Time Monitoring of Sleep and Behavioral Health: An Assessment Using Adaptive Neuro-Fuzzy Technique. ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2021. [DOI: 10.1007/s13369-021-06078-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
6
Gullapalli BT, Carreiro S, Chapman BP, Ganesan D, Sjoquist J, Rahman T. OpiTrack: A Wearable-based Clinical Opioid Use Tracker with Temporal Convolutional Attention Networks. PROCEEDINGS OF THE ACM ON INTERACTIVE, MOBILE, WEARABLE AND UBIQUITOUS TECHNOLOGIES 2021;5. [PMID: 35291374 DOI: 10.1145/3478107] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
7
Bozkurt F. A Comparative Study on Classifying Human Activities Using Classical Machine and Deep Learning Methods. ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2021. [DOI: 10.1007/s13369-021-06008-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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