1
|
Kubala AG, Roma PG, Jameson JT, Sessoms PH, Chinoy ED, Rosado LR, Viboch TB, Schrom BJ, Rizeq HN, Gordy PS, Hirsch LDA, Biggs LAT, Russell DW, Markwald RR. Advancing a U.S. navy shipboard infrastructure for sleep monitoring with wearable technology. Appl Ergon 2024; 117:104225. [PMID: 38219375 DOI: 10.1016/j.apergo.2024.104225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 12/20/2023] [Accepted: 01/03/2024] [Indexed: 01/16/2024]
Abstract
Development of fatigue management solutions is critical to U.S. Navy populations. This study explored the operational feasibility and acceptability of commercial wearable devices (Oura Ring and ReadiBand) in a warship environment with 845 Sailors across five ship cohorts during at-sea operations ranging from 10 to 31 days. Participants were required to wear both devices and check-in daily with research staff. Both devices functioned as designed in the environment and reliably collected sleep-wake data. Over 10,000 person-days at-sea, overall prevalence of Oura and ReadiBand use was 69% and 71%, respectively. Individual use rates were 71 ± 38% of days underway for Oura and 59 ± 34% for ReadiBand. Analysis of individual factors showed increasing device use and less device interference with age, and more men than women found the devices comfortable. This study provides initial support that commercial wearables can contribute to infrastructures for operational fatigue management in naval environments.
Collapse
Affiliation(s)
- Andrew G Kubala
- Warfighter Performance Department, Operational Readiness and Health Directorate, Naval Health Research Center, San Diego, CA, USA; Military and Veterans Health Solutions, Leidos Inc., San Diego, CA, USA
| | - Peter G Roma
- Warfighter Performance Department, Operational Readiness and Health Directorate, Naval Health Research Center, San Diego, CA, USA; Military and Veterans Health Solutions, Leidos Inc., San Diego, CA, USA
| | - Jason T Jameson
- Warfighter Performance Department, Operational Readiness and Health Directorate, Naval Health Research Center, San Diego, CA, USA; Military and Veterans Health Solutions, Leidos Inc., San Diego, CA, USA
| | - Pinata H Sessoms
- Warfighter Performance Department, Operational Readiness and Health Directorate, Naval Health Research Center, San Diego, CA, USA
| | - Evan D Chinoy
- Warfighter Performance Department, Operational Readiness and Health Directorate, Naval Health Research Center, San Diego, CA, USA
| | - Luis R Rosado
- Warfighter Performance Department, Operational Readiness and Health Directorate, Naval Health Research Center, San Diego, CA, USA; Military and Veterans Health Solutions, Leidos Inc., San Diego, CA, USA
| | - Trevor B Viboch
- Warfighter Performance Department, Operational Readiness and Health Directorate, Naval Health Research Center, San Diego, CA, USA; Military and Veterans Health Solutions, Leidos Inc., San Diego, CA, USA
| | - Brandon J Schrom
- Warfighter Performance Department, Operational Readiness and Health Directorate, Naval Health Research Center, San Diego, CA, USA; Military and Veterans Health Solutions, Leidos Inc., San Diego, CA, USA
| | - Hedaya N Rizeq
- Warfighter Performance Department, Operational Readiness and Health Directorate, Naval Health Research Center, San Diego, CA, USA; Military and Veterans Health Solutions, Leidos Inc., San Diego, CA, USA
| | - Prayag S Gordy
- Warfighter Performance Department, Operational Readiness and Health Directorate, Naval Health Research Center, San Diego, CA, USA; Military and Veterans Health Solutions, Leidos Inc., San Diego, CA, USA
| | | | - Lcdr Adam T Biggs
- Psychological Health and Resilience Department, Military Population Health Directorate, Naval Health Research Center, San Diego, CA, USA
| | - Dale W Russell
- Commander Naval Surface Force, U.S. Pacific Fleet, San Diego, CA, USA; Department of Psychiatry, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Rachel R Markwald
- Warfighter Performance Department, Operational Readiness and Health Directorate, Naval Health Research Center, San Diego, CA, USA.
| |
Collapse
|
2
|
de Zambotti M, Goldstein C, Cook J, Menghini L, Altini M, Cheng P, Robillard R. State of the science and recommendations for using wearable technology in sleep and circadian research. Sleep 2024; 47:zsad325. [PMID: 38149978 DOI: 10.1093/sleep/zsad325] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 12/21/2023] [Indexed: 12/28/2023] Open
Abstract
Wearable sleep-tracking technology is of growing use in the sleep and circadian fields, including for applications across other disciplines, inclusive of a variety of disease states. Patients increasingly present sleep data derived from their wearable devices to their providers and the ever-increasing availability of commercial devices and new-generation research/clinical tools has led to the wide adoption of wearables in research, which has become even more relevant given the discontinuation of the Philips Respironics Actiwatch. Standards for evaluating the performance of wearable sleep-tracking devices have been introduced and the available evidence suggests that consumer-grade devices exceed the performance of traditional actigraphy in assessing sleep as defined by polysomnogram. However, clear limitations exist, for example, the misclassification of wakefulness during the sleep period, problems with sleep tracking outside of the main sleep bout or nighttime period, artifacts, and unclear translation of performance to individuals with certain characteristics or comorbidities. This is of particular relevance when person-specific factors (like skin color or obesity) negatively impact sensor performance with the potential downstream impact of augmenting already existing healthcare disparities. However, wearable sleep-tracking technology holds great promise for our field, given features distinct from traditional actigraphy such as measurement of autonomic parameters, estimation of circadian features, and the potential to integrate other self-reported, objective, and passively recorded health indicators. Scientists face numerous decision points and barriers when incorporating traditional actigraphy, consumer-grade multi-sensor devices, or contemporary research/clinical-grade sleep trackers into their research. Considerations include wearable device capabilities and performance, target population and goals of the study, wearable device outputs and availability of raw and aggregate data, and data extraction, processing, and analysis. Given the difficulties in the implementation and utilization of wearable sleep-tracking technology in real-world research and clinical settings, the following State of the Science review requested by the Sleep Research Society aims to address the following questions. What data can wearable sleep-tracking devices provide? How accurate are these data? What should be taken into account when incorporating wearable sleep-tracking devices into research? These outstanding questions and surrounding considerations motivated this work, outlining practical recommendations for using wearable technology in sleep and circadian research.
Collapse
Affiliation(s)
- Massimiliano de Zambotti
- Center for Health Sciences, SRI International, Menlo Park, CA, USA
- Lisa Health Inc., Oakland, CA, USA
| | - Cathy Goldstein
- Sleep Disorders Center, Department of Neurology, University of Michigan-Ann Arbor, Ann Arbor, MI, USA
| | - Jesse Cook
- Department of Psychology, University of Wisconsin-Madison, Madison, WI, USA
| | - Luca Menghini
- Department of Psychology and Cognitive Science, University of Trento, Trento, Italy
| | - Marco Altini
- Department of Human Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Philip Cheng
- Sleep Disorders and Research Center, Henry Ford Health, Detroit, MI, USA
| | - Rebecca Robillard
- School of Psychology, University of Ottawa, Ottawa, ON, Canada
- Canadian Sleep Research Consortium, Canada
| |
Collapse
|
3
|
Parent AA, Guadagni V, Rawling JM, Poulin MJ. Performance Evaluation of a New Sport Watch in Sleep Tracking: A Comparison against Overnight Polysomnography in Young Adults. Sensors (Basel) 2024; 24:2218. [PMID: 38610432 PMCID: PMC11014025 DOI: 10.3390/s24072218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/13/2024] [Revised: 02/23/2024] [Accepted: 03/28/2024] [Indexed: 04/14/2024]
Abstract
Introduction: This study aimed to validate the ability of a prototype sport watch (Polar Electro Oy, FI) to recognize wake and sleep states in two trials with and without an interval training session (IT) 6 h prior to bedtime. Methods: Thirty-six participants completed this study. Participants performed a maximal aerobic test and three polysomnography (PSG) assessments. The first night served as a device familiarization night and to screen for sleep apnea. The second and third in-home PSG assessments were counterbalanced with/without IT. Accuracy and agreement in detecting sleep stages were calculated between PSG and the prototype. Results: Accuracy for the different sleep stages (REM, N1 and N2, N3, and awake) as a true positive for the nights without exercise was 84 ± 5%, 64 ± 6%, 81 ± 6%, and 91 ± 6%, respectively, and for the nights with exercise was 83 ± 7%, 63 ± 8%, 80 ± 7%, and 92 ± 6%, respectively. The agreement for the sleep night without exercise was 60.1 ± 8.1%, k = 0.39 ± 0.1, and with exercise was 59.2 ± 9.8%, k = 0.36 ± 0.1. No significant differences were observed between nights or between the sexes. Conclusion: The prototype showed better or similar accuracy and agreement to wrist-worn consumer products on the market for the detection of sleep stages with healthy adults. However, further investigations will need to be conducted with other populations.
Collapse
Affiliation(s)
- Andrée-Anne Parent
- Department of Physiology & Pharmacology, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 1N4, Canada; (A.-A.P.); (V.G.)
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 1N4, Canada
- Libin Cardiovascular Institute of Alberta, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 1N4, Canada
| | - Veronica Guadagni
- Department of Physiology & Pharmacology, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 1N4, Canada; (A.-A.P.); (V.G.)
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 1N4, Canada
| | - Jean M. Rawling
- Department of Family Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 1N4, Canada;
| | - Marc J. Poulin
- Department of Physiology & Pharmacology, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 1N4, Canada; (A.-A.P.); (V.G.)
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 1N4, Canada
- Libin Cardiovascular Institute of Alberta, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 1N4, Canada
- Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 1N4, Canada
- Faculty of Kinesiology, University of Calgary, Calgary, AB T2N 1N4, Canada
- O’Brien Institute of Public Health, Cumming School of Medicine, University of Calgary, Calgary, AB T2N 1N4, Canada
| |
Collapse
|
4
|
Nag DS, Swain A, Sahu S, Chatterjee A, Swain BP. Relevance of sleep for wellness: New trends in using artificial intelligence and machine learning. World J Clin Cases 2024; 12:1196-1199. [PMID: 38524514 PMCID: PMC10955542 DOI: 10.12998/wjcc.v12.i7.1196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Revised: 01/16/2024] [Accepted: 02/05/2024] [Indexed: 02/29/2024] Open
Abstract
Sleep and well-being have been intricately linked, and sleep hygiene is paramount for developing mental well-being and resilience. Although widespread, sleep disorders require elaborate polysomnography laboratory and patient-stay with sleep in unfamiliar environments. Current technologies have allowed various devices to diagnose sleep disorders at home. However, these devices are in various validation stages, with many already receiving approvals from competent authorities. This has captured vast patient-related physiologic data for advanced analytics using artificial intelligence through machine and deep learning applications. This is expected to be integrated with patients' Electronic Health Records and provide individualized prescriptive therapy for sleep disorders in the future.
Collapse
Affiliation(s)
- Deb Sanjay Nag
- Department of Anaesthesiology, Tata Main Hospital, Jamshedpur 831001, Jharkhand, India
| | - Amlan Swain
- Department of Anaesthesiology, Tata Main Hospital, Jamshedpur 831001, Jharkhand, India
| | - Seelora Sahu
- Department of Anaesthesiology, Tata Main Hospital, Jamshedpur 831001, Jharkhand, India
| | - Abhishek Chatterjee
- Department of Anaesthesiology, Tata Main Hospital, Jamshedpur 831001, Jharkhand, India
| | - Bhanu Pratap Swain
- Department of Anaesthesiology, Tata Main Hospital, Jamshedpur 831001, Jharkhand, India
| |
Collapse
|
5
|
Topalidis PI, Baron S, Heib DPJ, Eigl ES, Hinterberger A, Schabus M. From Pulses to Sleep Stages: Towards Optimized Sleep Classification Using Heart-Rate Variability. Sensors (Basel) 2023; 23:9077. [PMID: 38005466 PMCID: PMC10674316 DOI: 10.3390/s23229077] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Revised: 10/31/2023] [Accepted: 11/03/2023] [Indexed: 11/26/2023]
Abstract
More and more people quantify their sleep using wearables and are becoming obsessed in their pursuit of optimal sleep ("orthosomnia"). However, it is criticized that many of these wearables are giving inaccurate feedback and can even lead to negative daytime consequences. Acknowledging these facts, we here optimize our previously suggested sleep classification procedure in a new sample of 136 self-reported poor sleepers to minimize erroneous classification during ambulatory sleep sensing. Firstly, we introduce an advanced interbeat-interval (IBI) quality control using a random forest method to account for wearable recordings in naturalistic and more noisy settings. We further aim to improve sleep classification by opting for a loss function model instead of the overall epoch-by-epoch accuracy to avoid model biases towards the majority class (i.e., "light sleep"). Using these implementations, we compare the classification performance between the optimized (loss function model) and the accuracy model. We use signals derived from PSG, one-channel ECG, and two consumer wearables: the ECG breast belt Polar® H10 (H10) and the Polar® Verity Sense (VS), an optical Photoplethysmography (PPG) heart-rate sensor. The results reveal a high overall accuracy for the loss function in ECG (86.3 %, κ = 0.79), as well as the H10 (84.4%, κ = 0.76), and VS (84.2%, κ = 0.75) sensors, with improvements in deep sleep and wake. In addition, the new optimized model displays moderate to high correlations and agreement with PSG on primary sleep parameters, while measures of reliability, expressed in intra-class correlations, suggest excellent reliability for most sleep parameters. Finally, it is demonstrated that the new model is still classifying sleep accurately in 4-classes in users taking heart-affecting and/or psychoactive medication, which can be considered a prerequisite in older individuals with or without common disorders. Further improving and validating automatic sleep stage classification algorithms based on signals from affordable wearables may resolve existing scepticism and open the door for such approaches in clinical practice.
Collapse
Affiliation(s)
- Pavlos I. Topalidis
- Laboratory for Sleep, Cognition and Consciousness Research, Department of Psychology, Centre for Cognitive Neuroscience Salzburg (CCNS), Paris-Lodron University of Salzburg, 5020 Salzburg, Austria; (P.I.T.); (D.P.J.H.); (E.-S.E.)
| | - Sebastian Baron
- Department of Mathematics, Paris-Lodron University of Salzburg, 5020 Salzburg, Austria
- Department of Artificial Intelligence and Human Interfaces (AIHI), Paris-Lodron University of Salzburg, 5020 Salzburg, Austria
| | - Dominik P. J. Heib
- Laboratory for Sleep, Cognition and Consciousness Research, Department of Psychology, Centre for Cognitive Neuroscience Salzburg (CCNS), Paris-Lodron University of Salzburg, 5020 Salzburg, Austria; (P.I.T.); (D.P.J.H.); (E.-S.E.)
- Institut Proschlaf, 5020 Salzburg, Austria
| | - Esther-Sevil Eigl
- Laboratory for Sleep, Cognition and Consciousness Research, Department of Psychology, Centre for Cognitive Neuroscience Salzburg (CCNS), Paris-Lodron University of Salzburg, 5020 Salzburg, Austria; (P.I.T.); (D.P.J.H.); (E.-S.E.)
| | - Alexandra Hinterberger
- Laboratory for Sleep, Cognition and Consciousness Research, Department of Psychology, Centre for Cognitive Neuroscience Salzburg (CCNS), Paris-Lodron University of Salzburg, 5020 Salzburg, Austria; (P.I.T.); (D.P.J.H.); (E.-S.E.)
| | - Manuel Schabus
- Laboratory for Sleep, Cognition and Consciousness Research, Department of Psychology, Centre for Cognitive Neuroscience Salzburg (CCNS), Paris-Lodron University of Salzburg, 5020 Salzburg, Austria; (P.I.T.); (D.P.J.H.); (E.-S.E.)
| |
Collapse
|
6
|
Li X, Mao JJ, Garland SN, Root J, Li SQ, Ahles T, Liou KT. Comparing sleep measures in cancer survivors: Self-reported sleep diary versus objective wearable sleep tracker. Res Sq 2023:rs.3.rs-3407984. [PMID: 37886444 PMCID: PMC10602054 DOI: 10.21203/rs.3.rs-3407984/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Purpose Cancer survivors are increasingly using wearable fitness trackers, but it's unclear if they match traditional self-reported sleep diaries. We aimed to compare sleep data from Fitbit and the Consensus Sleep Diary (CSD) in this group. Methods We analyzed data from two randomized clinical trials, using both CSD and Fitbit to collect sleep outcomes: total sleep time (TST), wake time after sleep onset (WASO), number of awakenings (NWAK), time in bed (TIB) and sleep efficiency (SE). Insomnia severity was measured by Insomnia Severity Index (ISI). We used the Wilcoxon Singed Ranks Test, Spearman's rank correlation coefficients, and the Mann-Whitney Test to compare sleep outcomes and assess their ability to distinguish insomnia severity levels between CSD and Fitbit data. Results Among 62 participants, compared to CSD, Fitbit recorded longer TST by an average of 14.6 (SD = 84.9) minutes, longer WASO by an average of 28.7 (SD = 40.5) minutes, more NWAK by an average of 16.7 (SD = 6.6) times per night, and higher SE by an average of 7.1% (SD = 14.4); but shorter TIB by an average of 24.4 (SD = 71.5) minutes. All the differences were statistically significant (all p < 0.05), except for TST (p = 0.38). Moderate correlations were found for TST (r = 0.41, p = 0.001) and TIB (r = 0.44, p < 0.001). Compared to no/mild insomnia group, participants with clinical insomnia reported more NWAK (p = 0.009) and lower SE (p = 0.029) as measured by CSD, but Fitbit outcomes didn't. Conclusions TST was the only similar outcome between Fitbit and CSD. Our study highlights the advantages, disadvantages, and clinical utilization of sleep trackers in oncology.
Collapse
Affiliation(s)
| | - Jun J Mao
- Memorial Sloan Kettering Cancer Center
| | | | | | | | - Tim Ahles
- Memorial Sloan Kettering Cancer Center
| | | |
Collapse
|
7
|
Chiang AA, Khosla S. Consumer Wearable Sleep Trackers: Are They Ready for Clinical Use? Sleep Med Clin 2023; 18:311-330. [PMID: 37532372 DOI: 10.1016/j.jsmc.2023.05.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/04/2023]
Abstract
As the importance of good sleep continues to gain public recognition, the market for sleep-monitoring devices continues to grow. Modern technology has shifted from simple sleep tracking to a more granular sleep health assessment. We examine the available functionalities of consumer wearable sleep trackers (CWSTs) and how they perform in healthy individuals and disease states. Additionally, the continuum of sleep technology from consumer-grade to medical-grade is detailed. As this trend invariably grows, we urge professional societies to develop guidelines encompassing the practical clinical use of CWSTs and how best to incorporate them into patient care plans.
Collapse
Affiliation(s)
- Ambrose A Chiang
- Division of Sleep Medicine, Louis Stokes Cleveland VA Medical Center, 10701 East Blvd, Suite 2B-129, Cleveland, OH 44106, USA; Division of Pulmonary, Critical Care, and Sleep Medicine, University Hospitals Cleveland Medical Center, Cleveland, OH, USA; Department of Medicine, Case Western Reserve University, Cleveland, OH, USA.
| | - Seema Khosla
- North Dakota Center for Sleep, 1531 32nd Avenue S Ste 103, Fargo, ND 58103, USA
| |
Collapse
|
8
|
Long H, Li S, Chen Y. Digital health in chronic obstructive pulmonary disease. Chronic Dis Transl Med 2023; 9:90-103. [PMID: 37305103 PMCID: PMC10249197 DOI: 10.1002/cdt3.68] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Revised: 02/11/2023] [Accepted: 04/03/2023] [Indexed: 06/13/2023] Open
Abstract
Chronic obstructive pulmonary disease (COPD) can be prevented and treated through effective care, reducing exacerbations and hospitalizations. Early identification of individuals at high risk of COPD exacerbation is an opportunity for preventive measures. However, many patients struggle to follow their treatment plans because of a lack of knowledge about the disease, limited access to resources, and insufficient clinical support. The growth of digital health-which encompasses advancements in health information technology, artificial intelligence, telehealth, the Internet of Things, mobile health, wearable technology, and digital therapeutics-offers opportunities for improving the early diagnosis and management of COPD. This study reviewed the field of digital health in terms of COPD. The findings showed that despite significant advances in digital health, there are still obstacles impeding its effectiveness. Finally, we highlighted some of the major challenges and possibilities for developing and integrating digital health in COPD management.
Collapse
Affiliation(s)
- Huanyu Long
- Department of Pulmonary and Critical Care MedicinePeking University Third HospitalBeijingChina
| | - Shurun Li
- Peking University Health Science CenterBeijingChina
| | - Yahong Chen
- Department of Pulmonary and Critical Care MedicinePeking University Third HospitalBeijingChina
| |
Collapse
|
9
|
Yang RZ, Li YZ, Liang M, Yu JJ, Chen ML, Qiu JJ, Lin SZ, Wu XD, Zeng K. Stellate Ganglion Block Improves Postoperative Sleep Quality and Analgesia in Patients with Breast Cancer: A Randomized Controlled Trial. Pain Ther 2023; 12:491-503. [PMID: 36652140 PMCID: PMC10036705 DOI: 10.1007/s40122-022-00473-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 12/23/2022] [Indexed: 01/19/2023] Open
Abstract
INTRODUCTION Postoperative impaired sleep quality and pain are associated with adverse outcomes. Stellate ganglion block (SGB) has shown promising results in enhancing sleep quality and alleviating neuropathic pain. This study aimed to investigate the effects of ultrasound-guided SGB on postoperative sleep quality and pain in patients undergoing breast cancer surgery. METHODS This study is a parallel-group randomized controlled clinical trial with two groups: SGB and control. Fifty female patients undergoing breast cancer surgery were randomized in a 1:1 ratio to receive preoperative ultrasound-guided single-injection SGB (SGB group) or just an ultrasound scan (control group). All participants were blinded to the group assignment. The primary outcome was postoperative sleep quality, assessed by the St. Mary's Hospital Sleep Questionnaire and actigraphy 2 days postoperatively. The secondary outcome was postoperative pain, measured by the visual analog scale. RESULTS A total of 48 patients completed the study, with 23 patients in the control group and 25 in the SGB group. The postoperative St. Mary's Hospital Sleep Questionnaire scores were significantly higher in the SGB group than in the control group on 1 day postoperative (30.88 ± 2.44 versus 27.35 ± 4.12 points, P = 0.001). The SGB also increased the total sleep time and sleep efficiency (main actigraphy indicators) during the first two postoperative nights. Compared with the control group, preoperative SGB reduced postoperative pain and the incidence of breast cancer-related lymphedema (20% versus 52.2%, P = 0.02, odds ratio 0.229, 95% confidence interval 0.064-0.821). There were no adverse events related to SGB. CONCLUSION Preoperative ultrasound-guided SGB improves postoperative sleep quality and analgesia in patients undergoing breast cancer surgery. SGB may be a safe and practical treatment to enhance the postoperative quality of life in patients with breast cancer. TRIAL REGISTRATION The study was registered in the Chinese Clinical Trial Registry (ChiCTR2100046620, principal investigator: Kai Zeng, date of registration: 23 May 2021).
Collapse
Affiliation(s)
- Rui-Zhi Yang
- Department of Anesthesiology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, China
- Department of Anesthesiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, 350005, China
| | - Yan-Zhen Li
- Department of Anesthesiology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, China
- Department of Anesthesiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, 350005, China
| | - Min Liang
- Department of Anesthesiology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, China
- Department of Anesthesiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, 350005, China
| | - Jian-Jun Yu
- Department of Anesthesiology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, China
- Department of Anesthesiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, 350005, China
| | - Ming-Li Chen
- Department of Anesthesiology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, China
- Department of Anesthesiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, 350005, China
| | - Jin-Jia Qiu
- Department of Anesthesiology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, China
- Department of Anesthesiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, 350005, China
| | - Shi-Zhu Lin
- Department of Anesthesiology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, China
- Department of Anesthesiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, 350005, China
| | - Xiao-Dan Wu
- Department of Anesthesiology, Fujian Provincial Hospital, Fujian Provincial Clinical Medical College, Fujian Medical University, Fuzhou, 350001, China.
| | - Kai Zeng
- Department of Anesthesiology, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, Fuzhou, 350212, China.
- Department of Anesthesiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, 350005, China.
| |
Collapse
|
10
|
Chen Y, Zhou E, Wang Y, Wu Y, Xu G, Chen L. The past, present, and future of sleep quality assessment and monitoring. Brain Res 2023; 1810:148333. [PMID: 36931581 DOI: 10.1016/j.brainres.2023.148333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 03/09/2023] [Accepted: 03/12/2023] [Indexed: 03/17/2023]
Abstract
Sleep quality is considered to be an individual's self-satisfaction with all aspects of the sleep experience. Good sleep not only improves a person's physical, mental and daily functional health, but also improves the quality-of-life level to some extent. In contrast, chronic sleep deprivation can increase the risk of diseases such as cardiovascular diseases, metabolic dysfunction and cognitive and emotional dysfunction, and can even lead to increased mortality. The scientific evaluation and monitoring of sleep quality is an important prerequisite for safeguarding and promoting the physiological health of the body. Therefore, we have compiled and reviewed the existing methods and emerging technologies commonly used for subjective and objective evaluation and monitoring of sleep quality, and found that subjective sleep evaluation is suitable for clinical screening and large-scale studies, while objective evaluation results are more intuitive and scientific, and in the comprehensive evaluation of sleep, if we want to get more scientific monitoring results, we should combine subjective and objective monitoring and dynamic monitoring.
Collapse
Affiliation(s)
- Yanyan Chen
- School of Physical Education, Jianghan University, Wuhan Hubei, 430056, China
| | - Enyuan Zhou
- School of Physical Education, Jianghan University, Wuhan Hubei, 430056, China
| | - Yu Wang
- School of Physical Education, Jianghan University, Wuhan Hubei, 430056, China
| | - Yuxiang Wu
- School of Physical Education, Jianghan University, Wuhan Hubei, 430056, China
| | - Guodong Xu
- School of Physical Education, Jianghan University, Wuhan Hubei, 430056, China
| | - Lin Chen
- School of Physical Education, Jianghan University, Wuhan Hubei, 430056, China.
| |
Collapse
|
11
|
Ghosh A, Nag S, Gomes A, Gosavi A, Ghule G, Kundu A, Purohit B, Srivastava R. Applications of Smart Material Sensors and Soft Electronics in Healthcare Wearables for Better User Compliance. Micromachines (Basel) 2022; 14:121. [PMID: 36677182 PMCID: PMC9862021 DOI: 10.3390/mi14010121] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 12/25/2022] [Accepted: 12/27/2022] [Indexed: 06/17/2023]
Abstract
The need for innovation in the healthcare sector is essential to meet the demand of a rapidly growing population and the advent of progressive chronic ailments. Over the last decade, real-time monitoring of health conditions has been prioritized for accurate clinical diagnosis and access to accelerated treatment options. Therefore, the demand for wearable biosensing modules for preventive and monitoring purposes has been increasing over the last decade. Application of machine learning, big data analysis, neural networks, and artificial intelligence for precision and various power-saving approaches are used to increase the reliability and acceptance of smart wearables. However, user compliance and ergonomics are key areas that need focus to make the wearables mainstream. Much can be achieved through the incorporation of smart materials and soft electronics. Though skin-friendly wearable devices have been highlighted recently for their multifunctional abilities, a detailed discussion on the integration of smart materials for higher user compliance is still missing. In this review, we have discussed the principles and applications of sustainable smart material sensors and soft electronics for better ergonomics and increased user compliance in various healthcare devices. Moreover, the importance of nanomaterials and nanotechnology is discussed in the development of smart wearables.
Collapse
Affiliation(s)
- Arnab Ghosh
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India
| | - Sagnik Nag
- Department of Biotechnology, School of Biosciences & Technology, Vellore Institute of Technology (VIT), Tiruvalam Road, Vellore 632014, Tamil Nadu, India
| | - Alyssa Gomes
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India
| | - Apurva Gosavi
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India
| | - Gauri Ghule
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India
| | - Aniket Kundu
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India
| | - Buddhadev Purohit
- DTU Bioengineering, Technical University of Denmark, Søltofts Plads 221, 2800 Kongens Lyngby, Denmark
| | - Rohit Srivastava
- Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India
| |
Collapse
|
12
|
Kumar S, Victoria-Castro AM, Melchinger H, O'Connor KD, Psotka M, Desai NR, Ahmad T, Wilson FP. Wearables in Cardiovascular Disease. J Cardiovasc Transl Res 2022. [PMID: 36085432 DOI: 10.1007/s12265-022-10314-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 08/29/2022] [Indexed: 10/14/2022]
Abstract
Wearable devices stand to revolutionize the way healthcare is delivered. From consumer devices that provide general health information and screen for medical conditions to medical-grade devices that allow collection of larger datasets that include multiple modalities, wearables have a myriad of potential uses, especially in cardiovascular disorders. In this review, we summarize the underlying technologies employed in these devices and discuss the regulatory and economic aspects of such devices as well as the future implications of their use.
Collapse
|
13
|
Chakrabarti S, Biswas N, Jones LD, Kesari S, Ashili S. Smart Consumer Wearables as Digital Diagnostic Tools: A Review. Diagnostics (Basel) 2022; 12:2110. [PMID: 36140511 PMCID: PMC9498278 DOI: 10.3390/diagnostics12092110] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 08/26/2022] [Accepted: 08/29/2022] [Indexed: 11/17/2022] Open
Abstract
The increasing usage of smart wearable devices has made an impact not only on the lifestyle of the users, but also on biological research and personalized healthcare services. These devices, which carry different types of sensors, have emerged as personalized digital diagnostic tools. Data from such devices have enabled the prediction and detection of various physiological as well as psychological conditions and diseases. In this review, we have focused on the diagnostic applications of wrist-worn wearables to detect multiple diseases such as cardiovascular diseases, neurological disorders, fatty liver diseases, and metabolic disorders, including diabetes, sleep quality, and psychological illnesses. The fruitful usage of wearables requires fast and insightful data analysis, which is feasible through machine learning. In this review, we have also discussed various machine-learning applications and outcomes for wearable data analyses. Finally, we have discussed the current challenges with wearable usage and data, and the future perspectives of wearable devices as diagnostic tools for research and personalized healthcare domains.
Collapse
|
14
|
Rentz LE, Bryner RW, Ramadan J, Rezai A, Galster SM. Full-Body Photobiomodulation Therapy Is Associated with Reduced Sleep Durations and Augmented Cardiorespiratory Indicators of Recovery. Sports (Basel) 2022; 10:sports10080119. [PMID: 36006085 PMCID: PMC9414854 DOI: 10.3390/sports10080119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 07/27/2022] [Accepted: 07/29/2022] [Indexed: 11/29/2022] Open
Abstract
Research is emerging on the use of Photobiomodulation therapy (PBMT) and its potential for augmenting human performance, however, relatively little research exists utilizing full-body administration methods. As such, further research supporting the efficacy of whole-body applications of PBMT for behavioral and physiological modifications in applicable, real-world settings are warranted. The purpose of this analysis was to observe cardiorespiratory and sleep patterns surrounding the use of full-body PBMT in an elite cohort of female soccer players. Members of a women’s soccer team in a “Power 5 conference” of the National Collegiate Athletic Association (NCAA) were observed across one competitive season while wearing an OURA Ring nightly and a global positioning system (GPS) sensor during training. Within-subject comparisons of cardiorespiratory physiology, sleep duration, and sleep composition were evaluated the night before and after PBMT sessions completed as a standard of care for team recovery. Compared to pre-intervention, mean heart rate (HR) was significantly lower the night after a PBMT session (p = 0.0055). Sleep durations were also reduced following PBMT, with total sleep time (TST) averaging 40 min less the night after a session (p = 0.0006), as well as significant reductions in light sleep (p = 0.0307) and rapid eye movement (REM) sleep durations (p = 0.0019). Sleep durations were still lower following PBMT, even when controlling for daily and accumulated training loads. Enhanced cardiorespiratory indicators of recovery following PBMT, despite significant reductions in sleep duration, suggest that it may be an effective modality for maintaining adequate recovery from the high stress loads experienced by elite athletes.
Collapse
Affiliation(s)
- Lauren E. Rentz
- Division of Exercise Physiology, West Virginia University School of Medicine, Morgantown, WV 26506, USA;
- Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV 26506, USA; (J.R.); (A.R.); (S.M.G.)
- Correspondence:
| | - Randy W. Bryner
- Division of Exercise Physiology, West Virginia University School of Medicine, Morgantown, WV 26506, USA;
| | - Jad Ramadan
- Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV 26506, USA; (J.R.); (A.R.); (S.M.G.)
| | - Ali Rezai
- Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV 26506, USA; (J.R.); (A.R.); (S.M.G.)
| | - Scott M. Galster
- Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV 26506, USA; (J.R.); (A.R.); (S.M.G.)
| |
Collapse
|
15
|
Stein MA, Zulauf-McCurdy C, DelRosso LM. Attention Deficit Hyperactivity Disorder Medications and Sleep. Child Adolesc Psychiatr Clin N Am 2022; 31:499-514. [PMID: 35697398 DOI: 10.1016/j.chc.2022.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Sleep problems are common and often increase when initiating pharmacotherapy for ADHD. Stimulants are commonly associated with delayed sleep onset/insomnia although nonstimulants can be associated with daytime sleepiness. There is a wide variability in severity and duration of sleep effects, but most effects are mild and improve over time. Although sleep problems occur in all age groups, preschoolers and adolescents appear to be more vulnerable to adverse effects on sleep than adults and children. Interventions to improve sleep include behavioral therapy, changing dose schedules or formulations, and adding a sleep-promoting agent such as melatonin.
Collapse
|
16
|
Chinoy ED, Cuellar JA, Jameson JT, Markwald RR. Performance of Four Commercial Wearable Sleep-Tracking Devices Tested Under Unrestricted Conditions at Home in Healthy Young Adults. Nat Sci Sleep 2022; 14:493-516. [PMID: 35345630 PMCID: PMC8957400 DOI: 10.2147/nss.s348795] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 02/21/2022] [Indexed: 12/22/2022] Open
Abstract
PURPOSE Commercial wearable sleep-tracking devices are growing in popularity and in recent studies have performed well against gold standard sleep measurement techniques. However, most studies were conducted in controlled laboratory conditions. We therefore aimed to test the performance of devices under naturalistic unrestricted home sleep conditions. PARTICIPANTS AND METHODS Healthy young adults (n = 21; 12 women, 9 men; 29.0 ± 5.0 years, mean ± SD) slept at home under unrestricted conditions for 1 week using a set of commercial wearable sleep-tracking devices and completed daily sleep diaries. Devices included the Fatigue Science Readiband, Fitbit Inspire HR, Oura ring, and Polar Vantage V Titan. Participants also wore a research-grade actigraphy watch (Philips Respironics Actiwatch 2) for comparison. To assess performance, all devices were compared with a high performing mobile sleep electroencephalography headband device (Dreem 2). Analyses included epoch-by-epoch and sleep summary agreement comparisons. RESULTS Devices accurately tracked sleep-wake summary metrics (ie, time in bed, total sleep time, sleep efficiency, sleep latency, wake after sleep onset) on most nights but performed best on nights with higher sleep efficiency. Epoch-by-epoch sensitivity (for sleep) and specificity (for wake), respectively, were as follows: Actiwatch (0.95, 0.35), Fatigue Science (0.94, 0.40), Fitbit (0.93, 0.45), Oura (0.94, 0.41), and Polar (0.96, 0.35). Sleep stage-tracking performance was mixed, with high variability. CONCLUSION As in previous studies, all devices were better at detecting sleep than wake, and most devices compared favorably to actigraphy in wake detection. Devices performed best on nights with more consolidated sleep patterns. Unrestricted sleep TIB differences were accurately tracked on most nights. High variability in sleep stage-tracking performance suggests that these devices, in their current form, are still best utilized for tracking sleep-wake outcomes and not sleep stages. Most commercial wearables exhibited promising performance for tracking sleep-wake in real-world conditions, further supporting their consideration as an alternative to actigraphy.
Collapse
Affiliation(s)
- Evan D Chinoy
- Sleep, Tactical Efficiency, and Endurance Laboratory, Warfighter Performance Department, Naval Health Research Center, San Diego, CA, USA.,Leidos, Inc., San Diego, CA, USA
| | - Joseph A Cuellar
- Sleep, Tactical Efficiency, and Endurance Laboratory, Warfighter Performance Department, Naval Health Research Center, San Diego, CA, USA.,Leidos, Inc., San Diego, CA, USA
| | - Jason T Jameson
- Sleep, Tactical Efficiency, and Endurance Laboratory, Warfighter Performance Department, Naval Health Research Center, San Diego, CA, USA.,Leidos, Inc., San Diego, CA, USA
| | - Rachel R Markwald
- Sleep, Tactical Efficiency, and Endurance Laboratory, Warfighter Performance Department, Naval Health Research Center, San Diego, CA, USA
| |
Collapse
|
17
|
Ghorbani S, Golkashani HA, Chee NIYN, Teo TB, Dicom AR, Yilmaz G, Leong RLF, Ong JL, Chee MWL. Multi-Night at-Home Evaluation of Improved Sleep Detection and Classification with a Memory-Enhanced Consumer Sleep Tracker. Nat Sci Sleep 2022; 14:645-660. [PMID: 35444483 PMCID: PMC9015046 DOI: 10.2147/nss.s359789] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 03/31/2022] [Indexed: 12/13/2022] Open
Abstract
PURPOSE To evaluate the benefits of applying an improved sleep detection and staging algorithm on minimally processed multi-sensor wearable data collected from older generation hardware. PATIENTS AND METHODS 58 healthy, East Asian adults aged 23-69 years (M = 37.10, SD = 13.03, 32 males), each underwent 3 nights of PSG at home, wearing 2nd Generation Oura Rings equipped with additional memory to store raw data from accelerometer, infra-red photoplethysmography and temperature sensors. 2-stage and 4-stage sleep classifications using a new machine-learning algorithm (Gen3) trained on a diverse and independent dataset were compared to the existing consumer algorithm (Gen2) for whole-night and epoch-by-epoch metrics. RESULTS Gen 3 outperformed its predecessor with a mean (SD) accuracy of 92.6% (0.04), sensitivity of 94.9% (0.03), and specificity of 78.5% (0.11); corresponding to a 3%, 2.8% and 6.2% improvement from Gen2 across the three nights, with Cohen's d values >0.39, t values >2.69, and p values <0.01. Notably, Gen 3 showed robust performance comparable to PSG in its assessment of sleep latency, light sleep, rapid eye movement (REM), and wake after sleep onset (WASO) duration. Participants <40 years of age benefited more from the upgrade with less measurement bias for total sleep time (TST), WASO, light sleep and sleep efficiency compared to those ≥40 years. Males showed greater improvements on TST and REM sleep measurement bias compared to females, while females benefitted more for deep sleep measures compared to males. CONCLUSION These results affirm the benefits of applying machine learning and a diverse training dataset to improve sleep measurement of a consumer wearable device. Importantly, collecting raw data with appropriate hardware allows for future advancements in algorithm development or sleep physiology to be retrospectively applied to enhance the value of longitudinal sleep studies.
Collapse
Affiliation(s)
- Shohreh Ghorbani
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Hosein Aghayan Golkashani
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Nicholas I Y N Chee
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Teck Boon Teo
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Andrew Roshan Dicom
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Gizem Yilmaz
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Ruth L F Leong
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Ju Lynn Ong
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Michael W L Chee
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| |
Collapse
|
18
|
Chang T, Li H, Zhang N, Jiang X, Yu X, Yang Q, Jin Z, Meng H, Chang L. Highly integrated watch for noninvasive continual glucose monitoring. Microsyst Nanoeng 2022; 8:25. [PMID: 35310514 PMCID: PMC8866463 DOI: 10.1038/s41378-022-00355-5] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Revised: 12/25/2021] [Accepted: 01/12/2022] [Indexed: 05/08/2023]
Abstract
This article reports a highly integrated watch for noninvasive continual blood glucose monitoring. The watch employs a Nafion-coated flexible electrochemical sensor patch fixed on the watchband to obtain interstitial fluid (ISF) transdermally at the wrist. This reverse iontophoresis-based extraction method eliminates the pain and inconvenience that traditional fingerstick blood tests pose in diabetic patients' lives, making continual blood glucose monitoring practical and easy. All electronic modules, including a rechargeable power source and other modules for signal processing and wireless transmission, are integrated onto a watch face-sized printed circuit board (PCB), enabling comfortable wearing of this continual glucose monitor. Real-time blood glucose levels are displayed on the LED screen of the watch and can also be checked with the smartphone user interface. With 23 volunteers, the watch demonstrated 84.34% clinical accuracy in the Clarke error grid analysis (zones A + B). In the near future, commercial products could be developed based on this lab-made prototype to provide the public with noninvasive continual glucose monitoring.
Collapse
Affiliation(s)
- Tianrui Chang
- Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, 100083 China
| | - Hu Li
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Nianrong Zhang
- General Surgery Department & Obesity and Metabolic Disease Center, China-Japan Friendship Hospital, Beijing, 100029 China
| | - Xinran Jiang
- Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, 100083 China
| | - Xinge Yu
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Qingde Yang
- Sense Future (HangZhou) Co., Ltd, Hangzhou, 311217 China
| | - Zhiyuan Jin
- Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, 100083 China
| | - Hua Meng
- General Surgery Department & Obesity and Metabolic Disease Center, China-Japan Friendship Hospital, Beijing, 100029 China
| | - Lingqian Chang
- Key Laboratory of Biomechanics and Mechanobiology, Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, 100083 China
| |
Collapse
|
19
|
Alameri F, Aldaheri N, Almesmari S, Basaloum M, Albeshr NA, Simsekler MCE, Ugwuoke NV, Dalkilinc M, Al Qubaisi M, Campos LA, Almahmeed W, Alefishat E, Al Tunaiji H, Baltatu OC. Burnout and Cardiovascular Risk in Healthcare Professionals During the COVID-19 Pandemic. Front Psychiatry 2022; 13:867233. [PMID: 35444572 PMCID: PMC9014179 DOI: 10.3389/fpsyt.2022.867233] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 02/25/2022] [Indexed: 11/20/2022] Open
Abstract
INTRODUCTION The objective of this study was to investigate the psychosocial and cardiovascular markers in healthcare professionals during the COVID-19 pandemic. METHODS This was a STROBE compliant, blended exploratory study. Residents, staff physicians, nurses, and auxiliary healthcare professionals from both inpatient and outpatient medicine services were recruited using a planned random probability sample. The Maslach Burnout Inventory (MBI), Fuster-BEWAT score (FBS), and socio-demographic factors, as well as sleep quality, were studied. The correlations between burnout severity and cardiovascular risk were examined using multivariable linear regression models adjusted for confounding variables, such as sociodemographic and anthropometric characteristics. RESULTS The regression analysis with FBS as the outcome showed a negative association between cardiovascular health and emotional exhaustion [Coef.(95%CI): -0.029 (-0.048, -0.01), p = 0.002]. The higher the emotional exhaustion the lower the cardiovascular health. Further, the model showed a positive association between personal accomplishment and cardiovascular health [Coef.(95%CI): 0.045 (0.007, 0.082), p = 0.02]. Emotional exhaustion was significantly positive correlated with REM sleep and light average (Spearman's rank correlation: 0.37 and 0.35, respectively, with P < 0.05). CONCLUSION The data from this study show that healthcare practitioners who are with burnout and emotional exhaustion have an elevated cardiovascular risk, however, causality cannot be determined. As an adaptive response to stressful situations, REM sleep increases. The findings of this study may be relevant in creating preventive strategies for burnout and cardiovascular risk reduction or prevention. CLINICAL TRIAL REGISTRATION [www.ClinicalTrials.gov], identifier [NCT04422418].
Collapse
Affiliation(s)
- Fayeza Alameri
- Zayed Military Hospital, Abu Dhabi, United Arab Emirates
| | - Noura Aldaheri
- Zayed Military Hospital, Abu Dhabi, United Arab Emirates
| | | | - Manea Basaloum
- Zayed Military Hospital, Abu Dhabi, United Arab Emirates
| | | | | | - Nnamdi Valbosco Ugwuoke
- Department of Pharmacology, College of Medicine and Health Sciences, Khalifa University, Abu Dhabi, United Arab Emirates
| | | | - Mai Al Qubaisi
- Zayed Military Hospital, Abu Dhabi, United Arab Emirates
| | - Luciana Aparecida Campos
- Department of Public Health and Epidemiology, College of Medicine and Health Sciences, Khalifa University, Abu Dhabi, United Arab Emirates.,Center of Innovation, Technology and Education (CITE) at Anhembi Morumbi University - Anima Institute, São José dos Campos, Brazil
| | - Wael Almahmeed
- Heart and Vascular Institute - Cleveland Clinic, Abu Dhabi, United Arab Emirates
| | - Eman Alefishat
- Department of Pharmacology, College of Medicine and Health Sciences, Khalifa University, Abu Dhabi, United Arab Emirates.,Department of Biopharmaceutics and Clinical Pharmacy, Faculty of Pharmacy, The University of Jordan, Amman, Jordan.,Center for Biotechnology, Khalifa University, Abu Dhabi, United Arab Emirates
| | - Hashel Al Tunaiji
- Zayed Military Hospital, Abu Dhabi, United Arab Emirates.,Academic and Research Committee, Zayed Military University, Abu Dhabi, United Arab Emirates
| | - Ovidiu Constantin Baltatu
- Department of Pharmacology, College of Medicine and Health Sciences, Khalifa University, Abu Dhabi, United Arab Emirates.,Department of Public Health and Epidemiology, College of Medicine and Health Sciences, Khalifa University, Abu Dhabi, United Arab Emirates.,Center of Innovation, Technology and Education (CITE) at Anhembi Morumbi University - Anima Institute, São José dos Campos, Brazil
| |
Collapse
|
20
|
Ter Horst R, Dresler M. The Quantified Scientist: Citizen Neuroscience and Neurotechnology. AJOB Neurosci 2021; 13:63-65. [PMID: 34931959 DOI: 10.1080/21507740.2021.2001090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- Rob Ter Horst
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences
| | | |
Collapse
|