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G Ravindran KK, Della Monica C, Atzori G, Lambert D, Hassanin H, Revell V, Dijk DJ. Reliable Contactless Monitoring of Heart Rate, Breathing Rate, and Breathing Disturbance During Sleep in Aging: Digital Health Technology Evaluation Study. JMIR Mhealth Uhealth 2024; 12:e53643. [PMID: 39190477 PMCID: PMC11387924 DOI: 10.2196/53643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 05/13/2024] [Accepted: 06/25/2024] [Indexed: 08/28/2024] Open
Abstract
BACKGROUND Longitudinal monitoring of vital signs provides a method for identifying changes to general health in an individual, particularly in older adults. The nocturnal sleep period provides a convenient opportunity to assess vital signs. Contactless technologies that can be embedded into the bedroom environment are unintrusive and burdenless and have the potential to enable seamless monitoring of vital signs. To realize this potential, these technologies need to be evaluated against gold standard measures and in relevant populations. OBJECTIVE We aimed to evaluate the accuracy of heart rate and breathing rate measurements of 3 contactless technologies (2 undermattress trackers, Withings Sleep Analyzer [WSA] and Emfit QS [Emfit]; and a bedside radar, Somnofy) in a sleep laboratory environment and assess their potential to capture vital signs in a real-world setting. METHODS Data were collected from 35 community-dwelling older adults aged between 65 and 83 (mean 70.8, SD 4.9) years (men: n=21, 60%) during a 1-night clinical polysomnography (PSG) test in a sleep laboratory, preceded by 7 to 14 days of data collection at home. Several of the participants (20/35, 57%) had health conditions, including type 2 diabetes, hypertension, obesity, and arthritis, and 49% (17) had moderate to severe sleep apnea, while 29% (n=10) had periodic leg movement disorder. The undermattress trackers provided estimates of both heart rate and breathing rate, while the bedside radar provided only the breathing rate. The accuracy of the heart rate and breathing rate estimated by the devices was compared with PSG electrocardiogram-derived heart rate (beats per minute) and respiratory inductance plethysmography thorax-derived breathing rate (cycles per minute), respectively. We also evaluated breathing disturbance indexes of snoring and the apnea-hypopnea index, available from the WSA. RESULTS All 3 contactless technologies provided acceptable accuracy in estimating heart rate (mean absolute error <2.12 beats per minute and mean absolute percentage error <5%) and breathing rate (mean absolute error ≤1.6 cycles per minute and mean absolute percentage error <12%) at 1-minute resolution. All 3 contactless technologies were able to capture changes in heart rate and breathing rate across the sleep period. The WSA snoring and breathing disturbance estimates were also accurate compared with PSG estimates (WSA snore: r2=0.76; P<.001; WSA apnea-hypopnea index: r2=0.59; P<.001). CONCLUSIONS Contactless technologies offer an unintrusive alternative to conventional wearable technologies for reliable monitoring of heart rate, breathing rate, and sleep apnea in community-dwelling older adults at scale. They enable the assessment of night-to-night variation in these vital signs, which may allow the identification of acute changes in health, and longitudinal monitoring, which may provide insight into health trajectories. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) RR2-10.3390/clockssleep6010010.
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Affiliation(s)
- Kiran K G Ravindran
- Surrey Sleep Research Centre, Guildford, United Kingdom
- UK Dementia Research Institute, Care Research and Technology Centre at Imperial College, London, United Kingdom, and the University of Surrey, Guildford, London, United Kingdom
| | - Ciro Della Monica
- Surrey Sleep Research Centre, Guildford, United Kingdom
- UK Dementia Research Institute, Care Research and Technology Centre at Imperial College, London, United Kingdom, and the University of Surrey, Guildford, London, United Kingdom
| | - Giuseppe Atzori
- Surrey Sleep Research Centre, Guildford, United Kingdom
- UK Dementia Research Institute, Care Research and Technology Centre at Imperial College, London, United Kingdom, and the University of Surrey, Guildford, London, United Kingdom
| | - Damion Lambert
- Surrey Sleep Research Centre, Guildford, United Kingdom
- UK Dementia Research Institute, Care Research and Technology Centre at Imperial College, London, United Kingdom, and the University of Surrey, Guildford, London, United Kingdom
| | - Hana Hassanin
- UK Dementia Research Institute, Care Research and Technology Centre at Imperial College, London, United Kingdom, and the University of Surrey, Guildford, London, United Kingdom
- Surrey Clinical Research Facility, University of Surrey, Guildford, United Kingdom
- NIHR Royal Surrey Clinical Research Facility, Guildford, United Kingdom
| | - Victoria Revell
- Surrey Sleep Research Centre, Guildford, United Kingdom
- UK Dementia Research Institute, Care Research and Technology Centre at Imperial College, London, United Kingdom, and the University of Surrey, Guildford, London, United Kingdom
| | - Derk-Jan Dijk
- Surrey Sleep Research Centre, Guildford, United Kingdom
- UK Dementia Research Institute, Care Research and Technology Centre at Imperial College, London, United Kingdom, and the University of Surrey, Guildford, London, United Kingdom
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Gaur P, Temple DS, Hegarty-Craver M, Boyce MD, Holt JR, Wenger MF, Preble EA, Eckhoff RP, McCombs MS, Davis-Wilson HC, Walls HJ, Dausch DE. Continuous Monitoring of Heart Rate Variability in Free-Living Conditions Using Wearable Sensors: Exploratory Observational Study. JMIR Form Res 2024; 8:e53977. [PMID: 39110968 PMCID: PMC11339560 DOI: 10.2196/53977] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 05/14/2024] [Accepted: 06/06/2024] [Indexed: 08/25/2024] Open
Abstract
BACKGROUND Wearable physiological monitoring devices are promising tools for remote monitoring and early detection of potential health changes of interest. The widespread adoption of such an approach across communities and over long periods of time will require an automated data platform for collecting, processing, and analyzing relevant health information. OBJECTIVE In this study, we explore prospective monitoring of individual health through an automated data collection, metrics extraction, and health anomaly analysis pipeline in free-living conditions over a continuous monitoring period of several months with a focus on viral respiratory infections, such as influenza or COVID-19. METHODS A total of 59 participants provided smartwatch data and health symptom and illness reports daily over an 8-month window. Physiological and activity data from photoplethysmography sensors, including high-resolution interbeat interval (IBI) and step counts, were uploaded directly from Garmin Fenix 6 smartwatches and processed automatically in the cloud using a stand-alone, open-source analytical engine. Health risk scores were computed based on a deviation in heart rate and heart rate variability metrics from each individual's activity-matched baseline values, and scores exceeding a predefined threshold were checked for corresponding symptoms or illness reports. Conversely, reports of viral respiratory illnesses in health survey responses were also checked for corresponding changes in health risk scores to qualitatively assess the risk score as an indicator of acute respiratory health anomalies. RESULTS The median average percentage of sensor data provided per day indicating smartwatch wear compliance was 70%, and survey responses indicating health reporting compliance was 46%. A total of 29 elevated health risk scores were detected, of which 12 (41%) had concurrent survey data and indicated a health symptom or illness. A total of 21 influenza or COVID-19 illnesses were reported by study participants; 9 (43%) of these reports had concurrent smartwatch data, of which 6 (67%) had an increase in health risk score. CONCLUSIONS We demonstrate a protocol for data collection, extraction of heart rate and heart rate variability metrics, and prospective analysis that is compatible with near real-time health assessment using wearable sensors for continuous monitoring. The modular platform for data collection and analysis allows for a choice of different wearable sensors and algorithms. Here, we demonstrate its implementation in the collection of high-fidelity IBI data from Garmin Fenix 6 smartwatches worn by individuals in free-living conditions, and the prospective, near real-time analysis of the data, culminating in the calculation of health risk scores. To our knowledge, this study demonstrates for the first time the feasibility of measuring high-resolution heart IBI and step count using smartwatches in near real time for respiratory illness detection over a long-term monitoring period in free-living conditions.
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Affiliation(s)
- Pooja Gaur
- Research Triangle Institute, Research Triangle Park, NC, United States
| | - Dorota S Temple
- Research Triangle Institute, Research Triangle Park, NC, United States
| | | | - Matthew D Boyce
- Research Triangle Institute, Research Triangle Park, NC, United States
| | - Jonathan R Holt
- Research Triangle Institute, Research Triangle Park, NC, United States
| | - Michael F Wenger
- Research Triangle Institute, Research Triangle Park, NC, United States
| | - Edward A Preble
- Research Triangle Institute, Research Triangle Park, NC, United States
| | - Randall P Eckhoff
- Research Triangle Institute, Research Triangle Park, NC, United States
| | | | | | - Howard J Walls
- Research Triangle Institute, Research Triangle Park, NC, United States
| | - David E Dausch
- Research Triangle Institute, Research Triangle Park, NC, United States
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Sesma-Sánchez L, Ruiz-Castellano M, Romero-Roldán A, Álvarez-García L, Morrás-Gómez M, Tabar-Liberal I, Pulido-Fontes M, Salmón-García B. Continuous Temperature Telemonitoring of Patients with COVID-19 and Other Infectious Diseases Treated in Hospital-at-Home: Viture ® System Validation. SENSORS (BASEL, SWITZERLAND) 2024; 24:5027. [PMID: 39124073 PMCID: PMC11314737 DOI: 10.3390/s24155027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2024] [Revised: 07/17/2024] [Accepted: 07/20/2024] [Indexed: 08/12/2024]
Abstract
Body temperature must be monitored in patients receiving Hospital-at-Home (HaH) care for COVID-19 and other infectious diseases. Continuous temperature telemonitoring (CTT) detects fever and patient deterioration early, facilitating decision-making. We performed a validation clinical study assessing the safety, comfort, and impact on healthcare practice of Viture®, a CTT system, compared with a standard digital axillary thermometer in 208 patients with COVID-19 and other infectious diseases treated in HaH at the Navarra University Hospital (HUN). Overall, 3258 pairs of measurements showed a clinical bias of -0.02 °C with limits of agreement of -0.96/+0.92 °C, a 95% acceptance rate, and a mean absolute deviation of 0.36 (SD 0.30) °C. Viture® detected 3 times more febrile episodes and revealed fever in 50% more patients compared with spot measurements. Febrile episodes were detected 7.23 h (mean) earlier and modified the diagnostic and/or therapeutic approach in 43.2% of patients. Viture® was validated for use in a clinical setting and was more effective in detecting febrile episodes than conventional methods.
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Affiliation(s)
| | - María Ruiz-Castellano
- Hospital at Home Unit, Navarra University Hospital (HUN), 31008 Pamplona, Navarra, Spain; (M.R.-C.); (L.Á.-G.); (M.M.-G.); (I.T.-L.); (M.P.-F.); (B.S.-G.)
| | | | - Laura Álvarez-García
- Hospital at Home Unit, Navarra University Hospital (HUN), 31008 Pamplona, Navarra, Spain; (M.R.-C.); (L.Á.-G.); (M.M.-G.); (I.T.-L.); (M.P.-F.); (B.S.-G.)
| | - Marta Morrás-Gómez
- Hospital at Home Unit, Navarra University Hospital (HUN), 31008 Pamplona, Navarra, Spain; (M.R.-C.); (L.Á.-G.); (M.M.-G.); (I.T.-L.); (M.P.-F.); (B.S.-G.)
| | - Idoia Tabar-Liberal
- Hospital at Home Unit, Navarra University Hospital (HUN), 31008 Pamplona, Navarra, Spain; (M.R.-C.); (L.Á.-G.); (M.M.-G.); (I.T.-L.); (M.P.-F.); (B.S.-G.)
| | - Marta Pulido-Fontes
- Hospital at Home Unit, Navarra University Hospital (HUN), 31008 Pamplona, Navarra, Spain; (M.R.-C.); (L.Á.-G.); (M.M.-G.); (I.T.-L.); (M.P.-F.); (B.S.-G.)
| | - Belén Salmón-García
- Hospital at Home Unit, Navarra University Hospital (HUN), 31008 Pamplona, Navarra, Spain; (M.R.-C.); (L.Á.-G.); (M.M.-G.); (I.T.-L.); (M.P.-F.); (B.S.-G.)
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Rietz M, Schmidt-Persson J, Gillies Banke Rasmussen M, Overgaard Sørensen S, Rath Mortensen S, Brage S, Lund Kristensen P, Grøntved A, Brønd JC. Facilitating ambulatory heart rate variability analysis using accelerometry-based classifications of body position and self-reported sleep. Physiol Meas 2024; 45:055016. [PMID: 38684167 DOI: 10.1088/1361-6579/ad450d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Accepted: 04/29/2024] [Indexed: 05/02/2024]
Abstract
Objective.This study aimed to examine differences in heart rate variability (HRV) across accelerometer-derived position, self-reported sleep, and different summary measures (sleep, 24 h HRV) in free-living settings using open-source methodology.Approach.HRV is a biomarker of autonomic activity. As it is strongly affected by factors such as physical behaviour, stress, and sleep, ambulatory HRV analysis is challenging. Beat-to-beat heart rate (HR) and accelerometry data were collected using single-lead electrocardiography and trunk- and thigh-worn accelerometers among 160 adults participating in the SCREENS trial. HR files were processed and analysed in the RHRV R package. Start time and duration spent in physical behaviours were extracted, and time and frequency analysis for each episode was performed. Differences in HRV estimates across activities were compared using linear mixed models adjusted for age and sex with subject ID as random effect. Next, repeated-measures Bland-Altman analysis was used to compare 24 h RMSSD estimates to HRV during self-reported sleep. Sensitivity analyses evaluated the accuracy of the methodology, and the approach of employing accelerometer-determined episodes to examine activity-independent HRV was described.Main results.HRV was estimated for 31 289 episodes in 160 individuals (53.1% female) at a mean age of 41.4 years. Significant differences in HR and most markers of HRV were found across positions [Mean differences RMSSD: Sitting (Reference) - Standing (-2.63 ms) or Lying (4.53 ms)]. Moreover, ambulatory HRV differed significantly across sleep status, and poor agreement between 24 h estimates compared to sleep HRV was detected. Sensitivity analyses confirmed that removing the first and last 30 s of accelerometry-determined HR episodes was an accurate strategy to account for orthostatic effects.Significance.Ambulatory HRV differed significantly across accelerometry-assigned positions and sleep. The proposed approach for free-living HRV analysis may be an effective strategy to remove confounding by physical activity when the aim is to monitor general autonomic stress.
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Affiliation(s)
- Marlene Rietz
- Center for Research in Childhood Health, Research Unit for Exercise Epidemiology, Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense M, Denmark
- Division of Clinical Physiology, Department for Laboratory Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Jesper Schmidt-Persson
- Center for Research in Childhood Health, Research Unit for Exercise Epidemiology, Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense M, Denmark
- Applied Research in Child and Adult Health, Department of Midwifery, Physiotherapy, Occupational Therapy, and Psychomotor Therapy, University College Copenhagen, Copenhagen, Denmark
| | - Martin Gillies Banke Rasmussen
- Center for Research in Childhood Health, Research Unit for Exercise Epidemiology, Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense M, Denmark
- Steno Diabetes Center Odense, Odense University Hospital, Odense, Denmark
| | - Sarah Overgaard Sørensen
- Center for Research in Childhood Health, Research Unit for Exercise Epidemiology, Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense M, Denmark
| | - Sofie Rath Mortensen
- Center for Research in Childhood Health, Research Unit for Exercise Epidemiology, Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense M, Denmark
- The Research and Implementation Unit PROgrez, Department of Physiotherapy and Occupational Therapy, Naestved-Slagelse-Ringsted Hospitals, Region Zealand, Denmark
| | - Søren Brage
- Center for Research in Childhood Health, Research Unit for Exercise Epidemiology, Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense M, Denmark
- MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
| | - Peter Lund Kristensen
- Center for Research in Childhood Health, Research Unit for Exercise Epidemiology, Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense M, Denmark
| | - Anders Grøntved
- Center for Research in Childhood Health, Research Unit for Exercise Epidemiology, Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense M, Denmark
| | - Jan Christian Brønd
- Center for Research in Childhood Health, Research Unit for Exercise Epidemiology, Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Odense M, Denmark
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Volpes G, Valenti S, Genova G, Barà C, Parisi A, Faes L, Busacca A, Pernice R. Wearable Ring-Shaped Biomedical Device for Physiological Monitoring through Finger-Based Acquisition of Electrocardiographic, Photoplethysmographic, and Galvanic Skin Response Signals: Design and Preliminary Measurements. BIOSENSORS 2024; 14:205. [PMID: 38667198 PMCID: PMC11048376 DOI: 10.3390/bios14040205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/25/2024] [Revised: 04/12/2024] [Accepted: 04/18/2024] [Indexed: 04/28/2024]
Abstract
Wearable health devices (WHDs) are rapidly gaining ground in the biomedical field due to their ability to monitor the individual physiological state in everyday life scenarios, while providing a comfortable wear experience. This study introduces a novel wearable biomedical device capable of synchronously acquiring electrocardiographic (ECG), photoplethysmographic (PPG), galvanic skin response (GSR) and motion signals. The device has been specifically designed to be worn on a finger, enabling the acquisition of all biosignals directly on the fingertips, offering the significant advantage of being very comfortable and easy to be employed by the users. The simultaneous acquisition of different biosignals allows the extraction of important physiological indices, such as heart rate (HR) and its variability (HRV), pulse arrival time (PAT), GSR level, blood oxygenation level (SpO2), and respiratory rate, as well as motion detection, enabling the assessment of physiological states, together with the detection of potential physical and mental stress conditions. Preliminary measurements have been conducted on healthy subjects using a measurement protocol consisting of resting states (i.e., SUPINE and SIT) alternated with physiological stress conditions (i.e., STAND and WALK). Statistical analyses have been carried out among the distributions of the physiological indices extracted in time, frequency, and information domains, evaluated under different physiological conditions. The results of our analyses demonstrate the capability of the device to detect changes between rest and stress conditions, thereby encouraging its use for assessing individuals' physiological state. Furthermore, the possibility of performing synchronous acquisitions of PPG and ECG signals has allowed us to compare HRV and pulse rate variability (PRV) indices, so as to corroborate the reliability of PRV analysis under stationary physical conditions. Finally, the study confirms the already known limitations of wearable devices during physical activities, suggesting the use of algorithms for motion artifact correction.
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Affiliation(s)
| | | | | | | | | | | | | | - Riccardo Pernice
- Department of Engineering, University of Palermo, Viale delle Scienze, Building 9, 90128 Palermo, Italy; (G.V.); (S.V.); (G.G.); (C.B.); (A.P.); (L.F.); (A.B.)
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Braem CIR, Yavuz US, Hermens HJ, Veltink PH. Missing Data Statistics Provide Causal Insights into Data Loss in Diabetes Health Monitoring by Wearable Sensors. SENSORS (BASEL, SWITZERLAND) 2024; 24:1526. [PMID: 38475061 DOI: 10.3390/s24051526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 02/14/2024] [Accepted: 02/25/2024] [Indexed: 03/14/2024]
Abstract
BACKGROUND Data loss in wearable sensors is an inevitable problem that leads to misrepresentation during diabetes health monitoring. We systematically investigated missing wearable sensors data to get causal insight into the mechanisms leading to missing data. METHODS Two-week-long data from a continuous glucose monitor and a Fitbit activity tracker recording heart rate (HR) and step count in free-living patients with type 2 diabetes mellitus were used. The gap size distribution was fitted with a Planck distribution to test for missing not at random (MNAR) and a difference between distributions was tested with a Chi-squared test. Significant missing data dispersion over time was tested with the Kruskal-Wallis test and Dunn post hoc analysis. RESULTS Data from 77 subjects resulted in 73 cleaned glucose, 70 HR and 68 step count recordings. The glucose gap sizes followed a Planck distribution. HR and step count gap frequency differed significantly (p < 0.001), and the missing data were therefore MNAR. In glucose, more missing data were found in the night (23:00-01:00), and in step count, more at measurement days 6 and 7 (p < 0.001). In both cases, missing data were caused by insufficient frequency of data synchronization. CONCLUSIONS Our novel approach of investigating missing data statistics revealed the mechanisms for missing data in Fitbit and CGM data.
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Affiliation(s)
- Carlijn I R Braem
- Department of Biomedical Signals and Systems, University of Twente, 7522 NB Enschede, The Netherlands
| | - Utku S Yavuz
- Department of Biomedical Signals and Systems, University of Twente, 7522 NB Enschede, The Netherlands
| | - Hermie J Hermens
- Department of Biomedical Signals and Systems, University of Twente, 7522 NB Enschede, The Netherlands
| | - Peter H Veltink
- Department of Biomedical Signals and Systems, University of Twente, 7522 NB Enschede, The Netherlands
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Gerboni G, Comunale G, Chen W, Lever Taylor J, Migliorini M, Picard R, Cruz M, Regalia G. Prospective clinical validation of the Empatica EmbracePlus wristband as a reflective pulse oximeter. Front Digit Health 2023; 5:1258915. [PMID: 38111608 PMCID: PMC10726006 DOI: 10.3389/fdgth.2023.1258915] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 11/14/2023] [Indexed: 12/20/2023] Open
Abstract
Introduction Respiratory diseases such as chronic obstructive pulmonary disease, obstructive sleep apnea syndrome, and COVID-19 may cause a decrease in arterial oxygen saturation (SaO2). The continuous monitoring of oxygen levels may be beneficial for the early detection of hypoxemia and timely intervention. Wearable non-invasive pulse oximetry devices measuring peripheral oxygen saturation (SpO2) have been garnering increasing popularity. However, there is still a strong need for extended and robust clinical validation of such devices, especially to address topical concerns about disparities in performances across racial groups. This prospective clinical validation aimed to assess the accuracy of the reflective pulse oximeter function of the EmbracePlus wristband during a controlled hypoxia study in accordance with the ISO 80601-2-61:2017 standard and the Food & Drug Administration (FDA) guidance. Methods Healthy adult participants were recruited in a controlled desaturation protocol to reproduce mild, moderate, and severe hypoxic conditions with SaO2 ranging from 100% to 70% (ClinicalTrials.gov registration #NCT04964609). The SpO2 level was estimated with an EmbracePlus device placed on the participant's wrist and the reference SaO2 was obtained from blood samples analyzed with a multiwavelength co-oximeter. Results The controlled hypoxia study yielded 373 conclusive measurements on 15 subjects, including 30% of participants with dark skin pigmentation (V-VI on the Fitzpatrick scale). The accuracy root mean square (Arms) error was found to be 2.4%, within the 3.5% limit recommended by the FDA. A strong positive correlation between the wristband SpO2 and the reference SaO2 was observed (r = 0.96, P < 0.001), and a good concordance was found with Bland-Altman analysis (bias, 0.05%; standard deviation, 1.66; lower limit, -4.7%; and upper limit, 4.8%). Moreover, acceptable accuracy was observed when stratifying data points by skin pigmentation (Arms 2.2% in Fitzpatrick V-VI, 2.5% in Fitzpatrick I-IV), and sex (Arms 1.9% in females, and 2.9% in males). Discussion This study demonstrates that the EmbracePlus wristband could be used to assess SpO2 with clinically acceptable accuracy under no-motion and high perfusion conditions for individuals of different ethnicities across the claimed range. This study paves the way for further accuracy evaluations on unhealthy subjects and during prolonged use in ambulatory settings.
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Affiliation(s)
| | | | | | | | | | - Rosalind Picard
- Empatica, Inc., Cambridge, MA, United States
- MIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Marisa Cruz
- Empatica, Inc., Cambridge, MA, United States
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Posthuma LM, Preckel B. Initiatives to detect and prevent death from perioperative deterioration. Curr Opin Anaesthesiol 2023; 36:676-682. [PMID: 37767926 PMCID: PMC10621647 DOI: 10.1097/aco.0000000000001312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/29/2023]
Abstract
PURPOSE OF REVIEW This study indicates that there are differences between hospitals in detection, as well as in adequate management of postsurgical complications, a phenomenon that is described as 'failure-to-rescue'.In this review, recent initiatives to reduce failure-to-rescue in the perioperative period are described. RECENT FINDINGS Use of cognitive aids, emergency manuals, family participation as well as remote monitoring systems are measures to reduce failure-to-rescue situations. Postoperative visit of an anaesthesiologist on the ward was not shown to improve outcome, but there is still room for improvement of postoperative care. SUMMARY Improving the complete emergency chain, including monitoring, recognition and response in the afferent limb, as well as diagnostic and treatment in the efferent limb, should lead to reduced failure-to-rescue situations in the perioperative period.
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Affiliation(s)
- Linda M. Posthuma
- Department of Anesthesiology and Intensive Care Medicine, Amphia Hospital, Breda
| | - Benedikt Preckel
- Department of Anesthesiology, Amsterdam University Medical Centre, location University of Amsterdam
- Amsterdam Public Health Research Institute, Quality of Care, Amsterdam University Medical Centre, Amsterdam, The Netherlands
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van Rossum MC, da Silva PMA, Wang Y, Kouwenhoven EA, Hermens HJ. Missing data imputation techniques for wireless continuous vital signs monitoring. J Clin Monit Comput 2023; 37:1387-1400. [PMID: 36729298 PMCID: PMC9893204 DOI: 10.1007/s10877-023-00975-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Accepted: 01/16/2023] [Indexed: 02/03/2023]
Abstract
Wireless vital signs sensors are increasingly used for remote patient monitoring, but data analysis is often challenged by missing data periods. This study explored the performance of various imputation techniques for continuous vital signs measurements. Wireless vital signs measurements (heart rate, respiratory rate, blood oxygen saturation, axillary temperature) from surgical ward patients were used for repeated random simulation of missing data periods (gaps) of 5-60 min in two-hour windows. Gaps were imputed using linear interpolation, spline interpolation, last observation- and mean carried forwards technique, and cluster-based prognosis. Imputation performance was evaluated using the mean absolute error (MAE) between original and imputed gap samples. Besides, effects on signal features (window's slope, mean) and early warning scores (EWS) were explored. Gaps were simulated in 1743 data windows, obtained from 52 patients. Although MAE ranges overlapped, median MAE was structurally lowest for linear interpolation (heart rate: 0.9-2.6 beats/min, respiratory rate: 0.8-1.8 breaths/min, temperature: 0.04-0.17 °C, oxygen saturation: 0.3-0.7% for 5-60 min gaps) but up to twice as high for other techniques. Three techniques resulted in larger ranges of signal feature bias compared to no imputation. Imputation led to EWS misclassification in 1-8% of all simulations. Imputation error ranges vary between imputation techniques and increase with gap length. Imputation may result in larger signal feature bias compared to performing no imputation, and can affect patient risk assessment as illustrated by the EWS. Accordingly, careful implementation and selection of imputation techniques is warranted.
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Affiliation(s)
- Mathilde C van Rossum
- Biomedical Signals and Systems, University of Twente, Enschede, The Netherlands.
- Cardiovascular and Respiratory Physiology, University of Twente, Postbox 217, 7500 AE, Enschede, The Netherlands.
- Department of Surgery, Hospital Group Twente, Almelo, The Netherlands.
| | - Pedro M Alves da Silva
- Biomedical Signals and Systems, University of Twente, Enschede, The Netherlands
- NOVA School of Science and Technology, NOVA University of Lisbon, Lisbon, Portugal
| | - Ying Wang
- Biomedical Signals and Systems, University of Twente, Enschede, The Netherlands
- ZGT Academy, Hospital group Twente, Almelo, The Netherlands
| | | | - Hermie J Hermens
- Biomedical Signals and Systems, University of Twente, Enschede, The Netherlands
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Lu JK, Sijm M, Janssens GE, Goh J, Maier AB. Remote monitoring technologies for measuring cardiovascular functions in community-dwelling adults: a systematic review. GeroScience 2023; 45:2939-2950. [PMID: 37204639 PMCID: PMC10196312 DOI: 10.1007/s11357-023-00815-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 04/28/2023] [Indexed: 05/20/2023] Open
Abstract
Remote monitoring technologies (RMTs) allow continuous, unobtrusive, and real-time monitoring of the cardiovascular system. An overview of existing RMTs measuring cardiovascular physiological variables is lacking. This systematic review aimed to describe RMTs measuring cardiovascular functions in community-dwelling adults. An electronic search was conducted via PubMed, EMBASE, and Cochrane Library from January 1, 2020, to April 7, 2022. Articles reporting on non-invasive RMTs used unsupervised in community-dwelling adults were included. Reviews and studies in institutionalized populations were excluded. Two reviewers independently assessed the studies and extracted the technologies used, cardiovascular variables measured, and wearing locations of RMTs. Validation of the RMTs was examined based on the COSMIN tool, and accuracy and precision were presented. This systematic review was registered with PROSPERO (CRD42022320082). A total of 272 articles were included representing 322,886 individuals with a mean or median age from 19.0 to 88.9 years (48.7% female). Of all 335 reported RMTs containing 216 distinct devices, photoplethysmography was used in 50.3% of RMTs. Heart rate was measured in 47.0% of measurements, and the RMT was worn on the wrist in 41.8% of devices. Nine devices were reported in more than three articles, of which all were sufficiently accurate, six were sufficiently precise, and four were commercially available in December 2022. The top four most reported technologies were AliveCor KardiaMobile®, Fitbit Charge 2, and Polar H7 and H10 Heart Rate Sensors. With over 200 distinct RMTs reported, this review provides healthcare professionals and researchers an overview of available RMTs for monitoring the cardiovascular system.
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Affiliation(s)
- Jessica K Lu
- Centre for Healthy Longevity, National University Health System, Singapore, Singapore
- Healthy Longevity Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | | | - Georges E Janssens
- Laboratory Genetic Metabolic Diseases, Amsterdam University Medical Centers - location Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Jorming Goh
- Centre for Healthy Longevity, National University Health System, Singapore, Singapore
- Healthy Longevity Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Andrea B Maier
- Centre for Healthy Longevity, National University Health System, Singapore, Singapore.
- Healthy Longevity Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
- Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam Movement Sciences, Van der Boechorstsraat 7, 1081 BT, Amsterdam, The Netherlands.
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11
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van Rossum MC, Bekhuis REM, Wang Y, Hegeman JH, Folbert EC, Vollenbroek-Hutten MMR, Kalkman CJ, Kouwenhoven EA, Hermens HJ. Early Warning Scores to Support Continuous Wireless Vital Sign Monitoring for Complication Prediction in Patients on Surgical Wards: Retrospective Observational Study. JMIR Perioper Med 2023; 6:e44483. [PMID: 37647104 PMCID: PMC10500362 DOI: 10.2196/44483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Revised: 06/16/2023] [Accepted: 07/07/2023] [Indexed: 09/01/2023] Open
Abstract
BACKGROUND Wireless vital sign sensors are increasingly being used to monitor patients on surgical wards. Although early warning scores (EWSs) are the current standard for the identification of patient deterioration in a ward setting, their usefulness for continuous monitoring is unknown. OBJECTIVE This study aimed to explore the usability and predictive value of high-rate EWSs obtained from continuous vital sign recordings for early identification of postoperative complications and compares the performance of a sensor-based EWS alarm system with manual intermittent EWS measurements and threshold alarms applied to individual vital sign recordings (single-parameter alarms). METHODS Continuous vital sign measurements (heart rate, respiratory rate, blood oxygen saturation, and axillary temperature) collected with wireless sensors in patients on surgical wards were used for retrospective simulation of EWSs (sensor EWSs) for different time windows (1-240 min), adopting criteria similar to EWSs based on manual vital signs measurements (nurse EWSs). Hourly sensor EWS measurements were compared between patients with (event group: 14/46, 30%) and without (control group: 32/46, 70%) postoperative complications. In addition, alarms were simulated for the sensor EWSs using a range of alarm thresholds (1-9) and compared with alarms based on nurse EWSs and single-parameter alarms. Alarm performance was evaluated using the sensitivity to predict complications within 24 hours, daily alarm rate, and false discovery rate (FDR). RESULTS The hourly sensor EWSs of the event group (median 3.4, IQR 3.1-4.1) was significantly higher (P<.004) compared with the control group (median 2.8, IQR 2.4-3.2). The alarm sensitivity of the hourly sensor EWSs was the highest (80%-67%) for thresholds of 3 to 5, which was associated with alarm rates of 2 (FDR=85%) to 1.2 (FDR=83%) alarms per patient per day respectively. The sensitivity of sensor EWS-based alarms was higher than that of nurse EWS-based alarms (maximum=40%) but lower than that of single-parameter alarms (87%) for all thresholds. In contrast, the (false) alarm rates of sensor EWS-based alarms were higher than that of nurse EWS-based alarms (maximum=0.6 alarm/patient/d; FDR=80%) but lower than that of single-parameter alarms (2 alarms/patient/d; FDR=84%) for most thresholds. Alarm rates for sensor EWSs increased for shorter time windows, reaching 70 alarms per patient per day when calculated every minute. CONCLUSIONS EWSs obtained using wireless vital sign sensors may contribute to the early recognition of postoperative complications in a ward setting, with higher alarm sensitivity compared with manual EWS measurements. Although hourly sensor EWSs provide fewer alarms compared with single-parameter alarms, high false alarm rates can be expected when calculated over shorter time spans. Further studies are recommended to optimize care escalation criteria for continuous monitoring of vital signs in a ward setting and to evaluate the effects on patient outcomes.
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Affiliation(s)
- Mathilde C van Rossum
- Department of Biomedical Signals and Systems, University of Twente, Enschede, Netherlands
- Department of Cardiovascular and Respiratory Physiology, University of Twente, Enschede, Netherlands
| | - Robin E M Bekhuis
- Department of Surgery, Hospital Group Twente, Almelo, Netherlands
- Hospital Group Twente Academy, Hospital Group Twente, Almelo, Netherlands
| | - Ying Wang
- Department of Biomedical Signals and Systems, University of Twente, Enschede, Netherlands
- Hospital Group Twente Academy, Hospital Group Twente, Almelo, Netherlands
| | | | - Ellis C Folbert
- Department of Surgery, Hospital Group Twente, Almelo, Netherlands
| | | | - Cornelis J Kalkman
- Department of Anesthesiology, University Medical Center Utrecht, Utrecht, Netherlands
| | | | - Hermie J Hermens
- Department of Biomedical Signals and Systems, University of Twente, Enschede, Netherlands
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12
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van Melzen R, Haveman ME, Schuurmann RCL, Struys MMRF, de Vries JPPM. Implementing Wearable Sensors for Clinical Application at a Surgical Ward: Points to Consider before Starting. SENSORS (BASEL, SWITZERLAND) 2023; 23:6736. [PMID: 37571519 PMCID: PMC10422413 DOI: 10.3390/s23156736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 07/25/2023] [Accepted: 07/26/2023] [Indexed: 08/13/2023]
Abstract
Incorporating technology into healthcare processes is necessary to ensure the availability of high-quality care in the future. Wearable sensors are an example of such technology that could decrease workload, enable early detection of patient deterioration, and support clinical decision making by healthcare professionals. These sensors unlock continuous monitoring of vital signs, such as heart rate, respiration rate, blood oxygen saturation, temperature, and physical activity. However, broad and successful application of wearable sensors on the surgical ward is currently lacking. This may be related to the complexity, especially when it comes to replacing manual measurements by healthcare professionals. This report provides practical guidance to support peers before starting with the clinical application of wearable sensors in the surgical ward. For this purpose, the Non-Adoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) framework of technology adoption and innovations in healthcare organizations is used, combining existing literature and our own experience in this field over the past years. Specifically, the relevant topics are discussed per domain, and key lessons are subsequently summarized.
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Affiliation(s)
- Rianne van Melzen
- Division of Vascular Surgery, Department of Surgery, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands; (R.C.L.S.); (J.-P.P.M.d.V.)
| | - Marjolein E. Haveman
- Department of Anesthesiology, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands; (M.E.H.); (M.M.R.F.S.)
| | - Richte C. L. Schuurmann
- Division of Vascular Surgery, Department of Surgery, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands; (R.C.L.S.); (J.-P.P.M.d.V.)
| | - Michel M. R. F. Struys
- Department of Anesthesiology, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands; (M.E.H.); (M.M.R.F.S.)
| | - Jean-Paul P. M. de Vries
- Division of Vascular Surgery, Department of Surgery, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands; (R.C.L.S.); (J.-P.P.M.d.V.)
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13
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van der Stam JA, Mestrom EHJ, Scheerhoorn J, Jacobs FENB, Nienhuijs S, Boer AK, van Riel NAW, de Morree HM, Bonomi AG, Scharnhorst V, Bouwman RA. The Accuracy of Wrist-Worn Photoplethysmogram-Measured Heart and Respiratory Rates in Abdominal Surgery Patients: Observational Prospective Clinical Validation Study. JMIR Perioper Med 2023; 6:e40474. [PMID: 36804173 PMCID: PMC9989911 DOI: 10.2196/40474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 01/12/2023] [Accepted: 01/31/2023] [Indexed: 02/22/2023] Open
Abstract
BACKGROUND Postoperative deterioration is often preceded by abnormal vital parameters. Therefore, vital parameters of postoperative patients are routinely measured by nursing staff. Wrist-worn sensors could potentially provide an alternative tool for the measurement of vital parameters in low-acuity settings. These devices would allow more frequent or even continuous measurements of vital parameters without relying on time-consuming manual measurements, provided their accuracy in this clinical population is established. OBJECTIVE This study aimed to assess the accuracy of heart rate (HR) and respiratory rate (RR) measures obtained via a wearable photoplethysmography (PPG) wristband in a cohort of postoperative patients. METHODS The accuracy of the wrist-worn PPG sensor was assessed in 62 post-abdominal surgery patients (mean age 55, SD 15 years; median BMI 34, IQR 25-40 kg/m2). The wearable obtained HR and RR measurements were compared to those of the reference monitor in the postanesthesia or intensive care unit. Bland-Altman and Clarke error grid analyses were performed to determine agreement and clinical accuracy. RESULTS Data were collected for a median of 1.2 hours per patient. With a coverage of 94% for HR and 34% for RR, the device was able to provide accurate measurements for the large majority of the measurements as 98% and 93% of the measurements were within 5 bpm or 3 rpm of the reference signal. Additionally, 100% of the HR and 98% of the RR measurements were clinically acceptable on Clarke error grid analysis. CONCLUSIONS The wrist-worn PPG device is able to provide measurements of HR and RR that can be seen as sufficiently accurate for clinical applications. Considering the coverage, the device was able to continuously monitor HR and report RR when measurements of sufficient quality were obtained. TRIAL REGISTRATION ClinicalTrials.gov NCT03923127; https://www.clinicaltrials.gov/ct2/show/NCT03923127.
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Affiliation(s)
- Jonna A van der Stam
- Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands.,Clinical Laboratory, Catharina Hospital, Eindhoven, Netherlands.,Expert Center Clinical Chemistry Eindhoven, Eindhoven, Netherlands
| | - Eveline H J Mestrom
- Department of Anesthesiology, Intensive Care & Pain Medicine, Catharina Hospital, Eindhoven, Netherlands
| | - Jai Scheerhoorn
- Department of Surgery, Catharina Hospital, Eindhoven, Netherlands
| | - Fleur E N B Jacobs
- Department of Medical Physics, Catharina Hospital, Eindhoven, Netherlands
| | - Simon Nienhuijs
- Department of Surgery, Catharina Hospital, Eindhoven, Netherlands
| | - Arjen-Kars Boer
- Clinical Laboratory, Catharina Hospital, Eindhoven, Netherlands.,Expert Center Clinical Chemistry Eindhoven, Eindhoven, Netherlands
| | - Natal A W van Riel
- Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands.,Expert Center Clinical Chemistry Eindhoven, Eindhoven, Netherlands.,Department of Vascular Medicine, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Helma M de Morree
- Patient Care & Monitoring Department, Philips Research, Eindhoven, Netherlands
| | - Alberto G Bonomi
- Patient Care & Monitoring Department, Philips Research, Eindhoven, Netherlands
| | - Volkher Scharnhorst
- Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands.,Clinical Laboratory, Catharina Hospital, Eindhoven, Netherlands.,Expert Center Clinical Chemistry Eindhoven, Eindhoven, Netherlands
| | - R Arthur Bouwman
- Department of Anesthesiology, Intensive Care & Pain Medicine, Catharina Hospital, Eindhoven, Netherlands.,Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands
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14
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Haveman ME, van Melzen R, El Moumni M, Schuurmann RCL, Hermens HJ, Tabak M, de Vries JPPM. Determining the Reliable Measurement Period for Preoperative Baseline Values With Telemonitoring Before Major Abdominal Surgery: Pilot Cohort Study. JMIR Perioper Med 2022; 5:e40815. [PMID: 36441586 DOI: 10.2196/40815] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 10/07/2022] [Accepted: 10/29/2022] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Preoperative telemonitoring of vital signs, physical activity, and well-being might be able to optimize prehabilitation of the patient's physical and mental condition prior to surgery, support setting alarms during in-hospital monitoring, and allow personalization of the postoperative recovery process. OBJECTIVE The primary aim of this study was to evaluate when and how long patients awaiting major abdominal surgery should be monitored to get reliable preoperative individual baseline values of heart rate (HR), daily step count, and patient-reported outcome measures (PROMs). The secondary aim was to describe the perioperative course of these measurements at home. METHODS In this observational single-center cohort study, patients used a wearable sensor during waking hours and reported PROMs (pain, anxiety, fatigue, nausea) on a tablet twice a day. Intraclass correlation coefficients (ICCs) were used to evaluate the reliability of mean values on 2 specific preoperative days (the first day of telemonitoring and the day before hospital admission) and randomly selected preoperative periods compared to individual reference values. Mean values of HR, step count, and PROMs per day were visualized in a boxplot from 14 days before hospital admission until 30 days after surgery. RESULTS A total of 16 patients were included in the data analyses. The ICCs of mean values on the first day of telemonitoring were 0.91 for HR, 0.71 for steps, and at least 0.86 for PROMs. The day before hospital admission showed reliability coefficients of 0.76 for HR, 0.71 for steps, and 0.92-0.99 for PROMs. ICC values of randomly selected measurement periods increased over the continuous period of time from 0.68 to 0.99 for HR and daily step counts. A lower bound of the 95% CI of at least 0.75 was determined after 3 days of measurements. The ICCs of randomly selected PROM measurements were 0.89-0.94. Visualization of mean values per day mainly showed variable preoperative daily step counts (median 2409, IQR 1735-4661 steps/day) and lower postoperative daily step counts (median 884, IQR 474-1605 steps/day). In addition, pain was visually reduced until 30 days after surgery at home. CONCLUSIONS In this prospective pilot study, for patients awaiting major abdominal surgery, baseline values for HR and daily step count could be measured reliably by a wearable sensor worn for at least 3 consecutive days and PROMs during any preoperative day. No clear conclusions were drawn from the description of the perioperative course by showing mean values of HR, daily step count, and PROM values over time in the home situation.
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Affiliation(s)
- Marjolein E Haveman
- Department of Surgery, Division of Vascular Surgery, University Medical Center Groningen, University of Groningen, Groningen, Netherlands.,Department of Anesthesiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Rianne van Melzen
- Department of Surgery, Division of Vascular Surgery, University Medical Center Groningen, University of Groningen, Groningen, Netherlands.,Department of Surgery, Division of Trauma Surgery, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Mostafa El Moumni
- Department of Surgery, Division of Trauma Surgery, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Richte C L Schuurmann
- Department of Surgery, Division of Vascular Surgery, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Hermie J Hermens
- Department of Biomedical Signals and Systems, University of Twente, Enschede, Netherlands
| | - Monique Tabak
- Department of Biomedical Signals and Systems, University of Twente, Enschede, Netherlands.,eHealth group, Roessingh Research and Development, Enschede, Netherlands
| | - Jean-Paul P M de Vries
- Department of Surgery, Division of Vascular Surgery, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
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15
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Yang M, Liu S, Zhang C. The Related Metabolic Diseases and Treatments of Obesity. Healthcare (Basel) 2022; 10:1616. [PMID: 36141228 PMCID: PMC9498506 DOI: 10.3390/healthcare10091616] [Citation(s) in RCA: 39] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 08/19/2022] [Accepted: 08/23/2022] [Indexed: 11/17/2022] Open
Abstract
Obesity is a chronic disease characterized by the abnormal or excessive accumulation of body fat, affecting more than 1 billion people worldwide. Obesity is commonly associated with other metabolic disorders, such as type 2 diabetes, non-alcoholic fatty liver disease, cardiovascular diseases, chronic kidney disease, and cancers. Factors such as a sedentary lifestyle, overnutrition, socioeconomic status, and other environmental and genetic conditions can cause obesity. Many molecules and signaling pathways are involved in the pathogenesis of obesity, such as nuclear factor (NF)-κB, Toll-like receptors (TLRs), adhesion molecules, G protein-coupled receptors (GPCRs), programmed cell death 1 (PD-1)/programmed death-ligand 1 (PD-L1), and sirtuin 1 (SIRT1). Commonly used strategies of obesity management and treatment include exercise and dietary change or restriction for the early stage of obesity, bariatric surgery for server obesity, and Food and Drug Administration (FDA)-approved medicines such as semaglutide and liraglutide that can be used as monotherapy or as a synergistic treatment. In addition, psychological management, especially for patients with obesity and distress, is a good option. Gut microbiota plays an important role in obesity and its comorbidities, and gut microbial reprogramming by fecal microbiota transplantation (FMT), probiotics, prebiotics, or synbiotics shows promising potential in obesity and metabolic syndrome. Many clinical trials are ongoing to evaluate the therapeutic effects of different treatments. Currently, prevention and early treatment of obesity are the best options to prevent its progression to many comorbidities.
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Affiliation(s)
- Ming Yang
- Department of Surgery, University of Missouri, Columbia, MO 65212, USA
| | - Shuai Liu
- The First Affiliated Hospital, Zhejiang University, Hangzhou 310006, China
| | - Chunye Zhang
- Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO 65212, USA
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16
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Haveman ME, van Melzen R, Schuurmann RCL, Hermens HJ, Tabak M, de Vries JPPM. Feasibility and patient's experiences of perioperative telemonitoring in major abdominal surgery: an observational pilot study. Expert Rev Med Devices 2022; 19:515-523. [PMID: 35975601 DOI: 10.1080/17434440.2022.2108703] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
BACKGROUND Telemonitoring during the perioperative trajectory may improve patient outcomes and self-management. The aim of this study is to assess the feasibility of and patient's experiences with telemonitoring before and after major abdominal surgery to inform future study design. METHODS Patients planned for elective major abdominal surgery wore a sensor and answered well-being questions on a tablet daily for at least 2 weeks preoperatively up to 30-days postoperatively. Feasibility was assessed by participation and completion rate, compliance per day, weekly satisfaction scores, and reasons for nonscheduled contact. RESULTS Twenty-three patients were included (participation rate of 54.5%) with a completion rate of 69.6%. Median compliance with the wearable sensor and well-being questions was respectively: 94.7% and 83.3% preoperatively at home; 100% and 66.7% postoperatively in-hospital; and 95.4% and 85.8% postoperatively at home. Median weekly satisfaction scores for both wearing the sensor and well-being questions were 5 (IQR, 4-5). Contact moments were related to absence of sensor data and technological issues (76.0%) or patient discomfort and insecurity (24.0%). CONCLUSIONS In this study, telemonitoring showed high satisfaction and compliance during the perioperative trajectory. Future trial design regarding the effectiveness of telemonitoring requires embedding in clinical practice and support for patients, relatives, and healthcare personnel.
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Affiliation(s)
- Marjolein E Haveman
- Department of Surgery, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.,Department of Anesthesiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Rianne van Melzen
- Department of Surgery, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Richte C L Schuurmann
- Department of Surgery, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Hermie J Hermens
- Department of Biomedical Signals and Systems, University of Twente, Enschede, The Netherlands.,eHealth Group, Roessingh Research and Development, Enschede, The Netherlands
| | - Monique Tabak
- Department of Biomedical Signals and Systems, University of Twente, Enschede, The Netherlands.,eHealth Group, Roessingh Research and Development, Enschede, The Netherlands
| | - Jean-Paul P M de Vries
- Department of Surgery, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
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17
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Wearable Sensors for Vital Signs Measurement: A Survey. JOURNAL OF SENSOR AND ACTUATOR NETWORKS 2022. [DOI: 10.3390/jsan11010019] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
With the outbreak of coronavirus disease-2019 (COVID-19) worldwide, developments in the medical field have aroused concerns within society. As science and technology develop, wearable medical sensors have become the main means of medical data acquisition. To analyze the intelligent development status of wearable medical sensors, the current work classifies and prospects the application status and functions of wireless communication wearable medical sensors, based on human physiological data acquisition in the medical field. By understanding its working principles, data acquisition modes and action modes, the work chiefly analyzes the application of wearable medical sensors in vascular infarction, respiratory intensity, body temperature, blood oxygen concentration, and sleep detection, and reflects the key role of wearable medical sensors in human physiological data acquisition. Further exploration and prospecting are made by investigating the improvement of information security performance of wearable medical sensors, the improvement of biological adaptability and biodegradability of new materials, and the integration of wearable medical sensors and intelligence-assisted rehabilitation. The research expects to provide a reference for the intelligent development of wearable medical sensors and real-time monitoring of human health in the follow-up medical field.
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