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Cited by 670Non-Invasive Vital Sign MonitoringContext-Aware Activity Recognition SystemsWireless Body Area Networks

Wearables and the Medical Revolution

Open access
Dunn, Jessilyn, Runge, Ryan, Snyder, Michael·2018·Personalized Medicine
DOI 10.2217/pme-2018-0044PMC PMC12294383
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Abstract

Wearable sensors are already impacting healthcare and medicine by enabling health monitoring outside of the clinic and prediction of health events. This paper reviews current and prospective wearable technologies and their progress toward clinical application. We describe technologies underlying common, commercially available wearable sensors and early-stage devices and outline research, when available, to support the use of these devices in healthcare. We cover applications in the following health areas: metabolic, cardiovascular and gastrointestinal monitoring; sleep, neurology, movement disorders and mental health; maternal, pre- and neo-natal care; and pulmonary health and environmental exposures. Finally, we discuss challenges associated with the adoption of wearable sensors in the current healthcare ecosystem and discuss areas for future research and development.

AI snapshot

Written from the paper’s full text.

TL;DR

This review surveys wearable sensors for healthcare, covering mechanical, physiological, and biochemical devices and applications from hospital monitoring to chronic disease, maternal, pulmonary, and mental health. It argues wearables can enable continuous longitudinal monitoring and prediction but require validation, standards, integration, and regulatory clarity before broad clinical adoption.

Key findings

  • Wearables span mechanical, physiological, and biochemical sensors, with applications including glucose monitoring, arrhythmia detection, sleep, maternal/fetal care, pulmonary health, and environmental exposures.
  • In a partnership with the UCSF Health eHeart study, Cardiogram’s DeepHeart platform used data from 14,011 wearable-equipped participants and detected Type II diabetes at 85% accuracy, atrial fibrillation at 97%, sleep apnea at 90%, and hypertension at 82%. A trial comparing AliveCor’s technology with routine care (n = 1001) resulted in a nearly fourfold increase in atrial fibrillation diagnosis.
  • Other reported performance examples include Fitbit Charge post-ICU tachycardia detection with 69.5% sensitivity and 98.8% specificity (n = 50); Oura ring sleep detection with 96% sensitivity, 48% wake specificity, and 65/51/61% agreement for light/deep/REM sleep; Empatica Embrace detecting 94% of GTC seizures in 80 pediatric patients with less than one false alarm per 24 h; ADAMM asthma detection accuracy of 71% in 84 teens; and VitalConnect HealthPatch fall detection with 99% sensitivity and 100% specificity (n = 25).
  • The global wearable devices market was anticipated to reach $19.5 billion in 2021; replacing one in five outpatient consultations and home health visits with digital visits was estimated to save $40 billion a year, and remote monitoring in patients with implantable cardiovascular devices (n = 43) decreased healthcare costs by 25%.

Methods

  • Narrative review of current and prospective wearable technologies and their progress toward clinical application, organized by health areas: metabolic, cardiovascular, and gastrointestinal monitoring; sleep, neurology, movement disorders, and mental health; maternal, pre- and neo-natal care; and pulmonary health and environmental exposures.
  • No primary data collection; the paper synthesizes published studies, commercially available devices, early-stage devices, and examples from the literature.
  • No systematic search strategy, inclusion criteria, or meta-analysis is stated; the review also discusses regulatory oversight, economic impact, challenges, and future directions.

Limitations

  • The paper states limitations including high device cost, cross-platform incompatibility, lack of data standards, setup and charging burden, variable acceptability and stigma, need for large clinical and field trials, unsubstantiated commercial claims, false negatives and false positives, inaccurate activity tracking, need for clinician training, and potential emotional burden or technology addiction.
  • Evident from the text: as a narrative review, it lacks a systematic search or formal quality appraisal, and many cited studies are small, early-stage, feasibility, pilot, or not yet peer-reviewed; several device examples are commercial or under development.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.2217/pme-2018-0044

Cites

156 of 156 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 120 cited sources checked · 0 supported · 0 flagged

  • Findingcitation

    Algorithms have been developed to automatically process and interpret wearables data to present evidence-based health insights such as detection of inflammation or prediction of cardiometabolic health based on activity habits.

    “To address this data deluge, we and others have recently developed algorithms to automatically process and interpret wearables data in order to present evidence-based health insights such as detection of inflammation or prediction of cardiometabolic health based on activity habits [40-43].”
    Quote in the paperSubstantial claim0 of 4 sources checked
    • cites [40] Li X, Dunn J, Salins D Digital health: tracking physiomes and activity using wearable biosensors reveals useful health-related information. PLoS Biol. 15(1), e2001402 (2017). 28081144 PMC5230763 •• The first deep phenotyping study that used wearable sensing to detect health events. source

      Not checked in the free run.

    • cites [41] Ballinger B, Hsieh J, Singh A DeepHeart: semi-supervised sequence learning for cardiovascular risk prediction. arXiv (2018). https://arxiv.org/abs/1802.02511

      Not checked in the free run.

    • cites [42] Lim WK, Davila S, Teo JX Beyond fitness tracking: The use of consumer-grade wearable data from normal volunteers in cardiovascular and lipidomics research. PLoS Biol. 16(2), e2004285 (2018). 29485983 PMC5828350 source

      Not checked in the free run.

    • cites [43] Price ND, Magis AT, Earls JC A wellness study of 108 individuals using personal, dense, dynamic data clouds. Nat. Biotechnol 35(8), 747– 756 (2017). 28714965 PMC5568837 source

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  • Findingcitation

    A semi-supervised method reduces the amount of labeled wearables data needed for training digital biomarker models by tenfold.

    “A semi-supervised method that reduces the amount of labeled wearables data needed for training digital biomarker models by tenfold was developed to address this challenge.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [41] Ballinger B, Hsieh J, Singh A DeepHeart: semi-supervised sequence learning for cardiovascular risk prediction. arXiv (2018). https://arxiv.org/abs/1802.02511

      Not checked in the free run.

  • Findingcitation

    Wearables have been successful in detecting obstructive sleep apnea with personalized machine learning algorithms based on similarity to other OSA patients, with detection accuracies between 90 and 93.6%.

    “Wearables have been successful in detecting OSA in a variety of ways, including with personalized machine learning algorithms based on similarity to other OSA patients (detection accuracies between 90 and 93.6%) [41,87].”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [41] Ballinger B, Hsieh J, Singh A DeepHeart: semi-supervised sequence learning for cardiovascular risk prediction. arXiv (2018). https://arxiv.org/abs/1802.02511

      Not checked in the free run.

    • cites [87] Wu H-T, Wu J-C, Huang P-C Phenotype-based and self-learning inter-individual sleep Apnea screening with a level IV monitoring system. arXiv (2018). https://arxiv.org/abs/1802.09706 PMC6036126 30013479

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  • Findingcitation

    In a recent feasibility study, Fitbit Charge monitoring of post-ICU convalescence in 50 stable ICU patients over 24 h had tachycardia detection sensitivity 69.5% and specificity 98.8%.

    “Tachycardia detection had 69.5% sensitivity and 98.8% specificity [22].”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [22] Kroll RR, Mckenzie ED, Boyd JG Use of wearable devices for post-discharge monitoring of ICU patients: a feasibility study. J. Intensive Care 5, 64 (2017). 29201377 PMC5698959 source

      Not checked in the free run.

  • Findingreasoning

    Some digital biomarkers have been found to outperform traditional clinical methods, for example, for arrhythmia detection, because of their ability to continuously monitor patients outside of the clinic.

    “Some digital biomarkers have been found to outperform traditional clinical methods, for example, for arrhythmia detection, because of their ability to continuously monitor patients outside of the clinic.”
    Quote in the paperNot a substantial claim
  • Classified as probably not a substantial claim. 31
  • May combine two claims. 42

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Findingnone given

    Wearables most commonly related to clinical applications include biochemical sensors.

    “Wearables that are most commonly related to clinical applications include biochemical sensors.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Findingnone given

    The first continuous glucose monitor for retrospective patient analysis (MiniMed) earned FDA approval in 1999.

    “The first continuous glucose monitor (CGM) for retrospective patient analysis (MiniMed) earned FDA approval in 1999.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingcitation

    The Oura ring compared with polysomnography had 96% sensitivity to detect sleep, and agreement of 65, 51 and 61% in detecting light sleep, deep sleep and REM sleep, respectively.

    “The Oura ring (FIN) compared with polysomnography had a 96% sensitivity to detect sleep, and agreement of 65, 51 and 61%, in detecting ‘light sleep’, ‘deep sleep’ and REM sleep, respectively.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [35] De Zambotti M, Rosas L, Colrain IM, Baker FC. The sleep of the ring: comparison of the OURA sleep tracker against polysomnography. Behav. Sleep Med doi: 10.1080/15402002.2017.1300587 (2017) (Epub ahead of print). PMC6095823 28323455

      Not checked in the free run.

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    Findingcitation

    The leading CGMs on market today are Dexcom, Medtronic and Abbott devices.

    “The leading CGMs on market today are Dexcom (CA, USA), Medtronic (MN, USA) and Abbott (IL, USA) devices [2-5,19,31].”
    Quote in the paperNot a substantial claim0 of 6 sources checked
    • cites [2] Boscari F, Galasso S, Acciaroli G Head-to-head comparison of the accuracy of Abbott FreeStyle Libre and Dexcom G5 mobile. Nutr. Metab. Cardiovasc. Dis 28(4), 425– 427 (2018). 29502924

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    • cites [3] Thompson H, Lunt H, Fleckney C, Soule S. Insulin degludec overdose in an adolescent with Type 1 diabetes: proactive management including monitoring using the Freestyle Libre flash glucose monitoring system. Endocrinol. Diabetes Metab. Case Rep doi: 10.1530/EDM-18-0044 (2018) (Epub ahead of print). PMC5987182 29887987

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    • cites [4] Massa GG, Gys I, Op ‘t Eyndt A Evaluation of the FreeStyle® Libre Flash Glucose Monitoring System in children and adolescents with Type 1 diabetes. Horm. Res. Paediatr 89(3), 189– 199 (2018). 29587254

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    • cites [5] Matuleviciene V, Joseph JI, Andelin M A clinical trial of the accuracy and treatment experience of the Dexcom G4 sensor (Dexcom G4 system) and Enlite sensor (guardian REAL-time system) tested simultaneously in ambulatory patients with Type 1 diabetes. Diabetes Technol. Ther 16(11), 759– 767 (2014). 25233297 PMC4201312

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    • cites [19] Heinemann L, Freckmann G, Ehrmann D Real-time continuous glucose monitoring in adults with Type 1 diabetes and impaired hypoglycaemia awareness or severe hypoglycaemia treated with multiple daily insulin injections (HypoDE): a multicentre, randomised controlled trial. Lancet 391(10128), 1367– 1377 (2018). 29459019 source

      Not checked in the free run.

    • cites [31] Sinha M, Mckeon KM, Parker S A comparison of time delay in three continuous glucose monitors for adolescents and adults. J. Diabetes Sci. Technol 11(6), 1132– 1137 (2017). 28459159 PMC5951038

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  • May combine two claims.

    Findingcitation

    VitalConnect has built successful sleep apnea and fall detection algorithms using respiratory rate and accelerometry.

    “VitalConnect (CA, USA) has also built successful sleep apnea and fall detection algorithms using respiratory rate and accelerometry [48-51].”
    Quote in the paperNot a substantial claim0 of 4 sources checked
    • cites [48] Selvaraj N, Narasimhan R. Detection of sleep apnea on a per-second basis using respiratory signals. Presented at: Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE. Osaka, Japan, (3-7 July 2013). 24110140

      Not checked in the free run.

    • cites [49] Selvaraj N, Narasimhan R. Automated prediction of the apnea-hypopnea index using a wireless patch sensor. Presented at: Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE. IL, USA (26-30 August 2014). 25570349

      Not checked in the free run.

    • cites [50] Narasimhan R. Skin-contact sensor for automatic fall detection. Presented at: Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE. CA, USA (28 August-1 September 2012). 23366814

      Not checked in the free run.

    • cites [51] Chan AM, Selvaraj N, Ferdosi N, Narasimhan R. Wireless patch sensor for remote monitoring of heart rate, respiration, activity, and falls. Presented at: Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE. Osaka, Japan, (3-7 July 2013). 24111135

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingnone given

    Data from wearable sensors have been used for tracking gait, detecting atrial fibrillation and monitoring blood glucose.

    “Data from these sensors have been used in a wide range of tasks, including, for example, tracking gait, detecting atrial fibrillation and monitoring blood glucose, respectively.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Findingnone given

    Wearable pressure sensors have become increasingly common to track forces exerted on or by the body.

    “Wearable pressure sensors have also become increasingly common to track forces either exerted on or by the body.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingcitation

    The Cardiogram DeepHeart team has demonstrated early success in detecting Type II diabetes (85% accuracy), atrial fibrillation (97% accuracy), sleep apnea (90% accuracy), hypertension (82% accuracy) and cardiovascular risk using wearables data.

    “This team has demonstrated early success in detecting Type II diabetes (85% accuracy), atrial fibrillation (97% accuracy), sleep apnea (90% accuracy), hypertension (82% accuracy) and more recently, cardiovascular risk using the DeepHeart platform [42,48].”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [42] Lim WK, Davila S, Teo JX Beyond fitness tracking: The use of consumer-grade wearable data from normal volunteers in cardiovascular and lipidomics research. PLoS Biol. 16(2), e2004285 (2018). 29485983 PMC5828350

      Not checked in the free run.

    • cites [48] Selvaraj N, Narasimhan R. Detection of sleep apnea on a per-second basis using respiratory signals. Presented at: Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE. Osaka, Japan, (3-7 July 2013). 24110140

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Findingnone given

    At this time, most integration/interoperability apps aggregate data from hundreds of different wearables with their partnered electronic health record systems.

    “At this time, most integration/interoperability apps aggregate data from hundreds of different wearables with their partnered electronic health record systems.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Findingnone given

    Technological limitations include noisy heart rate during periods of high intensity activity.

    “Technological limitations include noisy heart rate during periods of high intensity activity.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingcitation

    An early-stage ingestible sensor is being explored to diagnose gastrointestinal slowdown or monitor food intake via gastrointestinal movement.

    “An early-stage ingestible sensor is being explored to diagnose gastrointestinal slowdown or monitor food intake via gastrointestinal movement [83].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [83] Dagdeviren C, Javid F, Joe P Flexible piezoelectric devices for gastrointestinal motility sensing. Nat. Biomed. Eng 1(10), 807 (2017). 31015594

      Not checked in the free run.

  • May combine two claims.

    Findingcitation

    The Empatica Embrace can detect seizures using electrodermal activity and accelerometry and can also notify emergency contacts.

    “The Empatica Embrace (MA, USA), a smartwatch that evolved out of the MIT Media Lab, can detect seizures using electrodermal activity and accelerometry and can also notify emergency contacts [20,21,103].”
    Quote in the paperNot a substantial claim0 of 3 sources checked
    • cites [20] Poh MZ, Loddenkemper T, Reinsberger C Convulsive seizure detection using a wrist-worn electrodermal activity and accelerometry biosensor. Epilepsia 53(5), e93– e97 (2012). 22432935 source

      Not checked in the free run.

    • cites [21] Dolgin E. Dressed to detect. Nature 511(Suppl. 7508), S16– S17 (2014). 25019131

      Not checked in the free run.

    • cites [103] Poh M-Z, Loddenkemper T, Reinsberger C Autonomic changes with seizures correlate with postictal EEG suppression. Neurology 78(23), 1868– 1876 (2012). 22539579 PMC3369522

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  • May combine two claims.

    Findingnone given

    Still a challenge is the dependence on active patient participation and the semi-quantitative nature of the measurements.

    “Still a challenge is the dependence on active patient participation and the semi-quantitative nature of the measurements.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Findingnone given

    Wearable technologies to detect, diagnose and manage gastrointestinal conditions are limited.

    “Wearable technologies to detect, diagnose and manage gastrointestinal conditions are limited.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingcitation

    Sentio Solutions' Feel wristband is anticipated to deliver personalized interventions to the wearer according to their mood state based on a proprietary neural network model that can accurately detect 70-75% of relaxed, anxious, excited and fun mood states using features of heart rate variability and skin conductance (n = 224).

    “One example is Sentio Solutions’ Feel wristband (San Francisco, CA, USA), which is anticipated to deliver personalized interventions to the wearer according to their mood state based on their proprietary neural network model that can accurately detect 70–75% of relaxed, anxious, excited and fun mood states using features of heart rate variability and skin conductance (n = 224) [37].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [37] Martinez HP, Bengio Y, Yannakakis GN. Learning deep physiological models of affect. IEEE Comput. Intel. Mag 8(2), 20– 33 (2013).

      Not checked in the free run.

  • May combine two claims.

    Findingcitation

    In a recent study, 33 and 43% of the alerts successfully engaged the participant in the self-regulation exercise and resulted in de-escalation of a potential episode, respectively.

    “In a recent study, 33 and 43% of the alerts successfully engaged the participant in the self-regulation exercise and resulted in de-escalation of a potential episode, respectively [99].”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [99] Torrado JC, Gomez J, Montoro G. Emotional self-regulation of individuals with autism spectrum disorders: smartwatches for monitoring and interaction. Sensors (Basel) 17(6), 1359 (2017). 28604607 PMC5492838

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  • May combine two claims.

    Findingcitation

    IMUs affixed to shoes were recently found to result in comparable diagnoses with gold standard video-based assessments to distinguish gait differences between PD and unaffected patients and for longitudinal tracking of gait changes in PD (n = 291).

    “IMUs affixed to shoes were recently found to result in comparable diagnoses with gold standard video-based assessments to distinguish gait differences between PD and unaffected patients and for longitudinal tracking of gait changes in PD (n = 291) [78].”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [78] Watanabe S, Hojo M, Nagahara A. Metabolic syndrome and gastrointestinal diseases. J. Gastroenterol 42(4), 267– 274 (2007). 17464454

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationnone given

    Wearable sensors are already impacting healthcare and medicine by enabling health monitoring outside of the clinic and prediction of health events.

    “Wearable sensors are already impacting healthcare and medicine by enabling health monitoring outside of the clinic and prediction of health events.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    Accelerometers are most common in wearables, but gyroscopes are appropriate when it is necessary to differentiate acceleration due to gravity versus acceleration due to movement.

    “Accelerometers are most common in wearables, but gyroscopes are appropriate when it is necessary to differentiate acceleration due to gravity versus acceleration due to movement [39].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [39] Casson AJ, Galvez AV, Jarchi D. Gyroscope vs. accelerometer measurements of motion from wrist PPG during physical exercise. ICT Express 2(4), 175– 179 (2016). source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Premisenone given

    Bioimpedance sensors are thought to be useful for detecting stress and emotion through changes in electrical resistance of tissues related to neural activity.

    “Bioimpedance sensors are thought to be useful for detecting stress and emotion through changes in electrical resistance of tissues related to neural activity.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationnone given

    Wearables facilitate algorithm development for automated health event prediction, prevention and intervention.

    “Wearables also facilitate algorithm development for automated health event prediction, prevention and intervention.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Premisenone given

    One major challenge in wide adoption of wearable biosensor technologies for healthcare is extraction of useful and actionable health-related information from the large volume of data.

    “One of the major challenges in the wide adoption of wearable biosensor technologies for healthcare is the extraction of useful and actionable health-related information from the large volume of data.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationreasoning

    New wearables-based analytic platforms are transforming quality and accessibility of healthcare from hospital ICUs to in-home chronic disease management to resource-limited field settings.

    “New wearables-based analytic platforms are coming online at an unprecedented rate and are transforming quality and accessibility of healthcare everywhere from hospital intensive care units (ICUs) to in-home chronic disease management to resource-limited field settings.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationnone given

    Wearable devices provide opportunities to improve healthcare in settings from in-hospital and in-clinic care to ambulatory care in the home and remote geographical settings.

    “Wearable devices provide opportunities to improve healthcare in a variety of settings, from in-hospital and in-clinic care, to ambulatory care in the home and in remote geographical settings including rural areas and low-resource environments (Figure 2A).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Nonimplantable wearable sensors can generally be classified into three main categories: mechanical, physiological and biochemical.

    “These sensors can generally be classified into three main categories: mechanical, physiological and biochemical (Figure 1B) [1].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [1] Tamsin M. Wearable biosensor technologies. Int. J. Innov. Sci. Res 13, 697– 703 (2015).

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationnone given

    Healthcare practitioners are now beginning to adopt wearables for patient monitoring.

    “Previously geared toward consumer health enthusiasts, healthcare practitioners are now beginning to adopt wearables for patient monitoring.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    Diagnosis and monitoring of hypertension and treatment efficacy is difficult because a single blood pressure measurement in the clinic often does not capture true average BP, BP fluctuates throughout the day based on circadian rhythms and daily activity, and white coat syndrome can lead to higher BP measurements in the clinic.

    “Diagnosis and monitoring of hypertension and treatment efficacy is difficult for a few reasons: a single blood pressure (BP) measurement in the clinic often does not capture true average BP, BP fluctuates throughout the day based on circadian rhythms and daily activity, and the ‘white coat syndrome’ can lead to higher BP measurements in the clinic [68-73].”
    Quote in the paperSubstantial claim0 of 6 sources checked
    • cites [68] Wexler R. Ambulatory blood pressure monitoring in primary care. South Med. J 103(5), 447– 452 (2010). 20375938

      Not checked in the free run.

    • cites [69] Hermida RC, Ayala DE, Mojon A, Fernandez JR. Decreasing sleep-time blood pressure determined by ambulatory monitoring reduces cardiovascular risk. J. Am. Coll. Cardiol 58(11), 1165– 1173 (2011). 21884956

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    • cites [70] Burkard T, Mayr M, Winterhalder C, Leonardi L, Eckstein J, Vischer AS. Reliability of single office blood pressure measurements. Heart doi: 10.1136/heartjnl-2017-312523 (2018) (Epub ahead of print). 29530989

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    • cites [71] Asayama K, Thijs L, Brguljan-Hitij J Risk stratification by self-measured home blood pressure across categories of conventional blood pressure: a participant-level meta-analysis. PLoS Med 11(1), e1001591 (2014). 24465187 PMC3897370 source

      Not checked in the free run.

    • cites [72] Pickering TG. The clinical significance of diurnal blood pressure variations. Dippers and nondippers. Circulation 81(2), 700– 702 (1990). 2137050

      Not checked in the free run.

    • cites [73] Mahabala C, Kamath P, Bhaskaran U, Pai ND, Pai AU. Antihypertensive therapy: nocturnal dippers and nondippers. Do we treat them differently? Vasc. Health Risk Manag. 9, 125– 133 (2013). 23569382 PMC3616131

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Polysomnography, the current gold standard for sleep monitoring, often conflicts with subjective self-reports of sleep and is difficult to monitor longitudinally.

    “Polysomnography, the current gold standard for sleep monitoring, often conflicts with subjective self-reports of sleep and is difficult to monitor longitudinally [84].”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [84] Kaplan KA, Hirshman J, Hernandez B When a gold standard isn’t so golden: lack of prediction of subjective sleep quality from sleep polysomnography. Biol. Psychol 123, 37– 46 (2017). 27889439 PMC5292065

      Not checked in the free run.

  • May combine two claims.

    Interpretationreasoning

    With the ability to more accurately track acute and chronic neurologic and mental health symptoms, the opportunity for real-time intervention follows.

    “With the ability to more accurately track acute and chronic neurologic and mental health symptoms, the opportunity for real-time intervention follows.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Interpretationreasoning

    The devices described provide new sensing and potential therapeutic modalities and are expected to dramatically improve gastrointestinal care.

    “The devices described above provide new sensing and potential therapeutic modalities and are expected to dramatically improve gastrointestinal care.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Interpretationnone given

    If FDA approved, these devices will pioneer the field of continuous BP monitoring.

    “If FDA approved, these devices will pioneer the field of continuous BP monitoring.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    Continuous, passive wearables monitoring can lower dependence on participant interaction and increase the volume of data that can be collected over time.

    “Continuous, passive wearables monitoring can lower dependence on participant interaction and increase the volume of data that can be collected over time.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    Sleep impacts chronic illness, neurological conditions and acute cognitive function including memory and mood.

    “Sleep impacts chronic illness, neurological conditions and acute cognitive function including memory and mood [22,88-90].”
    Quote in the paperNot a substantial claim0 of 4 sources checked
    • cites [22] Kroll RR, Mckenzie ED, Boyd JG Use of wearable devices for post-discharge monitoring of ICU patients: a feasibility study. J. Intensive Care 5, 64 (2017). 29201377 PMC5698959

      Not checked in the free run.

    • cites [88] Horvath K, Aschermann Z, Acs P Is the MDS-UPDRS a good screening tool for detecting sleep problems and daytime sleepiness in Parkinson’s disease? Parkinsons Dis. 2014, 806169 (2014). 25506041 PMC4251816

      Not checked in the free run.

    • cites [89] Walker MP. The role of sleep in cognition and emotion. Ann. NY Acad. Sci 1156, 168– 197 (2009). 19338508

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    • cites [90] Bianchi MT. Sleep devices: wearables and nearables, informational and interventional, consumer and clinical. Metabolism 84 99– 108 (2017). 29080814

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  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    Gait analysis is used to assess Parkinson's Disease patients and generally requires video-based motion-capture in a specialized laboratory.

    “Gait analysis is also used to assess Parkinson’s Disease (PD) patients and generally requires video-based motion-capture in a specialized laboratory [34].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [34] Schlachetzki JC, Barth J, Marxreiter F Wearable sensors objectively measure gait parameters in Parkinson’s disease. PLoS ONE 12(10), e0183989 (2017). 29020012 PMC5636070

      Not checked in the free run.

  • May combine two claims.

    Study design and conductcitation

    The Bloomlife labor risk score was developed based on in-hospital data from 55 pregnant women and evaluated on recordings from 142 pregnant women in free-living conditions.

    “Their labor risk score was developed based on in-hospital data from 55 pregnant women and was evaluated on recordings from 142 pregnant women in free-living conditions.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [18] Altini M, Rossetti E, Rooijakkers M Combining electrohysterography and heart rate data to detect labour. Presented at: Biomedical & Health Informatics (BHI), 2017 IEEE EMBS International Conference Orlando-, FL, USA (16-19 February 2017).

      Not checked in the free run.

    • cites [120] Altini M, Rossetti E, Rooijakkers M 762: remote labour detection using maternal electrohysterography and heart rate data acquired with a wearable sensor. Am. J. Obstet. Gynecol 216(1), S441– S442 (2017).

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationnone given

    Commercially available motion sensing, physiological and biochemical wearable sensors have been adopted for use in both consumer and clinical healthcare.

    “Commercially available motion sensing, physiological and biochemical wearable sensors have been adopted for use in both consumer and clinical healthcare.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationnone given

    Wearable and environmental sensors promise to improve information collection and transfer rapidly, potentially to off-site experts, and specially designed algorithms enable automated and real-time medical decision support in time- and resource-constrained environments.

    “Wearable and environmental sensors promise to improve information collection and transfer rapidly, potentially to off-site experts and specially designed algorithms enable automated and real-time medical decision support in time- and resource-constrained environments (Figure 2B).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    The ADAMM study established the device's utility for detection and a modest potential to predict near-future disease progression.

    “This study established the device’s utility for detection and a modest potential to predict near-future disease progression.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    Most wrist-worn devices adequately measure heart rate in laboratory-based activities, but poorly estimate energy expenditure.

    “Shcherbina et al. demonstrated that most wrist-worn devices adequately measure HR in laboratory-based activities, but poorly estimate energy expenditure and caution the use of those measurements as part of health improvement programs [144].”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [144] Shcherbina A, Mattsson CM, Waggott D Accuracy in wrist-worn, sensor-based measurements of heart rate and energy expenditure in a diverse cohort. J. Pers. Med 7(2), 3 (2017). 28538708 PMC5491979 source

      Not checked in the free run.

  • May combine two claims.

    Interpretationcitation

    Wearable tools can be used in specific settings to target extreme healthcare costs, for example, by reducing emergency room visits and hospital readmission rates, improving postsurgical and rehabilitation outcomes, assisting with aging in-home, and preventing serious, preventable and costly medical events.

    “Further, these tools can be used in specific settings to target extreme healthcare costs, for example, by reducing emergency room visits and hospital readmission rates, improving postsurgical and rehabilitation outcomes, assisting with aging in-home, and preventing serious, preventable and costly medical events (deemed ‘never events’ by CMS) (Figure 2A) [137].”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [137] Centers for Medicare & Medicaid Services. Eliminating serious, preventable, and costly medical errors – never events (2013). www.cms.gov/Newsroom/MediaReleaseDatabase/Fact-sheets/2006-Fact-sheets-items/2006-2005-2018.html

      Not checked in the free run.

  • May combine two claims.

    Interpretationcitation

    The acceptability of wearable devices and potential stigma associated with them varies by community and may be a factor in dividing who benefits from these technologies.

    “The acceptability of these devices and potential stigma associated with them varies by community and may also be a factor in dividing who benefits from these technologies [141].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [141] Farrington C. Wearable technologies and stigma in diabetes: the role of medical aesthetics. Lancet Diabetes Endocrinol. 4(7), 566 (2016). 26923941

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Premisenone given

    Several neurologic disorders include motor control dysregulation.

    “Several neurologic disorders include motor control dysregulation.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationnone given

    There is a wide effort to integrate information from wearable devices into electronic health records.

    “Currently, there is a wide effort to integrate information from these devices into electronic health records.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationnone given

    Wearable sensors have an extremely broad variety of applications to specific areas of medicine, enabling monitoring of acute and chronic conditions and overall health both in and outside of the clinical setting.

    “Wearable sensors have an extremely broad variety of applications to specific areas of medicine, enabling monitoring of acute and chronic conditions and overall health both in and outside of the clinical setting.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationnone given

    Although consumer-grade research devices have been primarily adopted for fitness, medical professionals are beginning to find utility in information collected by these devices.

    “Although consumer-grade research devices have been primarily adopted for fitness, medical professionals are beginning to find utility in information collected by these devices.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    Based on collective results of 16 studies, wheeze event classification had accuracies between 75.78-100% and crackle event classification had accuracies between 89-98.15%.

    “Based on collective results of 16 studies, wheeze and crackle event classification had accuracies between 75.78–100% and 89–98.15%, respectively [124].”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [124] Pramono RXA, Bowyer S, Rodriguez-Villegas E. Automatic adventitious respiratory sound analysis: a systematic review. PLoS ONE 12(5), e0177926 (2017). 28552969 PMC5446130

      Not checked in the free run.

  • May combine two claims.

    Interpretationnone given

    Many devices are not compatible across platforms and there is a lack of data standards, which limits their broad use and ubiquity.

    “Further, many devices are not compatible across platforms (e.g., iOS and Android smart phone operating systems) and there is a lack of data standards which limits their broad use and ubiquity.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    Wheezing is linked to both asthma and chronic obstructive pulmonary disease, while fine crackling is linked with pneumonia, congestive heart failure and lung fibrosis.

    “Wheezing, characterized by narrowing airway and limited airflow, is linked to both asthma and chronic obstructive pulmonary disease while fine crackling, caused by ‘explosive opening of small airways,’ is linked with pneumonia, congestive heart failure and lung fibrosis [124].”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [124] Pramono RXA, Bowyer S, Rodriguez-Villegas E. Automatic adventitious respiratory sound analysis: a systematic review. PLoS ONE 12(5), e0177926 (2017). 28552969 PMC5446130

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Interpretationnone given

    The time needed to choose and properly set up a device, and remembering to charge the device, are potential barriers to proper use.

    “The time needed to choose and properly set up a device, and remembering to charge the device are also potential barriers to proper use.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Interpretationnone given

    False negatives from wearable devices can cause a potentially fatal condition to be missed, while false positives can lead to overtreatment and/or anxiety.

    “False negatives can cause a potentially fatal condition to be missed while false positives can lead to overtreatment and/or anxiety.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationnone given

    It is common to find unsubstantiated scientific claims with no reference to peer-reviewed studies on commercial wearable device company websites and advertising materials.

    “It is common to find unsubstantiated scientific claims with no reference to peer-reviewed studies on commercial wearable device company websites and advertising materials that can set a dangerous precedent if inaccurate or misinterpreted data is factored into medical decision making.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationnone given

    Wearables can inform ongoing or new symptoms, such as medication side effects or interactions, and may be able to provide automated just-in-time interventions.

    “Wearables can inform ongoing or new symptoms, such as medication side effects or interactions, and may be able to provide automated just-in-time interventions.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationnone given

    High device cost is a concern that may hinder the accessibility of wearable healthcare technology to benefit only those who can afford the devices.

    “High device cost is a concern that may hinder the accessibility of this consumer healthcare technology to benefit only those who can afford the devices.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Interpretationnone given

    The tripartite regulation of wearable devices by the FDA, FCC and CMS creates challenges for device manufacturers and vendors because regulations can be difficult to adhere to due to different, sometimes divergent, objectives of these agencies.

    “The tripartite regulation of wearable devices by the federal government through the FDA, Federal Communications Commission and CMS creates challenges for device manufacturers and vendors whereby regulations can be difficult to adhere to due to the different, and sometimes divergent, objectives of these agencies.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    Pantelopoulos and Bourbakis created a scoring system from the perspective of patient/wearer, manufacturer and supervising physician for wearables and found that many systems score low on wearability because sensor, battery and on-body hardware size tends to be too bulky in weight and size.

    “Pantelopoulos and Bourbakis created a scoring system from the perspective of the patient/wearer, the manufacturer and supervising physician for wearables found that many systems score low on wearability, because sensor, battery and on-body hardware size tends to be too bulky in weight and size [165].”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [165] Pantelopoulos A, Bourbakis N. A survey on wearable biosensor systems for health monitoring. Conf. Proc. IEEE Eng. Med. Biol. Soc. 2008, 4887– 4890 (2008). 19163812

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    Wristbands to detect environmental exposures have been successful but require off-site analysis using gas chromatography on returned wristbands.

    “Wristbands to detect environmental exposures have been successful but require off-site analysis using gas chromatography on returned wristbands [154].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [154] Donald CE, Scott RP, Blaustein KL Silicone wristbands detect individuals’ pesticide exposures in West Africa. R. Soc. Open Sci 3(8), 160433 (2016). 27853621 PMC5108971

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.

    Interpretationnone given

    Although immense progress has been made in wearable sensing technologies and their healthcare applications, significant limitations must be addressed for wearable biosensing to achieve its full potential of seamless integration into healthcare.

    “Although immense progress has been made over the past several decades in wearable sensing technologies and even more recently toward their applications in healthcare, significant limitations must be addressed for wearable biosensing to achieve its full potential of seamless integration into healthcare.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    The wristband sweat sensor also measures skin temperature for calibration, and that data is useful in analyzing health.

    “The wristband device also measures skin temperature for calibration, and that data is also useful in analyzing health as described earlier [126,156].”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [126] Asimina S, Chapizanis D, Karakitsios S Assessing and enhancing the utility of low-cost activity and location sensors for exposure studies. Environ. Monit. Assess 190(3), 155 (2018). 29464404

      Not checked in the free run.

    • cites [156] Gao W, Emaminejad S, Nyein HYY Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis. Nature 529(7587), 509– 514 (2016). 26819044 PMC4996079 source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Interpretationnone given

    There are often conflicting technological constraints in device design.

    “There are often conflicting technological constraints in device design.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    The wristband sweat sensor was recently tested for cystic fibrosis diagnosis and preliminary investigation of the blood/sweat glucose correlation.

    “This device was recently tested for cystic fibrosis diagnosis and preliminary investigation of the blood/sweat glucose correlation [161].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [161] Emaminejad S, Gao W, Wu E Autonomous sweat extraction and analysis applied to cystic fibrosis and glucose monitoring using a fully integrated wearable platform. Proc. Natl Acad. Sci. USA 114(18), 4625– 4630 (2017). 28416667 PMC5422810 •• A seminal demonstration of how fully integrated wearable platforms with multimodal measurement capabilities can dramatically improve monitoring and intervention capabilities. source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationnone given

    Unsubstantiated claims that overstate the testing accuracy and indications for the device are commonly made by wearable device companies to improve sales.

    “Unsubstantiated claims that overstate the testing accuracy and indications for the device are commonly made by wearable device companies to improve sales, and further regulations are needed to ensure their appropriate use and to evaluate the potential harm that may result from medical interventions or overdiagnosis based on the use of these devices.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationnone given

    FDA-regulated devices like CGMs have substantially more clinical trials establishing their safety and efficacy in healthcare, but consumer-grade FDA devices have limited evidence of their utility in healthcare.

    “FDA-regulated devices like CGMs have substantially more clinical trials establishing the safety and efficacy of these devices in healthcare (only the most recent/impactful studies are referenced for brevity), but consumer-grade FDA devices have limited evidence of their utility in healthcare.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    BreathLink is a breath analysis technology to identify women with breast cancer and pulmonary tuberculosis, but it is not yet in a wearable form factor.

    “BreathLink is another breath analysis technology to identify women with breast cancer and pulmonary tuberculosis, but this technology is not yet in a wearable form factor [152,153].”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [152] Phillips M, Beatty JD, Cataneo RN Rapid point-of-care breath test for biomarkers of breast cancer and abnormal mammograms. PLoS ONE 9(3), e90226 (2014). 24599224 PMC3943910

      Not checked in the free run.

    • cites [153] Phillips M, Basa-Dalay V, Blais J Point-of-care breath test for biomarkers of active pulmonary tuberculosis. Tuberculosis (Edinb.) 92(4), 314– 320 (2012). 22647661

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    This type of integrated device has been explored most recently through closed-loop insulin delivery systems for Type 1 diabetics, and broader applications are forthcoming.

    “This type of device has been explored most recently through closed-loop insulin delivery systems for Type 1 diabetics, and broader applications are forthcoming [162].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [162] Stone JY, Haviland N, Bailey TS. Review of a commercially available hybrid closed-loop insulin-delivery system in the treatment of Type 1 diabetes. Ther. Deliv 9(2), 77– 87 (2018). 29235423

      Not checked in the free run.

  • May combine two claims.

    Interpretationreasoning

    Challenges to improving algorithms for wearable data include the wide range of device and system architectures and the proprietary nature of many analytic platforms, which limit their generalizability.

    “Challenges to addressing this include the wide range of device and system architectures and the proprietary nature of many analytic platforms which limit their generalizability.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    Wearable oxygen diffusion sensors have been used to track wound healing, and moisture sensors can inform better timing of wound dressing changes.

    “Wearable oxygen diffusion sensors have been used to track wound healing, and moisture sensors can inform better timing of wound dressing changes [148,149].”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [148] Niederauer MQ, Michalek JE, Armstrong DG. A prospective, randomized, double-blind multicenter study comparing continuous diffusion of oxygen therapy to sham therapy in the treatment of diabetic foot ulcers. J. Diabetes Sci. Technol 11(5), 883– 891 (2017). 28654304 PMC5950983

      Not checked in the free run.

    • cites [149] Milne SD, Seoudi I, Al Hamad H A wearable wound moisture sensor as an indicator for wound dressing change: an observational study of wound moisture and status. Int. Wound J 13(6), 1309– 1314 (2016). 26561281 PMC7950073

      Not checked in the free run.

66 of 66

  • The paper relies on this without support.

    Most airway abnormalities can be characterized by abnormal sounds (adventitious sounds).

    “Pulmonary disease wearables take advantage of the fact that most airway abnormalities can be characterized by the abnormal sounds (adventitious sounds).”
1 of 1

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Five initiatives are called four

    Minor

    The sentence names five initiatives but says there are four.

1 of 1

Cites

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Research works printed but not linked: 4

  1. 10.1177/19322968187632281932296818763228 · DOI
  2. Nandakumar S . Long-term remote monitoring of vital signs using a wireless patch sensor . Presented at: IEEE Health Innovations and Point-of-Care Technologies Conference . Seattle, WA, USA ( 8–10 October 2014 ).
  3. Semi Supervised Sequence Learning for Continuous Digital Biomarkers. Neural information processing systems machine learning for healthcare workshop ( 2016 ). www.nipsml4hc.ws/posters .
  4. WHO . Improving access to epilepsy care . WHO/entity/mental_health/neurology/epilepsy/en/index.html( 2018 ) ( Epub ahead of print ).

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Related

Authors
Dunn, J., Runge, R., & Snyder, M.
Affiliations
Stanford University (US)
Corresponding author
Snyder, Michael
ORCID
Venue
Personalized Medicine
Publisher
Informa UK Limited
Published
2018-09
Volume
15
Issue
5
Pages
429-448
ISSN
  • 1741-0541 (ISSN-L)
  • 1744-828X
DOI
10.2217/pme-2018-0044
PMC
PMC12294383
OpenAlex
W2893814198
Semantic Scholar
10a52258659a025213707790354a6cc13482bade
Cited by
654
References
154
Citations by year
2026: 99 · 2025: 88 · 2024: 101 · 2023: 94 · 2022: 94 · 2021: 95 · 2020: 56 · 2019: 22 · 2018: 5
FWCI
3.64
Type
journal article
Language
en
Open access
Licence
Locations
  • Personalized Medicine (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
Funders
Mobilize Center (U54 EB020405)
Topics
  • Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
  • Physical Sciences › Engineering › Biomedical Engineering › Wireless Body Area Networks
Keywords
wearable sensors, remote patient monitoring, clinical translation, metabolic monitoring, cardiovascular monitoring, gastrointestinal monitoring, sleep monitoring, neurology, movement disorders, mental health, maternal and newborn care, respiratory health, environmental exposure monitoring
MeSH terms
Wearable Electronic Devices, Delivery of Health Care, Humans, Monitoring, Physiologic, Telemetry, Monitoring, Ambulatory, Wireless Technology

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-09.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-09.

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