ArticleJournal of diabetes science and technology2018
First Experiences With a Wearable Multisensor in an Outpatient Glucose Monitoring Study, Part I: The Users' View.
Article in Journal of diabetes science and technology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Insertable Glucose Sensor Using a Compact and Cost-Effective Phosphorescence Lifetime Imager and Machine Learning.ACS nano · 2024Article
- The Impact of Wearable Technologies in Health Research: Scoping Review.JMIR mHealth and uHealth · 2022Article
- Smart-watch-programmed green-light-operated percutaneous control of therapeutic transgenes.Nature communications · 2021Article
- Review of Non-invasive Glucose Sensing Techniques: Optical, Electrical and Breath Acetone.Sensors (Basel, Switzerland) · 2020Review
- Continuous noninvasive glucose monitoring; water as a relevant marker of glucose uptake in vivo.Biophysical reviews · 2019Review
- Retrospective Continuous-Time Blood Glucose Estimation in Free Living Conditions with a Non-Invasive Multisensor Device.Sensors (Basel, Switzerland) · 2019Article
- Radio-Frequency and Microwave Techniques for Non-Invasive Measurement of Blood Glucose Levels.Diagnostics (Basel, Switzerland) · 2019Review
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Authors and funding
8 authors.
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Abstract
backgroundExtensive past work showed that noninvasive continuous glucose monitoring with a wearable Multisensor device worn on the upper arm provides useful information about glucose trends to improve diabetes therapy in controlled and semicontrolled conditions.
methodsTo test previous findings also in uncontrolled in-clinic and outpatient conditions, a long-term study has been conducted to collect Multisensor and reference glucose data in a population of 20 type 1 diabetes subjects. A total of 1072 study days were collected and a fully on-line compatible algorithmic routine linking Multisensor data to glucose applied to estimate glucose trends noninvasively. The operation of a digital log book, daily semiautomated data transfer and at least 10 daily SMBG values were requested from the patient.
resultsResults showed that the Multisensor is capable of indicating glucose trends. It can do so in 9 out of 10 cases either correctly or with one level of discrepancy. This means that in 90% of all cases the Multisensor shows the glucose dynamic to rapidly increase or at least increase.
conclusionsThe Multisensor and the algorithmic routine used in controlled conditions can track glucose trends in all patients, also in uncontrolled conditions. Training of the patient proved to be essential. The workload imposed on patients was significant and should be reduced in the next step with further automation. The feature of glucose trend indication was welcomed and very much appreciated by patients; this value creation makes a strong case for the justification of wearing a wearable.
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