Type1 Diabetes MellitusNCT04725799
Additional Signals for Exercise, Stress and Sleep and Prediction of Glucose Levels for AP Systems
An observational study of Type1 Diabetes Mellitus, run by University of Illinois Chicago at 1 site in United States.
Trial summary
The objective of this research is to determine the most informative variables for detecting exercise, acute stress and sleep, identify select sensors that report these variables, and develop the algorithms to detect the occurrence of exercise, stress and sleep, to discriminate them and to determine their… Read more about this study
- Who is it for?
- Ages 18 to 60 years
- Conditions the study is for
- Type1 Diabetes Mellitus
- How many people
- 23 participants
- Where
- 1 siteUnited States
- Study dates
- 24 May 2018to 13 Jul 2021
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 60 years
- All sexes
- No healthy volunteers
- Adult
Study population: Men and Women with Type 1 Diabetes
Who may be able to join
- Men and Women with T1DM
- 18-60 years of age
- Insulin pump user
Who cannot join
- Metabolic instability as evidenced by hospitalizations for diabetes or other diabetes-related complications (e.g., diabetic ketoacidosis and hypoglycemic seizures) within the preceding three months;
- Severe macrovascular disease, as evidenced by severe peripheral artery disease; history of myocardial infarction, heart failure, thromboembolic disease, or unstable angina; uncontrolled hypertension; abnormal resting EKG;
- Maximal exercise stress test with significant brady/tachy arrhythmia, ectopic beats, bundle branch block, or signs of acute ischemia;
- Severe microvascular disease as evidenced by history of vision-threatening proliferative or non-proliferative retinal disease; kidney disease;
- Any uncontrolled non-musculoskeletal condition that would limit the subject's ability to participate in the exercise program (e.g., chronic obstructive airways disease);
- Musculoskeletal conditions such as neurological or orthopedic conditions affecting lower limb strength and mobility (e.g., stroke; insensitive foot);
- Pregnancy;
- Documented medical condition or physical impairment that is judged by the health care practitioner to contraindicate exercise.
Trial locations and contacts
1 site in 1 country.
United States1 site
University of Illinois at Chicago
Chicago, Illinois, 60612
About this study
Official title: Additional Signals for Detection of Exercise, Stress and Sleep Effects and Prediction of Glucose Levels for Next Generation AP Systems
The objective of this research is to determine the most informative variables for detecting exercise, acute stress and sleep, identify select sensors that report these variables, and develop the algorithms to detect the occurrence of exercise, stress and sleep, to discriminate them and to determine their characteristics. Research is needed to identify which wearable devices report the most informative and predictive variables of exercise, acute stress and sleep with desired precision and accuracy, determine the best location to wear them for collecting reliable and informative data, and to distill accurate knowledge from data reported by wearable sensors. Data and their interpretation should be informative for various types of physical activities, stages of sleep, and types and intensities of acute stress, and concurrent occurrence of these factors. The investigators will use several devices (chest band, wristband and skin patches) to collect data and evaluate their information content and contribution to improvement of glucose concentration prediction, best locations for collecting accurate and reliable information by conducting clinical and free-living experiments at-home to assess the contributions of the wearable device in improving the accuracy of glucose concentration prediction and the performance of the multivariable artificial pancreas.
Read the detailed description
The focus of the proposed work is to determine the most informative variables for meals, exercise, acute stress and sleep (MESS), identify select sensors that report these variables, and develop the algorithms to detect the occurrence of MESS, to discriminate them and to determine their characteristics. Research is needed to identify which wearable devices report the most informative and predictive variables of MESS with desired precision and accuracy, determine the best location to wear them for collecting reliable and informative data, and to distill accurate knowledge from data reported by wearable sensors. Data and their interpretation should be informative for various types of physical activities, stages of sleep, and types and intensities of acute stress, and concurrent occurrence of MESS factors.
In the first year of the research, the investigators will use several devices to collect data and evaluate their information content and contribution to improvement of serum glucose prediction, best locations for collecting accurate and reliable information, and their acceptance by users. In the second year of the project, we will select a single wearable device, conduct additional clinical and free-living experiments at-home to assess the contributions of the information from the wearable device selected in improving the accuracy of glucose prediction and the performance of the multivariable AP.
The objectives of the proposed research are to determine the most informative variables and sensor locations to capture reliable and accurate information that complement glucose concentration measurements (CGM) and to develop algorithms to determine the presence of exercise, stress or sleep at any given time for estimating glucose concentrations and making control decisions by a multivariable artificial pancreas system. The proposed research will be conducted by achieving the following specific aims:
To systematically perturb the MESS factors within standardized experiments in the laboratory and at home for analyzing their effects and interactions on glucose concentrations; to identify the most informative and reliable measurement approaches (i.e. types of wearable sensors and locations on body) for discriminating MESS factors; to develop quantitative relations that identify the type and features of specific MESS activities, to develop algorithms to detect the presence of specific MESS activities, identify them, and predict glucose concentrations with recursive models in real time (for future integration with adaptive AP control systems); and to evaluate the performance of the multivariable models with data from wearable devices and CGM in closed-loop control with AP during exploratory clinical experiments.
The study will take place over a period of 3-4 weeks for a total of 6 study visits. The subjects will be continuously monitored using CGM (DEXCOM [US G5 PLATINUM]); 3 activity of the following activity monitor(s); (Empatica E4, BiostampRC™, Equivital™ Life Monitor) and Actigraph throughout the night. In addition, the subjects will use a sleep monitor (Zmachine® Insight \& Insight+ Model DT-200 and Zephyr Bioharness) throughout the 3-week period. Subjects will come in for a study visit 3 times during the first week during which the investigators will measure the subjects' oxygen capacity and muscular strength during a peak exercise stress test (peak V02) and a test of maximal muscle strength (1-RM), respectively. The results of this testing will establish a baseline from which we can calculate the intensity of submaximal aerobic and resistance exercise bouts. The next 3 study visits will occur over the following 3-4 weeks. During this time the subjects will perform activities that produce physiological and psychological stress alone, in combination or proximal to each other. Women will have a urine pregnancy test before each day of data collection. In addition, the subjects will perform a number of physical activities at home that will be scheduled with the research assistant. The research assistant will telephone the subjects periodically and have the subjects perform stressful activities, such as mental challenges.
- Conditions
- Type1 Diabetes Mellitus
- Keywords
- Exercise, Meals, Sleep, Stress, Artificial Pancreas
- Medical subject headings
- Motor Activity
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| MESS with and without stressful stimuli | The subjects participate in meal, exercise, sleep activities alone or in combination with stressful stimuli. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Measurement of Glucose Concentration
- Glucose concentration (mg/dl) will be measured by: Continuous Glucose Monitor (DEXCOM [US G5 PLATINUM/G6]
Measured: 3.5 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted27 Jan 2021
- Study start24 May 2018
- Primary completion13 Jul 2021
- Study completion13 Jul 2021
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (5)Papers the sponsor has linked to this study.
- Other trials for Type1 Diabetes MellitusStudies of the same condition, open and under way.
- More trials run by University of Illinois ChicagoThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Cross-sectional
- Enrolment
- 23 participants (actual)
Sponsor and investigators
- Lead sponsor
- University of Illinois Chicago
- Sponsor type
- University, hospital or other
- Collaborators
- Illinois Institute of Technology, University of Chicago
- Responsible party
- Principal investigator, Laurie Quinn, University of Illinois Chicago
- Investigators
- Ali Cinar, PhD, Principal investigator, Illinois Institute of Technoloy
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04725799
- Sponsor's protocol ID
- 2017-1016
- Status last verified
- Mar 2022
- First submitted
- 30 May 2018
- Last updated
- 1 Apr 2022
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Turksoy K, Samadi S, Feng J, Littlejohn E, Quinn L, Cinar A. Meal Detection in Patients With Type 1 Diabetes: A New Module for the Multivariable Adaptive Artificial Pancreas Control System. IEEE J Biomed Health Inform. 2016 Jan;20(1):47-54. doi: 10.1109/JBHI.2015.2446413. Epub 2015 Jun 16.
PubMed 26087510Eren-Oruklu M, Cinar A, Rollins DK, Quinn L. Adaptive System Identification for Estimating Future Glucose Concentrations and Hypoglycemia Alarms. Automatica (Oxf). 2012 Aug;48(8):1892-1897. doi: 10.1016/j.automatica.2012.05.076. Epub 2012 Jun 22.
PubMed 22865931Turksoy K, Bayrak ES, Quinn L, Littlejohn E, Rollins D, Cinar A. Hypoglycemia Early Alarm Systems Based On Multivariable Models. Ind Eng Chem Res. 2013 Sep 4;52(35):12329-36. doi: 10.1021/ie3034015.
PubMed 24187436Bayrak ES, Turksoy K, Cinar A, Quinn L, Littlejohn E, Rollins D. Hypoglycemia early alarm systems based on recursive autoregressive partial least squares models. J Diabetes Sci Technol. 2013 Jan 1;7(1):206-14. doi: 10.1177/193229681300700126.
PubMed 23439179Turksoy K, Roy A, Cinar A. Real-Time Model-Based Fault Detection of Continuous Glucose Sensor Measurements. IEEE Trans Biomed Eng. 2017 Jul;64(7):1437-1445. doi: 10.1109/TBME.2016.2535412. Epub 2016 Feb 25.
PubMed 26930674
Study at a glance
From the registry record, last updated by the sponsor on 1 Apr 2022. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Additional Signals for Detection of Exercise, Stress and Sleep Effects and Prediction of Glucose Levels for Next Generation AP Systems
- ClinicalTrials.gov ID
- NCT04725799
- Acronym / sponsor ID
- 2017-1016
- Conditions
- Type1 Diabetes Mellitus
- Keywords
- Exercise, Meals, Sleep, Stress, Artificial Pancreas
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 23 participants (actual)
- Lead sponsor
- University of Illinois ChicagoUniversity, hospital or other
- Collaborators
- Illinois Institute of Technology, University of Chicago
- Study start
- 24 May 2018 (actual)
- Primary completion
- 13 Jul 2021 (actual)
- Study completion
- 13 Jul 2021 (actual)
- First posted
- 27 Jan 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The objective of this research is to determine the most informative variables for detecting exercise, acute stress and sleep, identify select sensors that report these variables, and develop the algorithms to detect the occurrence of exercise, stress and sleep, to discriminate them and to determine their characteristics. Research is needed to identify which wearable devices report the most informative and predictive variables of exercise, acute stress and sleep with desired precision and accuracy, determine the best location to wear them for collecting reliable and informative data, and to distill accurate knowledge from data reported by wearable sensors. Data and their interpretation should be informative for various types of physical activities, stages of sleep, and types and intensities of acute stress, and concurrent occurrence of these factors. The investigators will use several devices (chest band, wristband and skin patches) to collect data and evaluate their information content and contribution to improvement of glucose concentration prediction, best locations for collecting accurate and reliable information by conducting clinical and free-living experiments at-home to assess the contributions of the wearable device in improving the accuracy of glucose concentration prediction and the performance of the multivariable artificial pancreas.
Detailed description
The focus of the proposed work is to determine the most informative variables for meals, exercise, acute stress and sleep (MESS), identify select sensors that report these variables, and develop the algorithms to detect the occurrence of MESS, to discriminate them and to determine their characteristics. Research is needed to identify which wearable devices report the most informative and predictive variables of MESS with desired precision and accuracy, determine the best location to wear them for collecting reliable and informative data, and to distill accurate knowledge from data reported by wearable sensors. Data and their interpretation should be informative for various types of physical activities, stages of sleep, and types and intensities of acute stress, and concurrent occurrence of MESS factors.
In the first year of the research, the investigators will use several devices to collect data and evaluate their information content and contribution to improvement of serum glucose prediction, best locations for collecting accurate and reliable information, and their acceptance by users. In the second year of the project, we will select a single wearable device, conduct additional clinical and free-living experiments at-home to assess the contributions of the information from the wearable device selected in improving the accuracy of glucose prediction and the performance of the multivariable AP.
The objectives of the proposed research are to determine the most informative variables and sensor locations to capture reliable and accurate information that complement glucose concentration measurements (CGM) and to develop algorithms to determine the presence of exercise, stress or sleep at any given time for estimating glucose concentrations and making control decisions by a multivariable artificial pancreas system. The proposed research will be conducted by achieving the following specific aims:
To systematically perturb the MESS factors within standardized experiments in the laboratory and at home for analyzing their effects and interactions on glucose concentrations; to identify the most informative and reliable measurement approaches (i.e. types of wearable sensors and locations on body) for discriminating MESS factors; to develop quantitative relations that identify the type and features of specific MESS activities, to develop algorithms to detect the presence of specific MESS activities, identify them, and predict glucose concentrations with recursive models in real time (for future integration with adaptive AP control systems); and to evaluate the performance of the multivariable models with data from wearable devices and CGM in closed-loop control with AP during exploratory clinical experiments.
The study will take place over a period of 3-4 weeks for a total of 6 study visits. The subjects will be continuously monitored using CGM (DEXCOM [US G5 PLATINUM]); 3 activity of the following activity monitor(s); (Empatica E4, BiostampRC™, Equivital™ Life Monitor) and Actigraph throughout the night. In addition, the subjects will use a sleep monitor (Zmachine® Insight \& Insight+ Model DT-200 and Zephyr Bioharness) throughout the 3-week period. Subjects will come in for a study visit 3 times during the first week during which the investigators will measure the subjects' oxygen capacity and muscular strength during a peak exercise stress test (peak V02) and a test of maximal muscle strength (1-RM), respectively. The results of this testing will establish a baseline from which we can calculate the intensity of submaximal aerobic and resistance exercise bouts. The next 3 study visits will occur over the following 3-4 weeks. During this time the subjects will perform activities that produce physiological and psychological stress alone, in combination or proximal to each other. Women will have a urine pregnancy test before each day of data collection. In addition, the subjects will perform a number of physical activities at home that will be scheduled with the research assistant. The research assistant will telephone the subjects periodically and have the subjects perform stressful activities, such as mental challenges.
Study design
- Observational model
- Cohort
- Time perspective
- Cross-sectional
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| MESS with and without stressful stimuli | – | –The subjects participate in meal, exercise, sleep activities alone or in combination with stressful stimuli. |
Who may qualify
- Ages
- 18 to 60 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult
- Study population
- Men and Women with Type 1 Diabetes
Key inclusion criteria (3 listed)
- Men and Women with T1DM
- 18-60 years of age
- Insulin pump user
Key exclusion criteria (8 listed)
- Metabolic instability as evidenced by hospitalizations for diabetes or other diabetes-related complications (e.g., diabetic ketoacidosis and hypoglycemic seizures) within the preceding three months;
- Severe macrovascular disease, as evidenced by severe peripheral artery disease; history of myocardial infarction, heart failure, thromboembolic disease, or unstable angina; uncontrolled hypertension; abnormal resting EKG;
- Maximal exercise stress test with significant brady/tachy arrhythmia, ectopic beats, bundle branch block, or signs of acute ischemia;
- Severe microvascular disease as evidenced by history of vision-threatening proliferative or non-proliferative retinal disease; kidney disease;
- Any uncontrolled non-musculoskeletal condition that would limit the subject's ability to participate in the exercise program (e.g., chronic obstructive airways disease);
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Measurement of Glucose Concentration
Time frame: 3.5 years
• Glucose concentration (mg/dl) will be measured by: Continuous Glucose Monitor (DEXCOM [US G5 PLATINUM/G6]
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 1 Apr 2022.
- Background: PubMed 26087510Turksoy K, Samadi S, Feng J, Littlejohn E, Quinn L, Cinar A. Meal Detection in Patients With Type 1 Diabetes: A New Module for the Multivariable Adaptive Artificial Pancreas Control System. IEEE J Biomed Health Inform. 2016 Jan;20(1):47-54. doi: 10.1109/JBHI.2015.2446413. Epub 2015 Jun 16.
- Background: PubMed 22865931Eren-Oruklu M, Cinar A, Rollins DK, Quinn L. Adaptive System Identification for Estimating Future Glucose Concentrations and Hypoglycemia Alarms. Automatica (Oxf). 2012 Aug;48(8):1892-1897. doi: 10.1016/j.automatica.2012.05.076. Epub 2012 Jun 22.
- Background: PubMed 24187436Turksoy K, Bayrak ES, Quinn L, Littlejohn E, Rollins D, Cinar A. Hypoglycemia Early Alarm Systems Based On Multivariable Models. Ind Eng Chem Res. 2013 Sep 4;52(35):12329-36. doi: 10.1021/ie3034015.
- Background: PubMed 23439179Bayrak ES, Turksoy K, Cinar A, Quinn L, Littlejohn E, Rollins D. Hypoglycemia early alarm systems based on recursive autoregressive partial least squares models. J Diabetes Sci Technol. 2013 Jan 1;7(1):206-14. doi: 10.1177/193229681300700126.
- Background: PubMed 26930674Turksoy K, Roy A, Cinar A. Real-Time Model-Based Fault Detection of Continuous Glucose Sensor Measurements. IEEE Trans Biomed Eng. 2017 Jul;64(7):1437-1445. doi: 10.1109/TBME.2016.2535412. Epub 2016 Feb 25.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Ali Cinar, PhD principal investigator
Illinois Institute of Technoloy
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Type1 Diabetes Mellitus, run by University of Illinois Chicago at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 8 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 1 Apr 2022. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Measurement of Glucose Concentration (time frame: 3.5 years). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04725799, which also lists 5 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 1 Apr 2022.