Application of portable wearable devices combined with exercise management platform in patients with type 2 diabetes mellitus
Bibliographic record
Abstract
Objective To explore the application effect of portable wearable device (including muscle oxygen monitor, heart rate armband combined with mobile APP) and exercise management platform in patients with type 2 diabetes mellitus (T2DM). Methods A total of 66 patients with T2DM were recruited from Department of Endocrinology of the First Affiliated Hospital, Henan University of Science and Technology between May 2017 and June 2018, and randomly divided into the test group (34 cases) and the control group (32 cases). Patients in the test group received portable wearable devices and sport management platform, and the controls received routine sport education. Levels of plasma glucose and lipid, muscle oxygen and heart rate before and after management were compared between these two groups. The t test and chi-square analysis were used for comparison between groups. Results After management, levels of glycated hemoglobin A1c (HbA1c) and fasting plasma glucose (FPG) in the test group were lower than those in the control group [(7.34±1.61)% vs (6.17±0.53)%, (8.17±2.48) vs (6.30±1.19) mmol/L, respectively; t=-3.248, -3.644, both P<0.05]. The maximum heart rate and the maximum exercise intensity were both higher than those in the control group [(139.00±16.28) vs (129.84±13.00) times/min and 0.80±0.08 vs 0.75±0.05, respectively; t=-2.400, -2.639, both P<0.05]. By increasing speed at 4 min×4 stage of treadmill, the average muscle oxygen ratio and the decrease of muscle oxygen ratio in the test group were both better than those in the control group [(54.79±14.12)% vs (58.00±14.14)%, and (24.56±19.58)% vs (19.03±15.68)%, respectively; t=-4.541, -2.563, both P<0.05]. Conclusion Intervention combined the portable wearable devices with the sport platform can optimize the exercise management and help to control blood glucose and improve muscle oxygen ratio in patients with T2DM. Key words: Diabetes mellitus, type 2; Sport management platform; Portable wearable devices
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".