Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
July 6, 2023

Real-time Non-invasive Blood Glucose Monitoring using Advanced Machine Learning Techniques

View Full Paper
Ask AI
Bookmark
Share

Key result

Proposed hybrid AI model detects diabetes using continuous vitals from smartwatch sensors.

Why the study?

Early detection of diabetes can reduce complications, and wearable technology like smartwatches with bioactive sensors offers potential for continuous non-invasive screening.

Does a hybrid AI model using smartwatch data accurately detect diabetes?

Comparison

Hybrid AI model vs standard methods for classifying diabetes status

Design

Machine learning model development study

Authors

LML Jenitha MaryVVV. VijayashanthiMPM. Parameswari

Discussion

Loading...

Member takes

Implication

Supports wearable-based diabetes screening feasibility; leaves open prospective validation before clinical adoption.

Structured PICO

Does a hybrid AI model using smartwatch data accurately detect diabetes?

P
Population
Patients with or without diabetes (no specific sample size or demographics provided)
I
Intervention
Hybrid AI model combining deep learning and traditional AI using smartwatch data (skin conductance, circulatory strain, pulse)
O
Outcome
Accuracy of diabetes detection/localization

A proposed hybrid AI model using smartwatch-derived vital signs may offer a non-invasive method for continuous diabetes screening.

Cite This Study

Mary et al. (2023) studied Diabetes. Hybrid AI model using smartwatch bioactive sensor data was evaluated on Diabetes detection. A proposed hybrid AI model combines deep learning and traditional AI to detect diabetes using continuous bodily vitals collected from smartwatch bioactive sensors.

synapsesocial.com/papers/6a16586086504b844dd97033https://doi.org/10.1109/icesc57686.2023.10193483
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1A Noninvasive Blood Glucose Monitoring System Based on Smartphone PPG Signal Processing and Machine Learning2020 · 182 citations
  2. 2Machine learning algorithms for Diabetes prediction and neural network method for blood glucose measurement2021 · 38 citations
  3. 3Novel Wearable Optical Sensors for Vital Health Monitoring Systems—A Review2023 · 148 citations
  4. 4Novel Approach to Non-Invasive Blood Glucose Monitoring Based on Transmittance and Refraction of Visible Laser Light2017 · 87 citations
  5. 5Chinese diabetes datasets for data-driven machine learning2023 · 84 citations