top of page

Clinical Research &
Development

Know Labs is progressing on the path to FDA submission for clearance as a medical device. As we prioritize external validation of our technology and transparency in our progress, we are continuously adding to a growing body of evidence. 

March 6, 2024

Clinical study among people with prediabetes and T2 diabetes using venous blood as comparative reference.

Clinical study among people with prediabetes and T2 diabetes using venous blood as comparative reference.

A study titled, “Non-Invasive Blood Glucose Monitoring in People with Diabetes Using an RF Sensor and Venous Blood Comparator,” assesses the accuracy of the novel Know Labs radiofrequency (RF) dielectric sensor for non-invasive blood glucose measurement in participants with prediabetes and Type 2 diabetes using venous blood as comparative reference. Results were presented as e-Poster at the 17th International Conference on Advanced Technologies and Treatments for Diabetes.

Klyve D, Anderson JH, Currie K, Ward C, Pandya K, Somers V.  Published March 6, 2024. Non-Invasive Blood Glucose Monitoring in People with Diabetes Using an RF Sensor and Venous Blood Comparator. The 17th International Conference on Advanced Technologies and Treatments for Diabetes, Florence, IT.

July 26, 2023

Novel Data Preprocessing Techniques in an Expanded Dataset Improve Machine Learning Model Accuracy

Novel Data Preprocessing Techniques in an Expanded Dataset Improve Machine Learning Model Accuracy

A study titled, “Novel Data Preprocessing Techniques in an Expanded Dataset Improve Machine Learning Model Accuracy for a Non-Invasive Blood Glucose Monitor,” validates the stability of a machine learning model on an expanded dataset.

Klyve D, Pandya K, Ward C, Shelton B. Novel Data Preprocessing Techniques in an Expanded Dataset Improve Machine Learning Model Accuracy for a Non-Invasive Blood Glucose Monitor. Published online July 26, 2023

May 30, 2023

Algorithm Refinement In The Non-Invasive Detection of Blood Glucose

Algorithm Refinement In The Non-Invasive Detection of Blood Glucose

A study titled, “Algorithm Refinement in the Non-Invasive Detection of Blood Glucose Using Know Labs' Bio-RFID Technology,” demonstrates an ML model and other data science techniques improved the accuracy of Bio-RFID for predicting blood glucose, using the Dexcom G6® as reference device.

Peer Reviewed By: Members of Know Labs' Scientific Advisory Board

Klyve D, Currie K, Anderson JH, Ward C, Schwarz D, Shelton B. Algorithm Refinement in the Non-Invasive Detection of Blood Glucose via Bio-RFIDTM Technology. Published online July 6, 2023:2023.05.25.23290539. doi:10.1101/2023.05.25.23290539

May 5, 2023

Technical Feasibility Clinical Study

Technical Feasibility Clinical Study

A study titled, “Technical Feasibility of a Novel Sensor for Non-Invasive Blood Glucose Monitoring Compared to Dexcom G6®,” demonstrates that the Bio-RFID sensor can deliver stable, repeatable results in predicting blood glucose concentrations using the Dexcom G6® as a reference device. Results were presented at American Association of Clinical Endocrinology (AACE) 2023 Annual Meeting.

Klyve D, Shelton B, Ward C, Schwarz D, Anderson JH, Kent S. Published May 5, 2023. Technical Feasibility of a Novel Sensor for Non-Invasive Blood Glucose Monitoring Compared to Dexcom G6®. American Association of Clinical Endocrinology, Seattle, WA.

April 21, 2023

Proof of Principle Study in Collaboration with Mayo Clinic

Proof of Principle Study in Collaboration with Mayo Clinic

A study titled, “Detecting Unique Analyte-Specific Radio Frequency Spectral Responses in Liquid Solutions – Implications for Non-Invasive Physiologic Monitoring,” was conducted in collaboration with Mayo Clinic and demonstrates the accuracy of Know Labs’ non-invasive Bio-RFID technology in quantifying different analytes in vitro. Results were presented at the American Physiological Society 2023 Summit.

Klyve D, Anderson JH, Lorentz G, Somers VK. Detecting Unique Analyte-Specific Radio Frequency Spectral Responses in Liquid Solutions—Implications for Non-Invasive Physiologic Monitoring. Sensors. 2023;23(10):4817. doi:10.3390/s23104817

February 28, 2023

Proof of Concept Clinical Study

Proof of Concept Clinical Study

This technical report titled, "Non-Invasive Blood Glucose Monitoring: A Validation of a Novel Sensor Compared to a Dexcom G6®," presents proof of concept for a new method to quantify blood glucose levels (BGL) in vivo non-invasively using RF methods by means of training a model to predict readings of the Dexcom G6®, as a proxy for BGL. The method uses a new type of sensing device that rapidly scans a wide band of RF frequencies. The report outlines data science techniques used to train a neural network model to make predictions, and includes metrics of model success and future directions of this work.

Peer Reviewed By: Members of Know Labs' Scientific Advisory Board

Klyve D, Shelton B, Lowe S, Ward C, Schwarz D, Kent S. Non-Invasive Blood Glucose Monitoring: A Validation of a Novel Sensor Compared to a Dexcom G6. Published online February 28, 2023.

December 22, 2023

Proof of Concept Blood Oxygen Saturation

Proof of Concept Blood Oxygen Saturation

This exploratory study was ongoing, in parallel to blood glucose clinical research, and provided a proof-of-concept that Know Labs’ technology has the potential to accurately identify and monitor blood oxygen saturation levels.

October 6, 2021

Exploratory Clinical Study

Exploratory Clinical Study

This exploratory study was conducted in August 2021 and provided the first indication that Know Labs’ technology could be an accurate, cost-effective, and non-invasive alternative to the current FDA-cleared glucose monitoring devices on the market.

KNOWLABS_GEN_2_MARKETING_RENDERING_TOPSIDE

Development Progress

Ongoing clinical research is advancing the testing of our technology
as we continue to refine our device and algorithms. 

The KnowU

TM

February '24

Gen 1 Prototype

June '23

Internal Clinical Trial

September '22

Expected Path To Market

Expected PTM.png
Generation 1 Prototype

Generation 1 Prototype