17490714. APPARATUS AND METHOD FOR ESTIMATING LIPID CONCENTRATION simplified abstract (SAMSUNG ELECTRONICS CO., LTD.)

APPARATUS AND METHOD FOR ESTIMATING LIPID CONCENTRATION

Organization Name

SAMSUNG ELECTRONICS CO., LTD.

Inventor(s)

Yun S Park of Suwon-si (KR)

Seoung Bum Kim of Seoul (KR)

Yong Joo Kwon of Yongin-si (KR)

Mingu Kwak of Seoul (KR)

Yoon Sang Cho of Seoul (KR)

Chunghyup Mok of Seoul (KR)

Yeol Ho Lee of Uiwang-si (KR)

Joon Hyung Lee of Seongnam-si (KR)

Kee Won Jeong of Seoul (KR)

Jinsoo Bae of Seoul (KR)

APPARATUS AND METHOD FOR ESTIMATING LIPID CONCENTRATION - A simplified explanation of the abstract

This abstract first appeared for US patent application 17490714 titled 'APPARATUS AND METHOD FOR ESTIMATING LIPID CONCENTRATION

Simplified Explanation

The patent application describes an apparatus for estimating lipid concentration in the human body using sensor data and reference lipid concentration measurements.

• The apparatus collects training data by measuring reference lipid concentration through blood samples and capturing sensor data from multiple users over a specific time period.
• The collected sensor data is preprocessed using techniques like moving average and data augmentation.
• The preprocessed sensor data and reference lipid concentration are used to identify relevant variables that are associated with changes in lipid concentration.
• Based on the selected variables, a lipid concentration prediction model is generated by the processor.

Potential Applications

This technology has potential applications in various fields, including:

• Healthcare: The apparatus can be used in medical settings to monitor and estimate lipid concentration in patients, aiding in the diagnosis and management of lipid-related disorders.
• Fitness and wellness: The technology can be utilized in wearable devices or mobile applications to provide real-time feedback on lipid concentration, helping individuals track their health and make informed lifestyle choices.
• Research: The apparatus can be used in scientific studies and clinical trials to gather data on lipid concentration changes in different populations and evaluate the effectiveness of interventions.

Problems Solved

The technology addresses several problems associated with estimating lipid concentration:

• Non-invasive measurement: By utilizing sensor data, the apparatus eliminates the need for invasive blood sampling, providing a more convenient and comfortable method for lipid concentration estimation.
• Real-time monitoring: The ability to continuously collect sensor data allows for real-time monitoring of lipid concentration, enabling prompt intervention and personalized treatment plans.
• Data-driven prediction: The lipid concentration prediction model generated by the apparatus is based on data collected from multiple users, enhancing accuracy and reliability compared to traditional methods.

Benefits

The technology offers several benefits:

• Convenience: Users can estimate their lipid concentration without the need for frequent blood tests, making it more convenient and less intrusive.
• Personalization: The apparatus generates a lipid concentration prediction model based on individual sensor data, allowing for personalized monitoring and intervention strategies.
• Early detection: Continuous monitoring and real-time feedback enable the early detection of abnormal lipid concentration levels, facilitating timely medical intervention and preventive measures.

Original Abstract Submitted

An apparatus for estimating lipid concentration is provided. According to an example embodiment, the apparatus may include a training data collector configured to collect, as training data, a reference lipid concentration measured through blood samples of a plurality of users for a predetermined time period and sensor data obtained through light signals detected from the plurality of users for the predetermined time period and a processor configured to perform preprocessing including a moving average and data augmentation on the obtained sensor data, select a valid variable relevant to a change in lipid concentration based on the preprocessed sensor data and the reference lipid concentration, and generate a lipid concentration prediction model based on the selected valid variable.