Google llc (20240090827). Methods and Systems for Improving Measurement of Sleep Data by Classifying Users Based on Sleeper Type simplified abstract

Methods and Systems for Improving Measurement of Sleep Data by Classifying Users Based on Sleeper Type

Organization Name

google llc

Inventor(s)

Alexander Statan of Berkeley CA (US)

Sarah Ann Stokes Kernasovskiy of San Francisco CA (US)

Alexandros Antonios Pantelopoulos of El Cerrito CA (US)

Conor Joseph Heneghan of Campbell CA (US)

Methods and Systems for Improving Measurement of Sleep Data by Classifying Users Based on Sleeper Type - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240090827 titled 'Methods and Systems for Improving Measurement of Sleep Data by Classifying Users Based on Sleeper Type

Simplified Explanation

The present disclosure is directed towards systems and methods for improving analysis of sleep data by classifying users based on sleeper type. In particular, a wearable computing system can obtain a first set of motion sensor data from the motion sensor for a user during a first period. The wearable computing system can determine a sleeper type from a plurality of sleeper types for the user based on the first set of motion sensor data received from the motion sensor. The wearable computing system can select a sleep analysis model from a plurality of sleep analysis models based on the sleeper type determined for the user. The wearable computing system can use the selected sleep analysis model to analyze a second set of motion sensor data from a second period to determine one or more sleep characteristics for the user during the second period.

• Wearable computing system classifies users based on sleeper type
• Obtains motion sensor data to determine sleeper type and select appropriate sleep analysis model
• Analyzes motion sensor data to determine sleep characteristics for the user

Potential Applications

This technology can be applied in:

• Sleep tracking devices
• Health monitoring systems
• Fitness trackers

Problems Solved

• Improved accuracy in analyzing sleep data
• Personalized sleep analysis based on sleeper type
• Enhanced understanding of sleep patterns

Benefits

• Customized sleep analysis for users
• Better insights into sleep quality
• Potential for improved overall health and well-being

Potential Commercial Applications

Optimizing sleep tracking devices for:

• Consumer market
• Healthcare industry
• Fitness and wellness sector

Possible Prior Art

One possible prior art could be traditional sleep tracking devices that do not classify users based on sleeper type before analyzing sleep data.

Unanswered Questions

How does the wearable computing system determine the sleeper type from the motion sensor data?

The abstract does not provide specific details on the methodology used to classify users based on sleeper type.

What are the specific sleep characteristics that can be determined by the wearable computing system?

The abstract mentions determining one or more sleep characteristics, but it does not specify what these characteristics are.

Original Abstract Submitted

the present disclosure is directed towards systems and methods for improving analysis of sleep data by classifying users based on sleeper type. in particular, a wearable computing system can obtain a first set of motion sensor data from the motion sensor for a user during a first period. the wearable computing system can determine a sleeper type from a plurality of sleeper types for the user based on the first set of motion sensor data received from the motion sensor. the wearable computing system can select a sleep analysis model from a plurality of sleep analysis models based on the sleeper type determined for the user. the wearable computing system can use the selected sleep analysis model to analyze a second set of motion sensor data from a second period to determine one or more sleep characteristics for the user during the second period.