17985098. IDENTIFYING POOR CARDIORESPIRATORY FITNESS USING SENSORS OF WEARABLE DEVICES simplified abstract (Apple Inc.)

IDENTIFYING POOR CARDIORESPIRATORY FITNESS USING SENSORS OF WEARABLE DEVICES

Organization Name

Apple Inc.

Inventor(s)

Katherine Niehaus of San Francisco CA (US)

Britni A. Crocker of Santa Cruz CA (US)

Maxsim L. Gibiansky of Sunnyvale CA (US)

William R. Powers, Iii of San Francisco CA (US)

Allison L. Gilmore of Redwood City CA (US)

Asif Khalak of Belmont CA (US)

Sheena Sharma of Carbondale IL (US)

Richard A. Fineman of Campbell CA (US)

Kyle A. Reed of Carmel IN (US)

Karthik Jayaraman Raghuram of Foster City CA (US)

Adeeti V. Ullal of Emerald Hills CA (US)

IDENTIFYING POOR CARDIORESPIRATORY FITNESS USING SENSORS OF WEARABLE DEVICES - A simplified explanation of the abstract

This abstract first appeared for US patent application 17985098 titled 'IDENTIFYING POOR CARDIORESPIRATORY FITNESS USING SENSORS OF WEARABLE DEVICES

Simplified Explanation

The patent application describes a method for identifying poor cardio metabolic health using sensors in wearable devices. The method includes obtaining estimates of maximal oxygen consumption during exercise, adjusting the estimates using confidence weights based on context data, and aggregating the adjusted estimates to generate a summary estimate and confidence interval for the user's cardiorespiratory fitness. The user's fitness level is then classified based on the summary estimate, confidence interval, population error model, or a low fitness threshold.

• Method for identifying poor cardio metabolic health using wearable devices
• Estimates maximal oxygen consumption during exercise
• Adjusts estimates using confidence weights based on context data
• Aggregates adjusted estimates to generate a summary estimate and confidence interval
• Classifies user's cardiorespiratory fitness based on summary estimate, confidence interval, population error model, or low fitness threshold

Potential Applications

• Personal fitness tracking and monitoring
• Healthcare and wellness applications
• Remote patient monitoring
• Fitness and health coaching

Problems Solved

• Provides a non-invasive and convenient method for assessing cardiorespiratory fitness
• Enables early identification of poor cardio metabolic health
• Allows for personalized fitness and health recommendations

Benefits

• Enables individuals to track and improve their cardiorespiratory fitness
• Facilitates early intervention and prevention of cardiovascular diseases
• Provides valuable data for healthcare professionals to monitor and manage patients' health
• Promotes a healthier lifestyle and overall well-being

Original Abstract Submitted

Embodiments are disclosed for identifying poor cardio metabolic health using sensors of wearable devices. In an embodiment, a method comprises: obtaining estimates of maximal oxygen consumption of a user during exercise; determining at least one confidence weight based on context data; adjusting the maximal oxygen consumption estimates using the at least one confidence weight; aggregating the adjusted maximal oxygen consumption estimates to generate a summary maximal oxygen consumption estimate and corresponding confidence interval for the user; and classifying cardiorespiratory fitness of the user based on at least one of the summary maximum consumption estimate, the corresponding confidence interval, a population error model or a low cardiorespiratory fitness threshold.