Real-time and continuous determination of excess post-exercise oxygen consumption and the estimation of blood lactate
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Publication Number
US-11291392-B2
Publication Date
2022-04-05
Expiration Date
Abstract
The current invention pertains to an apparatus and method for the determination of excess post-exercise oxygen consumption (EPOC) and the estimation of blood lactate levels. While these exercise parameters are traditionally determined using indirect calorimetry and blood sampling, this invention provides a method for the determination of these parameters using heart rate data. A wearable photoplethysmography device for measuring heart rate is included as an exemplary embodiment, however, the method of the current inventions can also be used with heart rate data from any heart rate monitor. In an embodiment of the present invention a supply demand differential equation is used to continuously monitor EPOC in real-time. Furthermore, blood lactate levels can also be estimated as a function of EPOC. Importantly, the process of determining EPOC and blood lactate can be linked to a biomathematical model of human physiology to access additional parameters such as hormonal changes, body composition changes or other physiological fluctuations or transient physiological behavior.
Core Innovation
The invention determines excess post-exercise oxygen consumption (EPOC) and an estimated blood lactate level of an individual using photoplethysmography (PPG) light absorbance data captured by an optical sensor in a wearable device. The PPG light absorbance data is transformed into raw physiological signals, from which physiological parameters are determined, including continuous heart rate, HRmax, HRrest, HR reserve, oxygen consumption, VO2max, VO2rest, VO2 reserve, and exercise intensity.
EPOC is determined by applying a supply-demand differential equation to at least one of the determined physiological parameters. The estimated blood lactate level is calculated as a function of the EPOC. The approach incorporates a biomathematical model of human physiology to calculate additional parameters from the determined EPOC and the estimated blood lactate level, where the biomathematical model comprises biomathematical models of metabolism, body composition change, hormonal changes, or any other biomathematical model that describes a physiological process.
In a system implementation, the wearable device acquires PPG light absorbance data, determines heart rate data and additional physiological parameters from the PPG light absorbance data, applies the supply-demand differential equation to determine EPOC, and calculates the estimated blood lactate level as a function of the determined EPOC. The determined EPOC and the estimated blood lactate level are transmitted to a server, and the server incorporates a biomathematical model of human physiology to calculate additional parameters from the determined EPOC and the estimated blood lactate level.
Claims Coverage
The provided partial content includes three independent claims, a method, a system, and a wearable device. Across these independent claims, the inventive coverage centers on deriving physiological parameters from wearable PPG data, applying a supply-demand differential equation to determine EPOC, calculating estimated blood lactate from EPOC, and incorporating a biomathematical model of human physiology to compute additional parameters.
Wearable PPG capture and parameter determination for EPOC and lactate estimation
Capturing PPG light absorbance data from at least one optical sensor in contact with skin of the individual within a wearable device; transforming the PPG light absorbance data into raw physiological signals; determining physiological parameters including continuous heart rate, HRmax, HRrest, HR reserve, oxygen consumption, VO2max, VO2rest, VO2 reserve, and exercise intensity.
Supply-demand differential equation for EPOC
Applying a supply-demand differential equation to at least one of the determined physiological parameters to determine the EPOC.
EPOC-to-estimated blood lactate calculation
Calculating the estimated blood lactate level as a function of the EPOC.
Biomathematical model incorporation for additional parameters
Incorporating a biomathematical model of human physiology to calculate additional parameters from the determined EPOC and the estimated blood lactate level, wherein the biomathematical model comprises biomathematical models of metabolism, body composition change, hormonal changes, or any other biomathematical model that describes a physiological process.
Server wearable system for EPOC and lactate using PPG with biomathematical model
A system comprising a server and a wearable device where the wearable device collects PPG light absorbance data via at least one optical sensor, determines heart rate data including continuous HR, HRmax, HRrest, determines additional physiological parameters including HR reserve and VO2 reserve, calculates exercise intensity, applies a supply-demand differential equation to determine EPOC, calculates the estimated blood lactate level as a function of the determined EPOC, transmits the determined EPOC and the estimated blood lactate level to the server, and the server incorporates a biomathematical model of human physiology to calculate additional parameters from the determined EPOC and the estimated blood lactate level.
Wearable device architecture for EPOC and lactate with biomathematical model
A wearable device comprising at least one optical sensor configured to capture PPG light absorbance data when in contact with the individual's skin and a processor configured to generate raw physiological signals from the PPG light absorbance data; determine the individual's heart rate; determine physiological parameters including HR reserve and oxygen consumption reserve; calculate percentage VO2max and exercise intensity; apply a supply-demand differential equation to determine EPOC and calculate the estimated blood lactate level as a function of EPOC; and incorporate a biomathematical model of human physiology to calculate additional parameters from the determined EPOC and the determined heart rate.
Across the independent method, system, and wearable-device claims, the core inventive combination is to derive physiological parameters from wearable PPG light absorbance data, determine EPOC using a supply-demand differential equation, compute an estimated blood lactate level as a function of EPOC, and incorporate a biomathematical model of human physiology to calculate additional parameters.
Stated Advantages
Determines excess post-exercise oxygen consumption (EPOC) from PPG light absorbance data captured by a wearable optical sensor.
Calculates an estimated blood lactate level as a function of the determined EPOC.
Calculates additional parameters by incorporating a biomathematical model of human physiology including metabolism, body composition change, and hormonal changes.
Documented Applications
A system implementation where the wearable device transmits the determined EPOC and the estimated blood lactate level to a server for incorporation of a biomathematical model to calculate additional parameters.
A wearable-device implementation where the wearable device itself generates raw physiological signals, determines heart rate and physiological parameters, applies the supply-demand differential equation to determine EPOC, calculates estimated blood lactate, and incorporates the biomathematical model to calculate additional parameters.
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