System and method of measuring and estimating human health parameters

1 . A system for measuring health parameters with context-adaptive sensor fusion, the system comprising:

two or more sensing modules for capturing values of two or more sensed measurements associated with a user;

a memory storing multiple sets of weightages, wherein each set of weightages corresponds to a different context selected from: time of day, user characteristics, presence of motion artifacts, or measurement reliability conditions; and

a processor configured to:

(a) determine a current context based on one or more contextual parameters;

(b) select from the memory a set of weightages corresponding to the determined current context;

(c) assign the selected weightages to the values of the two or more sensed measurements; and

(d) determine a value of a health parameter using a weighted average of the values with the assigned weightages.

2 . The system of claim 1 , wherein the different contexts include different times of day, and wherein the processor assigns different weightages for morning measurements compared to evening measurements based on sensor reliability variations throughout the day.

3 . The system of claim 1 , wherein the processor is configured to:

detect presence of motion artifacts during measurement; and

select a set of weightages that reduces impact of sensing modules susceptible to motion artifacts when motion artifacts are detected.

4 . The system of claim 1 , wherein the user characteristics include weight management conditions, and wherein the processor selects weightages that prioritize more reliable sensing modules when the user has weight management conditions.

5 . The system of claim 1 , wherein the system is configured for multi-user operation, and wherein the processor stores context-specific weightages separately for each user of a plurality of users.

6 . The system of claim 1 , wherein the measurement reliability conditions include determination of signal quality from each sensing module, and wherein the processor dynamically adjusts weightages based on real-time assessment of signal quality during measurement.

7 . A system for measuring health parameters with adaptive measurement pathways, the system comprising:

two or more sensing modules;

a memory storing a database comprising:

(a) identification of multiple sets of sensing modules, wherein each set is capable of measuring a same health parameter through different measurement methods; and

(b) accuracy and reliability information for each set of sensing modules;

a processor configured to:

(c) determine availability status of the two or more sensing modules;

(d) identify available sets of sensing modules from the database;

(e) provide to a user options for measuring the health parameter using the available sets along with the accuracy and reliability information; and

(f) capture values and determine the health parameter using a user-selected set of sensing modules.

8 . The system of claim 7 , wherein the multiple sets of sensing modules include:

a first set comprising an ECG sensing module for measuring heart rate; and

a second set comprising a PPG sensing module for measuring heart rate;

wherein the database stores different accuracy ratings for the first set and the second set.

9 . The system of claim 7 , wherein the multiple sets of sensing modules for measuring blood pressure include:

a first set comprising a cuff-based oscillometric blood pressure sensing module;

a second set comprising a PPG-based sensing module requiring user-specific calibration; and

a third set comprising a cuff-based blood pressure sensing module synchronized with a digital auscultation sensing module for detecting Korotkoff sounds.

10 . The system of claim 7 , wherein the processor is further configured to:

notify the user when a preferred set of sensing modules with higher accuracy is unavailable due to a missing sensing module or sub-component; and

recommend attachment of the missing sensing module or sub-component.

11 . The system of claim 7 , wherein at least one sensing module of the two or more sensing modules includes a detachable sub-component, and wherein the processor is configured to:

detect attachment status of the detachable sub-component; and

update the availability status based on whether the detachable sub-component is attached.

12 . The system of claim 7 wherein the processor is further configured to:

determine that a first set of sensing modules requires calibration using a second set of sensing modules before the first set can be used; and

guide the user to perform calibration measurement using the second set before enabling measurement using the first set.

13 . A system for measuring health parameters through synchronized sensor operation, the system comprising:

two or more sensing modules for capturing values of two or more sensed measurements associated with a user;

a processor configured to:

(a) determine that measurement of a health parameter requires synchronized operation of the two or more sensing modules;

(b) initiate simultaneous capture of the values by operating the two or more sensing modules in temporal synchronization;

(c) maintain temporal alignment of the captured values; and

(d) determine the health parameter by analyzing timing relationships between the temporally synchronized values.

14 . The system of claim 13 , wherein:

the two or more sensing modules comprise an ECG sensing module and a PPG sensing module; and

the processor determines pulse arrival time (PAT) or pulse transit time (PTT) by analyzing timing differences between synchronized ECG waveform and PPG waveform measurements.

15 . The system of claim 13 , wherein:

the two or more sensing modules comprise a cuff-based blood pressure sensing module and a digital auscultation sensing module; and

the processor determines systolic and diastolic blood pressure by synchronizing cuff pressure measurements with detection of Korotkoff sounds from the digital auscultation sensing module.

16 . The system of claim 13 , wherein the processor is configured to:

detect when the two or more sensing modules have lost temporal synchronization during measurement; and

automatically restart the measurement process when loss of synchronization is detected.

17 . The system of claim 13 , wherein the processor is configured to derive multiple different health parameters from a single synchronized measurement session, including at least two of: pulse arrival time, pulse transit time, heart rate variability, or blood pressure estimates.

18 . A method for measuring health parameters, comprising:

determining, by a processor, availability of two or more sensing modules required to capture values of two or more sensed measurements associated with a user;

capturing, by the two or more sensing modules, the values of the two or more sensed measurements associated with the health of the user; and

determining, by the processor, a value of a health parameter by processing the values of the two or more sensed measurements obtained from the two or more sensing modules;

storing, in a memory, user-specific calibration data for a plurality of users wherein the system is configured for multi-user operation; and

determining, by the processor, when calibration is required for the user based on one or more of: absence of calibration data for the user, lapse of a predetermined period since last calibration for the user, or deviation of measured values from expected values for the user.

19 . The method of claim 18 , further comprising:

determining a current context based on one or more of: time of day, user characteristics, or presence of motion artifacts;

selecting a set of weightages from multiple stored sets based on the determined current context;

assigning the selected weightages to the values of the two or more sensed measurements; and

determining the value of the health parameter as a weighted average using the assigned weightages.

20 . The method of claim 18 , wherein determining when calibration is required further comprises:

using an output of a first sensing module of the two or more sensing modules to generate calibration data for a second sensing module of the two or more sensing modules; and

storing the calibration data in association with the user in the memory.