CLIAMS:1. A method for monitoring a physiological parameter associated with a subject using a hand held device (100), the method comprising:
obtaining a plurality of sample photoplethysmographic (PPG) features associated with a sample subject, from a video of a body part (128) of the sample subject;
selecting, from among the plurality of sample PPG features, at least one relevant sample PPG feature associated with the physiological parameter, based on a ground truth value of the physiological parameter for the subject; and
determining, based on the at least one relevant sample PPG feature and the ground truth value of the physiological parameter, a mathematical model indicative of a correlation between the relevant sample PPG feature and the physiological parameter, wherein the mathematical model is deployed for monitoring the physiological parameter in real time.
2. The method as claimed in claim 1, wherein the obtaining the plurality of PPG features comprises extracting the plurality of PPG features from the video in one of a time domain and a frequency domain.
3. The method as claimed in claim 1, wherein the physiological parameter comprises at least one of a blood pressure, an electrocardiograph (ECG) indicative of heart condition, and a respiration rate.
4. The method as claimed in claim 1, wherein the PPG sample features comprise a set of at least one of time domain features and frequency domain features.
5. The method as claimed in claim 1, wherein the PPG sample features comprise physical characteristics associated with the sample subject.
6. The method as claimed in claim 5, wherein the physical characteristics include height of the sample subject, weight of the sample subject, and age of the sample subject.
7. The method as claimed in claim 1, wherein the determining the mathematical model is based on a supervised learning technique.
8. The method as claimed in claim 1, further comprising:
obtaining test PPG features associated with a test subject from a video of a body part (134) of the test subject; and
monitoring the physiological parameter for the test subject, based on the test PPG features and the mathematical model.
9. The method as claimed in claim 1, wherein the selecting comprises:
determining a relevance rating for each of the plurality of sample PPG features, wherein the relevance rating is indicative of a relation of each of the plurality of sample PPG feature with the physiological parameter; and
ascertaining the at least one relevant sample PPG feature from among the plurality of sample PPG features, based on the relevance rating of each of the plurality of sample PPG features and a threshold relevance rating.
10. A method for monitoring a physiological parameter associated with a subject using a hand held device (100), the method comprising:
obtaining a plurality of sample photoplethysmographic (PPG) features associated with a sample subject, from a video of a body part (128) of the sample subject;
selecting, from among the plurality of sample PPG features, at least one relevant sample PPG feature associated with the physiological parameter, based on a ground truth value of the physiological parameter for the subject; and
determining, based on only the at least one relevant sample PPG feature and the ground truth value of the physiological parameter, a mathematical model indicative of a correlation between the relevant sample PPG feature and the physiological parameter, wherein the mathematical model is deployed for monitoring the physiological parameter in real time, the physiological parameter being at least one of a blood pressure (BP) and electrocardiograph (ECG) features.
11. A modeling system (100) for monitoring physiological parameters associated with a subject, the modeling system (100) comprising:
a processor (102);
a processing module (110) coupled to the processor (102) to obtain a plurality of sample photoplethysmographic (PPG) features associated with a sample subject, wherein the sample PPG features are extracted from a video of a body part (128) of the sample subject;
a feature selection module (112) coupled to the processor (102) to select at least one relevant sample PPG features associated with the physiological parameter, from among the plurality of sample PPG features, based on a ground truth value of the physiological parameter; and
a modeling module (114) coupled to the processor (102) to determine, based on the at least one relevant sample PPG feature and the ground truth value of the physiological parameter, a mathematical model indicative of a correlation between the relevant sample PPG feature and the physiological parameter, wherein the mathematical model is adapted for monitoring the physiological parameter in real time.
12. The modeling system (100) as claimed in claim 11, wherein the processing module (110):
obtains the video of the body part (128) of the subject from a sampling device (126); and
processes the video to determine a sample PPG waveform.
13. The modeling system (100) as claimed in claim 11, wherein the processing module (110) obtains the plurality of PPG features from the video in at least one of a time domain and a frequency domain.
14. The modeling system (100) as claimed in claim 11, wherein the modeling module (114) determines the mathematical model based on supervised learning techniques.
15. The modeling system (100) as claimed in claim 11, wherein the feature selection module (112):
determines a relevance rating for each of the plurality of sample PPG features, wherein the relevance rating is indicative of a relation of each sample PPG feature with the physiological parameter; and
compares the relevance rating of each of the plurality of sample PPG features with a threshold relevance rating to select the at least one relevant sample PPG feature.
16. A physiological parameter monitoring device (132) for monitoring physiological parameters associated with a subject, the physiological parameter monitoring device (132) comprising:
a processor;
a monitoring module (140) coupled to the processor to,
obtain a mathematical model indicative of a correlation between relevant sample PPG feature and the physiological parameter to be monitored, wherein the relevant sample PPG features are selected from among a plurality of sample PPG features based on influence of the physiological parameter on the plurality of sample PPG features;
ascertain test PPG features associated with a test subject from a video of a body part (134) of the test subject, the video being captured using a camera (136) of the physiological parameter monitoring device (132); and
monitor the physiological parameter for the test subject, based on the test PPG features and the mathematical model.
17. A non-transitory computer readable medium having a set of computer readable instructions that, when executed, cause a modeling system (100) to:
obtain a plurality of sample photoplethysmographic (PPG) features associated with a sample subject, from a video of a body part (128) of the sample subject;
select, from among the plurality of sample PPG features, at least one relevant sample PPG feature associated with the physiological parameter, based on a ground truth value of the physiological parameter for the subject; and
determine, based on the at least one relevant sample PPG feature and the ground truth value of the physiological parameter, a mathematical model indicative of a correlation between the relevant sample PPG feature and the physiological parameter,

wherein the mathematical model is adapted for monitoring the physiological parameter in real time. ,TagSPECI:As Attached