Abstract: This disclosure relates generally to stress classification and quantification, and more particularly to system and method for classification and quantitative estimation of cognitive stress from analysis of keystrokes and signals derived from physiological sensors. In one embodiment, a method includes obtaining, while a user is engaged in performance of a task, physiological signals from physiological sensors accessible to the user. Feature sets are identified from the physiological signals which correlate with cognitive stress experienced by the user. Using a regression model, a stress indicator metric comprising a quantitative estimate of the cognitive stress is predicted. The regression model is trained using the feature sets and independently determined quantitative estimates of cognitive stress used as a ground truth to output the value of the stress indicator metric.

Abstract: This disclosure relates generally to PPG signal quality assessment, and more particularly to, a system and method for sensor agnostic PPG signal quality assessment using morphological analysis. In one embodiment, a method for PPG signal quality assessment includes obtaining a PPG signal captured using a testing device in real-time, and segmenting into a first plurality of PPG signal samples such that length of each of the first plurality of PPG signal samples more than a threshold length. A signal sufficiency check (SSC) is performed for each first PPG signal sample to obtain at least a first set of PPG signal samples complying with the SSC. A set of features is extracted from the first set of PPG signal samples, based on which each PPG signal sample is identified as one of a noisy and clean signal sample using a plurality of Random Forest (RF) models created during the training phase.

Abstract: Current technologies analyze electrocardiogram (ECG) signals for a long duration, which is not always a practical scenario. Moreover the current scenarios perform a binary classification between normal and Atrial Fibrillation (AF) only, whereas there are many abnormal rhythms apart from AF. Conventional systems/methods have their own limitations and may tend to misclassify ECG signals, thereby resulting in an unbalanced multi-label classification problem.

Abstract: A system and method for estimating blood pressure (BP) using photoplethysmogram (PPG) has been explained. The PPG is captured from a PPG sensor (102). For preparing training model, a pulse oximeter is used for capturing PPG. For testing, a smartphone camera is used for capturing the PPG signal. A plurality of features are extracted from the preprocessed PPG signal. A BP distribution is then generated using the plurality of features and the training model. The BP distribution is part of a set of BP distributions generated from different subjects.

Abstract: A system and method for classifying the phonocardiogram (PCG) signal quality has been described. The system is configured to identify the quality of the PCG signal recording and accepting only diagnosable quality recordings for further cardiac analysis. The system includes the derivation of plurality features of the PCG signal from the training dataset. The extracted features are preprocessed and are then ranked using mRMR algorithm. Based on the ranking the irrelevant and redundant features are rejected if their mRMR strength is less. A training model is generated using the relevant set of features. The PCG signal of the person under test is captured using a digital stethoscope and a smartphone. The PCG signal is preprocessed and only the relevant set of features are extracted. And finally the PCG signal is classified into diagnosable or non-diagnosable using the relevant set of features and a random forest classifier.

Abstract: Identification of pulmonary diseases involves accurate auscultation as well as elaborate and expensive pulmonary function tests. Also, there is a dependency on a reference signal from a flowmeter or need for labelled respiratory phases. The present disclosure provides extraction of frequency and time-frequency domain lung sound features such as spectral and spectrogram features respectively that enable classification of healthy and abnormal lung sounds without the dependencies of prior art. Furthermore extraction of wavelet and cepstral features improves accuracy of classification. The lung sound signals are pre-processed prior to feature extraction to eliminate heart sounds and reduce computational requirements while ensuring that information providing adequate discrimination between healthy and abnormal lung sounds is not lost.

Abstract: A method and system for blood pressure (BP) estimation of a person is provided. The system is estimating pulse transit time (PTT) using the ECG signal and PPG signal of the person. A plurality of features are extracted from the PPG. The plurality of PPG features and the PTT are provided as inputs to an automated feature selection algorithm. This algorithm selects a set of features suitable for BP estimation. The selected features are fed to a classifier to classify the database into low/normal BP range and a high BP range. The correctly classified normal BP data are then used to create a regression model to predict BP from the selected features. The current methodology uses automated feature selection mechanism and also employs a block to reject extreme BP data. Thus the available accuracy in predicting BP is expected to be more than the existing BP estimation methods.

Abstract: A method and system for detection of coronary artery disease (CAD) in a person using a fusion approach has been described. The invention the detection of CAD in the person by capturing of a plurality of physiological signals such as phonocardiogram (PCG), photoplethysmograph (PPG), ECG, galvanic skin response (GSR) etc. from the person. A plurality of features are extracted from the physiological signals. The person is then classified as CAD or normal using the each of the features independently. The classification is done based on supervised machine learning technique. The output of the classification is then fused and used for the detection of the CAD in the person using a predefined criteria.

Abstract: A physiological parameter measurement device comprising a processor and a video processing module coupled to the processor to divide each of a plurality of frames of a video into a plurality of blocks, where the video is of a body part of a subject whose physiological parameter is to be determined. The video processing module further is to select a block having highest peak signal to noise ratio (PSNR) from amongst the plurality of blocks. Further, the video processing module is to extract a photoplethysmogram (PPG) signal from the video based on a block identifier associated with the block. The physiological parameter measurement device further comprises a signal enhancement module coupled to the processor, to process the PPG signal to obtain an enhanced PPG signal for determining a value of the physiological parameter for the subject.

Abstract: A method for monitoring physiological parameters associated with a subject using a hand held device is described herein. In an implementation, the method includes obtaining a plurality of sample photoplethysmographic (PPG) features associated with a sample subject, from a video of a body part of the sample subject. From among the plurality of sample PPG features, at least one relevant sample PPG feature associated with the physiological parameter, is selected based on a ground truth value of the physiological parameter for the subject. Further, 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, is determined. The mathematical model can be deployed for monitoring the physiological parameter in real time.

Abstract: A method and system is provided for noise cleaning of photoplethysmogram signals. The method and system is disclosed for noise cleaning of photoplethysmogram signals for estimating blood pressure of a user; wherein photoplethysmogram signals are extracting from the user; the extracted photoplethysmogram signals are up sampled; the up sampled photoplethysmogram signals are filtered; uneven baseline drift of each cycle is removed from the up sampled and filtered photoplethysmogram signals; outlier cycles of the photoplethysmogram signals are removed and remaining cycles of the photoplethysmogram signals are modeled; and time domain features are extracted from originally extracted and modeled photoplethysmogram signals for estimating blood pressure of the user.

Abstract: An indoor positioning system and method of localizing a person/object in an indoor environment by identifying the orientation and direction of a person/object to provide a true location of the person/object without navigation errors. The system comprises magnets disposed on a doorway to create a unique magnetic field; a wireless communication unit comprising a magnetometer sensor to sense perturbations in each of the unique magnetic fields in the event that the person/object with the wireless communication unit passes through the doorway, and generate corresponding signals; a processor receiving the signals and extracting data from the same; and a backend server wirelessly communicating with the wireless communication unit, the backend server processing the data sample received from the wireless communication unit to identify the opening and the wireless communication unit to localize the person/object.

Abstract: A method and system is provided for noise cleaning of photoplethysmogram signals. The method and system is disclosed for noise cleaning of photoplethysmogram signals for estimating blood pressure of a user; wherein photoplethysmogram signals are extracting from the user; the extracted photoplethysmogram signals are up sampled; the up sampled photoplethysmogram signals are filtered; uneven baseline drift of each cycle is removed from the up sampled and filtered photoplethysmogram signals; outlier cycles of the photoplethysmogram signals are removed and remaining cycles of the photoplethysmogram signals are modeled; and time domain features are extracted from originally extracted and modeled photoplethysmogram signals for estimating blood pressure of the user.

Abstract: System and method for determining a heart rate and a heart rate variability of an individual is disclosed. An audio signal of heart sound is amplified. Subsequently, an envelope of the amplified audio signal is detected by squaring of the amplified audio signal to obtain emphasized high amplitude components and diminished low amplitude components of the audio signal, applying a band pass filter on the audio signal upon squaring and applying a Teager-Kaiser Energy Operator (TKEO) on the filtered audio signal. Peaks in the envelope of the audio signal are detected by calculating difference in magnitude of a point in the audio signal with an average of magnitude of earlier points in the audio signal from the last detected peak or the initial sample value in the processing window when no peak is detected. Based on the peaks detected, heart rate and heart rate variability for the individual are determined.

Abstract: A method, system and apparatus for determining crowdedness at a location, using a first portable communication device having a proximity sensor, wherein the location of a first user is determined using the first portable communication device having an application installed on a memory module thereof, wherein the application is configured to connect to a location sensor embedded in the first portable communication device. The method and system further comprises sensing and identifying a second portable communication device in vicinity of the first user, followed by transmitting a media access control address (MAC address) of the identified second portable communication device to a remote fusion server. Further removing redundancies pertaining to the identified second portable communication device based on the MAC address received by the remote fusion server using a fusion algorithm to determine the crowdedness at the determined location.

Abstract: A physiological parameter measurement device comprising a processor and a video processing module coupled to the processor to divide each of a plurality of frames of a video into a plurality of blocks, where the video is of a body part of a subject whose physiological parameter is to be determined. The video processing module further is to select a block having highest peak signal to noise ratio (PSNR) from amongst the plurality of blocks. Further, the video processing module is to extract a photoplethysmogram (PPG) signal from the video based on a block identifier associated with the block. The physiological parameter measurement device further comprises a signal enhancement module coupled to the processor, to process the PPG signal to obtain an enhanced PPG signal for determining a value of the physiological parameter for the subject.

Abstract: A method for measuring blood pressure of a subject is described herein. In an implementation, the method includes obtaining a plurality of photoplethysmogram (PPG) features associated with the subject. The method further includes ascertaining one or more latent parameters associated with the subject based on the plurality of PPG features and a reference model, wherein the reference model indicates a correlation between the plurality of PPG features and the one or more latent parameters. Further, blood pressure of the subject is determined based on the one or more latent parameters and the plurality of PPG features.

Abstract: A method, system and apparatus for determining crowdedness at a location, using a first portable communication device having a proximity sensor, wherein the location of a first user is determined using the first portable communication device having an application installed on a memory module thereof, wherein the application is configured to connect to a location sensor embedded in the first portable communication device. The method and system further comprises sensing and identifying a second portable communication device in vicinity of the first user, followed by transmitting a media access control address (MAC address) of the identified second portable communication device to a remote fusion server. Further removing redundancies pertaining to the identified second portable communication device based on the MAC address received by the remote fusion server using a fusion algorithm to determine the crowdedness at the determined location.

Abstract: A method and system is provided for determining and displaying least water logging prone route, from a source location to a destination location specified by a user, during a water logging condition in an area. Particularly, the invention provides a method and system for utilizing Global Positioning System (GPS) information including the source and destination location coordinates for determining the at least one alternate route to a user from the at least two routes from the source location to the destination location and rendering result on the user's portable communication device.

Abstract: An indoor positioning system and method of localizing a person/object in an indoor environment by identifying the orientation and direction of a person/object to provide a true location of the person/object without navigation errors. The system comprises magnets disposed on a doorway to create a unique magnetic field; a wireless communication unit comprising a magnetometer sensor to sense perturbations in each of the unique magnetic fields in the event that the person/object with the wireless communication unit passes through the doorway, and generate corresponding signals; a processor receiving the signals and extracting data from the same; and a backend server wirelessly communicating with the wireless communication unit, the backend server processing the data sample received from the wireless communication unit to identify the opening and the wireless communication unit to localize the person/object.