Samsung Electronics Co., Ltd.

Sujit Jos

Kiran Bynam

Young Jun Hong

Chang Soon Park

Jinesh Parameshwaran Nair

Manoj Choudhary

Chandrashekhar Thejaswi Ps

So Young Lee

Young Soo Kim

Gorish Aggarwal

Ashutosh Deepak Gore

Rahul Arora

Youngsoo Kim

Ka Ram Choi

Ibrahim A

Srikanth Mallavarapu Rama

Sang Kon Bae

Arun Naniyat

Ibrahim Abdul Majeed

Joon Seong Kang

Sang Kyu Kim

Young-Jun Hong

Amar Prakash Azad

Kannan Govindan

ChangSoon Park

Sandhya Patil

Debarati Sen

Chandrashekhar Thejaswi Pattaguppe Suryanarayan Bhat

Taeseok Kim

Ps Chandrashekhar Thejaswi

Preeti Nagvanshi

Youngjun Hong

Sreejith Kallummil

Kim Young Soo Soo

A method of transforming Monte Carlo (MC) simulations for diffuse reflectance spectroscopy (DRS) may include obtaining, by a DRS device, MC simulated DRS measurements using a pre-defined number of photons; pre-processing, by the DRS device, the MC simulated DRS measurements to obtain normalized DRS measurements; correcting, by the DRS device, non-monotonicity of the normalized DRS measurements to obtain monotonic DRS measurements; converting, by the DRS device, the monotonic DRS measurements to a logarithmic domain to obtain logarithmic DRS measurements; performing, by the DRS device, curve fitting on the logarithmic DRS measurements in the logarithmic domain to obtain curve-fitted logarithmic DRS measurements; and transforming, by the DRS device, the curve-fitted logarithmic DRS measurements to a non-logarithmic domain to obtain transformed MC simulated DRS measurements.

Method and system for optimizing Monte Carlo simulations for diffuse reflectance spectroscopy

A method of predicting a blood compound concentration of a target may include receiving, by a system, spectral data associated with a region of the target, using near-infrared (NIR) spectroscopy. The method may include classifying, by the system, each of the plurality of data instances of the spectral data to one of a plurality of labelled classes. The method may include obtaining, by the system, one or more best fit models from a plurality of prediction models based on the classification. The method may include determining, by the system, blood compound concentration values corresponding to each of the one or more best fit models. The method may include predicting, by the system, the blood compound concentration of the target using the blood compound concentration values predicted using the best fit models.

Method and system for predicting blood compound concentration of a target

A method and apparatus for pre-processing a photoplethysmogram (PPG) signal include receiving, by an apparatus, the PPG signal including a plurality of pulses, obtaining, by the apparatus, a smoothed PPG signal based on smoothing the PPG signal using a moving average filter, obtaining, by the apparatus, a drift removed PPG signal based on removing drift from the smoothed PPG signal using a fitted polynomial function, and obtaining, by the apparatus, a rectified PPG signal based on correcting a motion artifact of the drift removed PPG signal by replacing each of the plurality of pulses using a combination of a global signal pulse and a corresponding local signal pulse.

Method and apparatus for pre-processing PPG signal

The present disclosure relates to a method and system for processing a photoplethysmogram (PPG) signal to improve accuracy of measurement of physiological parameters of a subject. The method may include removing a baseline drift from the PPG signal; obtaining a drift removed signal; filtering the drift removed signal; obtaining a filtered signal; performing motion artifact correction on the filtered signal; and obtaining a corrected signal.

Drift, noise, and motion artifact correction method for photoplethysmogram (PPG) signals and system thereof

A method of estimating concentration of a blood compound may include: removing a baseline drift from Near-Infrared (NIR) spectroscopy data to obtain drift-free spectral features; obtaining a set of global features based on the drift-free spectral features; and estimating the concentration of the blood compound by regression using the set of global features.

Apparatus and method for estimation concentration of blood compound

A method for obtaining blood glucose concentration using near infrared spectroscopy (NIR) data is provided. The method includes obtaining, by an independent component analysis (ICA) temporal module, orthogonal pure spectra from human NIR spectra; performing, by a processing module, one or more preprocessings and drift removal on the human NIR spectra and the orthogonal pure spectra to obtain preprocessed spectra; and obtaining, by a regression block, the blood glucose concentration from the preprocessed spectra.

System and method for obtaining blood glucose concentration using temporal independent component analysis (ICA)

A method includes processing near infrared spectroscopy (NIR) spectra and pure spectra, to obtain a preprocessed NIR spectra, wherein the preprocessed NIR spectra includes any one or any combination of a training data of a plurality of subjects, a calibration data of a test subject and a validation data of the test subject, extracting a dominant feature set from the preprocessed NIR spectra, wherein the dominant feature set includes at least one preprocessed NIR spectrum corresponding to each of the training data, the calibration data and the validation data, and determining a blood glucose concentration of the test subject, using the training data of the plurality of subjects and based on the extracted dominant feature set.

Methods and systems for performing universal calibration to non-invasively determine blood glucose concentration

A method of extracting glucose feature, a method for monitoring glucose using near-infrared (NIR) spectroscopy and a glucose monitoring device are provided. The method comprising: removing noise from a near-infrared (NIR) data; extracting a glucose signal from the NIR data; and removing temporal drift components from the extracted glucose signal.

Method of enabling feature extraction for glucose monitoring using near-infrared (NIR) spectroscopy

A method for predicting a blood glucose level using a near-Infrared (NIR) spectrometer is provided. The method may include obtaining a feature set from an NIR glucose spectra; and predicting glucose values from the feature set based on a binary classification of the NIR glucose spectra and an in-class prediction of glucose using Machine Learning Regression.

Method of predicting blood glucose level using near-infrared (NIR) spectroscopy data

A method to detect a packet includes: receiving an input sequence including preambles; detecting a transition from a noise period to a signal period in the input sequence; dynamically adjusting a gain of the input sequence in response to the signal period being initiated; and distinguishing an intended packet from other packets, among packets received in the preambles.

Method and apparatus for detecting packet

A method and a transmitter for transmitting a pay load sequence are provided. The transmitter includes a ternary sequence mapper configured to map a binary data sequence to a ternary sequence stored in the transmitter, and a pulse shaping filter configured to generate a first signal based on the mapped ternary sequence. The ternary sequence includes elements of &#x2212;1, 0, and 1.

Method and device for transmitting pay load sequence

The present invention describes a method and system for simultaneous transmission of data to coherent and non-coherent receivers. The method at the transmitter includes retrieving a base ternary sequence having a pre-defined length, obtaining one or more ternary sequences corresponding to data to be transmitted and transmitting the obtained one or more ternary sequences by the transmitter. The method steps at the receiver includes receiving one or more ternary sequences corresponding to the data transmitted, demodulating each of the received ternary sequences by correlating with all cyclic shifts of the base ternary sequence by the receiver if the receiver is a coherent receiver, demodulating each of the received ternary sequences by correlating with all cyclic shifts of the absolute of the base ternary sequence by the receiver if the receiver is a non-coherent receiver and detecting the transmitted data based on the cyclic shifts corresponding to maximum correlation values.

Method and system using ternary sequences for simultaneous transmission to coherent and non-coherent receivers

A method and apparatus estimating carrier frequency offset (CFO) with timing synchronization are provided. The apparatus includes processor that receives analog-to-digital converter (ADC) samples, determines a coarse angle from the received ADC samples, obtains an improved coarse angle by altering the coarse angle based on a preamble duration, determines a base CFO estimate from the improved coarse angle and determines a plurality of candidate CFOs based on the base CFO estimate and a difference frequency.

Method for estimating carrier frequency offset with timing synchronization in wireless receiver

Disclosed is a method and system to transmit independent data by at least two transmitters to corresponding at least two receivers. The method includes obtaining, at a first transmitter, a first ternary sequence from a first base ternary sequence corresponding to a first set of data-symbols, and obtaining, at a second transmitter, a second ternary sequence from a second base ternary sequence corresponding to a second set of data-symbols. The method also includes transmitting, from the first transmitter, the first ternary sequence to a first set of receivers associated with the first transmitter. The method transmits, from the second transmitter, the second ternary sequence to a second set of receivers associated with the second transmitter.

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Bengaluru, India

Sujit Jos