AU2021107474A4 - Early Illness Detection System - Google Patents

Early Illness Detection System Download PDF

Info

Publication number
AU2021107474A4
AU2021107474A4 AU2021107474A AU2021107474A AU2021107474A4 AU 2021107474 A4 AU2021107474 A4 AU 2021107474A4 AU 2021107474 A AU2021107474 A AU 2021107474A AU 2021107474 A AU2021107474 A AU 2021107474A AU 2021107474 A4 AU2021107474 A4 AU 2021107474A4
Authority
AU
Australia
Prior art keywords
disease
illness
symptoms
data
early
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
AU2021107474A
Inventor
Abdul Kawnain
Vikrant Sharma
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Individual
Original Assignee
Individual
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Individual filed Critical Individual
Priority to AU2021107474A priority Critical patent/AU2021107474A4/en
Application granted granted Critical
Publication of AU2021107474A4 publication Critical patent/AU2021107474A4/en
Ceased legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/48—Other medical applications
    • A61B5/4803—Speech analysis specially adapted for diagnostic purposes
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
    • G10L25/48—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use
    • G10L25/51—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use for comparison or discrimination
    • G10L25/66—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use for comparison or discrimination for extracting parameters related to health condition
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/0205—Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/024—Detecting, measuring or recording pulse rate or heart rate
    • A61B5/02438—Detecting, measuring or recording pulse rate or heart rate with portable devices, e.g. worn by the patient
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
    • A61B5/1455—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue using optical sensors, e.g. spectral photometrical oximeters
    • A61B5/14551—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue using optical sensors, e.g. spectral photometrical oximeters for measuring blood gases
    • A61B5/14552—Details of sensors specially adapted therefor
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
    • A61B5/7267—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems involving training the classification device
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7271—Specific aspects of physiological measurement analysis
    • A61B5/7275—Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7271—Specific aspects of physiological measurement analysis
    • A61B5/7282—Event detection, e.g. detecting unique waveforms indicative of a medical condition
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/74—Details of notification to user or communication with user or patient ; user input means
    • A61B5/742—Details of notification to user or communication with user or patient ; user input means using visual displays

Abstract

The impact of the global pandemic in 2020 has helped us identify key lackings in disease and illness detection methods that currently exist. These factors have highlighted that it is imperative that better, quicker, and accurate techniques to detect illness at an early stage are identified and developed. With advancements such as machine learning and big data, it is possible to implement industry-leading solutions for early symptoms detection. By leveraging the advantages of signal processing and machine learning, we are able to learn, train and identify trends which allows a system to classify voice signatures that can output symptoms for disease and illnesses to its users. The system also takes advantage of it's integrated heart rate and blood oxygen level sensor to improve the accuracy of the symptoms presented on to the user. The implementation of this system can help health practitioners more efficiently diagnose patients at an early stage of the disease or illness and help reduce hospitalization rates as well. 2/2 Voice Input Convert input data into a signal over time Update test Data Compare against stored test data Provide Output Figure 1 2 Figure 2

Description

2/2
Voice Input
Convert input data into a signal over time
Update test Data Compare against stored test data
Provide Output
Figure 1
2
Figure 2
EARLY ILLNESS DETECTION DEVICE
[0001] Early illness detection system in accordance with this invention has one main objective; that is to be able to detect certain diseases and conditions at an early stage either by the use of a handheld device which operates on the principles of signal analysis and deep learning.
[0002] this new invention is based on the amalgamation of unique signal processing techniques and deep learning. The main idea behind the invention is to have a low cost and time saving and effective method of determining certain medical conditions. The physical structure/ casing of the device is 3D printed and mated together using fasteners (screws), the casing is very robust and is designed to fit in the palm for ease of use. The circuitry of the device will be assembled using a 12S microphone (input device), Pimoroni MAX30105 heart rate and blood oxygen level sensor (input device), Raspberry Pi zero (micro-controller), Waveshare NB-oT eMTC (data communications unit) and a 3inch LCD screen (output device), this will implement a simple input, processing and output structure. The device will also contain a power button and charging port) and rechargeable batteries.
[0003] the micro-controller will be programmed to contain pre-tested (healthy voice (signal) and un-healthy voice (signal)) data and will take the input voice, convert it into a signal over time and compare the similarities/dis-similarities with the stored data and give an output as to whether the person (voice) is healthy or has an alarming medical condition which should be looked into. The data will then be stored into the devices memory will increase the accuracy of the device the more it is used.
[0004] the device is designed to be used handheld and can be used at homes or in hospitals. The device is programmed to operate in real time, as the power button is pressed and an individual speaks into the device the data will be taken in instantly, converted into a signal and processed. Combined with data from heart rate and blood oxygen level sensors, the device further analyses the data to further narrow down the list of possible diseases the person is displaying symptoms for. The output is then presented on the LCD screen.
[0005] the device can send notifications to authorized health practitioners based on the output it has generated from its findings based on the voice signature sample(s) received, the patient's blood oxygen level and the heart rate/pulse generated through the heart rate sensor.
[0006] the invention can be better understood by making references to the illustrations of embodiments of the invention which:
[0006a] Figure 1 shows a flowchart which shows programming and operating structure of the device.
[0006b] Shown in Figure 2 is a diagram of the device. Labelled 1 is the early detection device, labelled 2 is LCD, labelled 3 is OXY and heart rate combined sensor, labelled 4 is the input microphone.

Claims (4)

EDITORIAL NOTE 2021107474 THERE IS ONE PAGE OF CLAIMS ONLY CLAIMS The claims defining the invention are as follows:
1. The system will be able to develop and learn different variations in voice signatures as a function of a time based domain. Through iterations of sampling large sets of data, the system will gain the ability to distinguish and classify between different patterns of signals.
2. The device will then use its extensive database to train itself further to improve accuracy between different classifications.
3. By leveraging the large data sets of samples, the system will then be able to accurately identify the health status of an individual by analyzing their vocal signature.
4. The system can be utilized as an early detection of health concerns that may contribute to preventative treatment of the disease/illness.
AU2021107474A 2021-08-25 2021-08-25 Early Illness Detection System Ceased AU2021107474A4 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
AU2021107474A AU2021107474A4 (en) 2021-08-25 2021-08-25 Early Illness Detection System

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
AU2021107474A AU2021107474A4 (en) 2021-08-25 2021-08-25 Early Illness Detection System

Publications (1)

Publication Number Publication Date
AU2021107474A4 true AU2021107474A4 (en) 2021-12-23

Family

ID=78958201

Family Applications (1)

Application Number Title Priority Date Filing Date
AU2021107474A Ceased AU2021107474A4 (en) 2021-08-25 2021-08-25 Early Illness Detection System

Country Status (1)

Country Link
AU (1) AU2021107474A4 (en)

Similar Documents

Publication Publication Date Title
US7039560B2 (en) Measuring device with comment input function
Bhaskar et al. Time series classification-based correlational neural network with bidirectional LSTM for automated detection of kidney disease
CN104361245B (en) Measurement data-processing system and method
CN107970027B (en) Radial artery detection and human body constitution identification system and method
Basjaruddin et al. Measurement device for stress level and vital sign based on sensor fusion
CN114121266A (en) Intelligent auxiliary diagnosis method and system
US20120278072A1 (en) Remote healthcare system and healthcare method using the same
AU2021107474A4 (en) Early Illness Detection System
Mishra et al. Classification of normal and abnormal heart sounds for automatic diagnosis
CN103149363A (en) Integrated glucose meter
Hezarjaribi et al. S2NI: A mobile platform for nutrition monitoring from spoken data
CN112244875A (en) Schizophrenia detection method based on electroencephalogram and deep learning
Chatterjee et al. D-Cov19Net: A DNN based COVID-19 detection system using lung sound
Fatima et al. Multi-Modality and Feature Fusion-Based COVID-19 Detection Through Long Short-Term Memory.
Ogungbe et al. Design and Implementation of Diagnosis System for Cardiomegaly from Clinical Chest X-ray Reports
Ramesh COVID or Just a Cough? AI for Detecting COVID-19 from Cough Sounds
KR20240037814A (en) Severity classification method for respiratory disease based on acoustic data collected by smartphone
CN112117015B (en) Sepsis early warning equipment, sepsis early warning method, sepsis early warning device and sepsis early warning storage medium
US20210369136A1 (en) System & Method for Measurement of Respiratory Rate and Tidal Volume Through Feature Analysis of Breath Sounds to Detect Disease State
US20220322965A1 (en) Transforming cheap spirometers to estimate flow-volume graph by deep learning
CN103417241A (en) Automatic analyzer of lung sounds
Tian et al. Natural interactive techniques for the detection and assessment of neurological diseases
Chauhan et al. Comparative study of various techniques to diagnose disease using Pulse sensing
Liu et al. Research on the key technology based-nlp of chinese medicine pulse's mathematical quantifying
Deraniyagala et al. Development of a Web App for Asthmatic Wheeze Detection using Convolutional Neural Networks

Legal Events

Date Code Title Description
FGI Letters patent sealed or granted (innovation patent)
MK22 Patent ceased section 143a(d), or expired - non payment of renewal fee or expiry