Keen Ear

This project focuses on Audio Analysis as the main theme which is a form of Machine Learning. Audio analysis refers to the extraction of information and meaning from audio signals for analysis, classification, storage, retrieval, synthesis, etc. The observation mediums and interpretation methods var

Project Title

Keen Ear

Project Area of Specialization

Wearables and Implantable

Project Summary

This project focuses on Audio Analysis as the main theme which is a form of Machine Learning. Audio analysis refers to the extraction of information and meaning from audio signals for analysis, classification, storage, retrieval, synthesis, etc. The observation mediums and interpretation methods vary, as audio analysis can refer to the human ear and how people interpret the audible sound source, or it could refer to using technology such as an Audio analyzer to evaluate other qualities of a sound source such as amplitude, distortion, frequency response, and more. Audio data analysis is about analyzing and understanding audio signals captured by digital devices, with numerous applications in the enterprise, healthcare, productivity, and smart cities. Applications include customer satisfaction analysis from customer support calls, media content analysis and retrieval, medical diagnostic aids and patient monitoring, assistive technologies for people with hearing impairments, and audio analysis for public safety.

Out of the applications mentioned above, Keen Ear falls in the healthcare application of audio data analysis.

Reference: https://www.kdnuggets.com/2020/02/audio-data-analysis-deep-learning-python-part-1.html

Project Objectives

Academic Objective:

Our primary objective is to ensure the completion of our project along with the fulfillment of prerequisites of the final year project. This will include building individual scientific and AI skills and presenting the perfect details of the project. This project shall aid to build the necessary skills that would allow our group members to become capable of penetrating into the industry without confronting unnecessary hurdles. Group members will become aware of how AI works and give them the root understanding of ML and Algorithms working in it. Members shall get the idea of the latest technologies and techniques that are being used in building AI.

The core skills that they will gain from this final year project are:

• Machine learning
• Deep Learning
• Artificial Intelligence
• Data Analysis
• Microprocessors
• Embedded Programming

Application/End Goal Objective:

The goal of this project is to develop a gadget that both doctors and patients could take advantage of. This gadget would help the doctors in the healthcare system in diagnosis and reduce the cost of diagnostic procedures for the patients. It is supposed to be an important introduction in the Healthcare Department.

Working of the Final Product:

. It will be a controller chip with the machine learning algorithm installed on it. An audio input mechanism would be a stethoscope connected to the microchip. This stethoscope will take a patient's respiratory sound in live-time and the ML Algorithm will predict a disease for that audio or declare it to be healthy. The result of this, healthy or name of a disease, would be shown using an LED Output mechanism also connected to the controller chip.

Project Implementation Method

1. Capture Audio??????

Keen Ear will be able to capture the respiratory audio of a patient at live time, through an input mechanism. This is an important functionality as all the other functionalities will be dependent on the audio recorded in this feature.

The device will prompt the user to record audio when the user presses the appropriate button on the device.

2. Disease Prediction

It will help the user know as to which disease the patient has. This is the key feature of the product. The ML algorithm will predict the disease for the patient using the audio recorded. The patient’s audio will either be classified as ‘healthy’ or a disease like COPD, Asthma, Bronchitis, Tuberculosis etc.

Benefits of the Project

Audio data analysis is about analyzing and understanding audio signals captured by digital devices, with numerous applications in the enterprise, healthcare, productivity, and smart cities. Its intended applications include customer satisfaction analysis from customer support calls, media content analysis and retrieval, medical diagnostic aids and patient monitoring, assistive technologies for people with hearing impairments, and audio analysis for public safety. Among all these areas the most relevant is the area of health, specifically patients monitoring and diagnostics aids.

This project will have intended benefits for the patients and doctors both as follows:

1. Act as a device for the input and processing respiratory audios of patients.

2. Prediction of patients with identifiable respiratory diseases based on the audio.

3. Provide users with an intuitive and easy-to-use interface for the final hardware device.

4. Help the doctors (and other users) in reducing the process of diagnosis.

The goal of this project is to develop a gadget that both doctors and patients could take advantage of. This gadget would help the doctors in the healthcare system in diagnosis and reduce the cost of diagnostic procedures for the patients. It is supposed to be an important introduction to the Healthcare Department. An audio input mechanism would be a stethoscope connected to the microchip. This stethoscope will take a patient's respiratory sound in live-time and the ML Algorithm will predict a disease for that audio or declare it to be healthy. The result of this, healthy or name of a disease, would be shown using an LED Output mechanism also connected to the controller chip.

As a business opportunity as well the product may be further developed to meet the needs of the local community to start with and expand operations if it gets successful in helping both patients and doctors

Technical Details of Final Deliverable

The scope of the project is to help the doctors and diagnosticians in the process of diagnosis of respiratory diseases by writing a machine learning code that can tell different diseases apart based on their respiratory audios. The project will give a hardware device that can take respiratory voice of a patient at live time and predict a respiratory disorder that the patient might have like Tuberculosis, COPD, Asthma, Bronchitis etc.

Following are a list of features and uses that Keen Ear will have

1. Input and process respiratory audios of users.
2. Correctly predict respiratory diseases based on the respiratory audio
3. Have an intuitive and easy-to-use interface for the final hardware device.
4. Help the doctors (and other users) in reducing the process of diagnosis.

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Medical

Other Industries

IT

Core Technology

Wearables and Implantables

Other Technologies

Artificial Intelligence(AI)

Sustainable Development Goals

Good Health and Well-Being for People

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com