Master Thesis In-ear health monitoring with smart sensors
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Job Location:
Monthly Salary:
Posted on:
30+ days ago
Vacancies:
1 Vacancy
Job Summary
Problem statement
Wearable smart devices are everywhere and the demand for personal health monitoring solutions in these devices is increasing it is no longer all about smart watches. This masters thesis project will offer you an exciting opportunity to develop a health monitoring application using our in-ear headphones.
The headphones are equipped with Bosch Sensortec sensors that can monitor movements and tiny vibrations reaching the ear canal. The challenge is to transform raw sensor data into meaningful and actionable health insights. Through this project you will gain hands-on experience with cutting-edge smart sensor technology and signal processing development contributing to innovation in wearable health analytics.
Proposed solution
This thesis project will focus on developing algorithms for extracting a health insight from the in-ear headphone raw sensor data. This will include exploration of the data application of traditional signal processing methods and preferably machine learning methods. Depending on the choice of health insight there is some data collected for this project but you are encouraged to also collect your own data using our headphones.
We propose the following topics to be covered in the thesis:
- Initial exploration of the sensor and its raw data
- Describe and identify the features in the sensor data relevant to the physiological state or health metric
- Research and find suitable algorithms (classical signal processing or machine learning/AI methods) for reliably detecting and identifying the features
- Implement test and refine the chosen algorithms
- Produce a simple demo using your findings
You will of course be able to shape the thesis based on your knowledge interest and discoveries during the project.
Scope of master thesis project
Two students completing 30 credits each (20 weeks) onsite at the Lund office
Qualifications :
Your profile
To be successful in the project with think you are:
- A student in Engineering Mathematics/Physics Control Science Electronics or equivalent
- At least one upper basic or advanced course in mathematical statistics
- Relevant courses in statistical signal processing or machine learning
- An interest in algorithm development
- Experienced with or have at least some knowledge of programming in Matlab Python C or similar.
- Self-driven able to challenge yourself and gain the experience needed to move the project forward.
- A person with team spirit social skills and a curiosity for exploring new technology areas.
Remote Work :
No
Employment Type :
Full-time
Problem statement
Wearable smart devices are everywhere and the demand for personal health monitoring solutions in these devices is increasing it is no longer all about smart watches. This masters thesis project will offer you an exciting opportunity to develop a health monitoring application using our in-ear headphones.
The headphones are equipped with Bosch Sensortec sensors that can monitor movements and tiny vibrations reaching the ear canal. The challenge is to transform raw sensor data into meaningful and actionable health insights. Through this project you will gain hands-on experience with cutting-edge smart sensor technology and signal processing development contributing to innovation in wearable health analytics.
Proposed solution
This thesis project will focus on developing algorithms for extracting a health insight from the in-ear headphone raw sensor data. This will include exploration of the data application of traditional signal processing methods and preferably machine learning methods. Depending on the choice of health insight there is some data collected for this project but you are encouraged to also collect your own data using our headphones.
We propose the following topics to be covered in the thesis:
- Initial exploration of the sensor and its raw data
- Describe and identify the features in the sensor data relevant to the physiological state or health metric
- Research and find suitable algorithms (classical signal processing or machine learning/AI methods) for reliably detecting and identifying the features
- Implement test and refine the chosen algorithms
- Produce a simple demo using your findings
You will of course be able to shape the thesis based on your knowledge interest and discoveries during the project.
Scope of master thesis project
Two students completing 30 credits each (20 weeks) onsite at the Lund office
Qualifications :
Your profile
To be successful in the project with think you are:
- A student in Engineering Mathematics/Physics Control Science Electronics or equivalent
- At least one upper basic or advanced course in mathematical statistics
- Relevant courses in statistical signal processing or machine learning
- An interest in algorithm development
- Experienced with or have at least some knowledge of programming in Matlab Python C or similar.
- Self-driven able to challenge yourself and gain the experience needed to move the project forward.
- A person with team spirit social skills and a curiosity for exploring new technology areas.
Remote Work :
No
Employment Type :
Full-time
Key Skills
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About Company
Bosch first started in Vietnam with a representative office in 1994. Bosch has its main office in Ho Chi Minh City, with branch offices in Hanoi and Da Nang, and a Powertrain Solutions plant in the Dong Nai province to manufacture pushbelt for continuously variable transmissions (CVT) ... View more
