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Monitoring respiration rate using wearable technologies
The aim of this project is to develop an unobtrusive wearable for the measurement of respiration rate. Measurements made by such a device can be used to track and guide users’ exercise routine.
Wearables are commonly used for fitness tracking. These devices allow for continuous measurements of environmental and physiological data that can be used to monitor, quantify, or optimize training loads. External and internal measures of exercise intensity are used to inform training routine adaptations, prevent physical overuse, and guide recovery from injuries. Various solutions are available for monitoring the external measures; however, tracking internal training loads remains a challenge. Respiration rate has proven to be a predictive indicator of internal exercise loads. This research is focused on developing smart garments using our textile sensing technologies for continuous measurements of respiration rate in runners towards the prediction of their internal training loads.
Wearables are commonly used for fitness tracking. These devices allow for continuous measurements of environmental and physiological data that can be used to monitor, quantify, or optimize training loads. External and internal measures of exercise intensity are used to inform training routine adaptations, prevent physical overuse, and guide recovery from injuries. Various solutions are available for monitoring the external measures; however, tracking internal training loads remains a challenge. Respiration rate has proven to be a predictive indicator of internal exercise loads. This research is focused on developing smart garments using our textile sensing technologies for continuous measurements of respiration rate in runners towards the prediction of their internal training loads.
**Goals**
- Develop electronics to acquire data from capacitive sensors
- Incorporate sensors (provided by applied materials researchers within BMHT or commercial options) and electronics into garments for respiration rate measurement
- Evaluate the performance of the garment in static and dynamic conditions
- Visualize results and write a report of the work (manuscript or project report)
**Tasks**
- Literature review (10%)
- Development of garment using capacitive sensors (40%)
- Data collection (10%)
- Data analysis and evaluation (20%)
- Report and presentation (20%)
**Your Profile**
- Background in Electrical Engineering, Computer Engineering, or related fields
- Prior experience with prototyping (electrical circuits and microcontroller programming)
- Prior experience with machine learning algorithms
- Independent worker with critical thinking and problem solving skills
- Can collect data and visualize it using different charts such as boxplot and scatter plots
**Goals**
- Develop electronics to acquire data from capacitive sensors
- Incorporate sensors (provided by applied materials researchers within BMHT or commercial options) and electronics into garments for respiration rate measurement
- Evaluate the performance of the garment in static and dynamic conditions
- Visualize results and write a report of the work (manuscript or project report)
**Tasks**
- Literature review (10%)
- Development of garment using capacitive sensors (40%)
- Data collection (10%)
- Data analysis and evaluation (20%)
- Report and presentation (20%)
**Your Profile**
- Background in Electrical Engineering, Computer Engineering, or related fields
- Prior experience with prototyping (electrical circuits and microcontroller programming)
- Prior experience with machine learning algorithms
- Independent worker with critical thinking and problem solving skills
- Can collect data and visualize it using different charts such as boxplot and scatter plots
Prof Dr Carlo Menon and Dr. Chakaveh Ahmadizadeh will supervise the student and the research will be performed at the Biomedical and Mobile Health Technology lab (www.bmht.ethz.ch) at ETH Zurich, Switzerland.
To apply, use the button below to tell us why you want to do this project ("motivation"); attach a mini CV with your current program of study, your grades and any other info you deem relevant--maybe the name and phone number of a postdoc or a professor willing to be your reference; and make any further comments ("additional remarks").
Prof Dr Carlo Menon and Dr. Chakaveh Ahmadizadeh will supervise the student and the research will be performed at the Biomedical and Mobile Health Technology lab (www.bmht.ethz.ch) at ETH Zurich, Switzerland.
To apply, use the button below to tell us why you want to do this project ("motivation"); attach a mini CV with your current program of study, your grades and any other info you deem relevant--maybe the name and phone number of a postdoc or a professor willing to be your reference; and make any further comments ("additional remarks").
