Development of smart garments to monitor the frontal plane knee angle for sports and medical applications

The frontal plane knee angle is a valuable measure that can be used for rehabilitation in addition to the assessment and prevention of injuries. Despite the importance of this measure, the current methods of its quantification are focused on using cameras. The most commonly used methods involve the use of motion capture systems or the combination of cameras and image processing. These methods limit the practicality of continuous measurements of the frontal plane knee angle in daily life. Motion capture systems are expensive and require professionals for setup and operation. Both motion capture systems and image processing-based methods can only be used in equipped spaces that are often limited to a room. Wearables that measure the frontal plane knee angle can provide a solution that makes valuable information available and widely accessible. Most current wearables focused on this measure use IMUs that require computationally extensive processing and are prone to errors such as environmental interference. This project proposes the use of smart garments using our textile-based sensors and/or other novel sensing modalities for the measurement of the frontal plane knee angle.

The frontal plane knee angle is a valuable measure that can be used for rehabilitation in addition to the assessment and prevention of injuries. Despite the importance of this measure, the current methods of its quantification are focused on using cameras. The most commonly used methods involve the use of motion capture systems or the combination of cameras and image processing. These methods limit the practicality of continuous measurements of the frontal plane knee angle in daily life. Motion capture systems are expensive and require professionals for setup and operation. Both motion capture systems and image processing-based methods can only be used in equipped spaces that are often limited to a room. Wearables that measure the frontal plane knee angle can provide a solution that makes valuable information available and widely accessible. Most current wearables focused on this measure use IMUs that require computationally extensive processing and are prone to errors such as environmental interference. This project proposes the use of smart garments using our textile-based sensors and/or other novel sensing modalities for the measurement of the frontal plane knee angle.

**Goals** - Explore various sensing modalities for the measurement of the frontal knee angle - Explore various sensing modalities for the measurement of the frontal knee angle - Implement electronics and software for the acquisition of signals form the sensing modalities being investigated - Incorporate sensors and electronics into textile to produce smart garments - Evaluate the performance of the garments in static and dynamic conditions - Visualize results and write a report of the work (manuscript or project report) **Tasks** - Literature review (20%) - Exploration of various sensing modalities (20%) - Development of garment (10%) - Data collection (10%) - Data analysis and evaluation (20%) - Report and presentation (20%) **Your Profile** - Background in Electrical Engineering, Computer Engineering, mechanical engineering, or related fields - Prior experience with prototyping (electrical circuits and microcontroller programming) - Prior experience with data analysis (signal processing, machine learning algorithms, or similar) - 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**

- Explore various sensing modalities for the measurement of the frontal knee angle

- Explore various sensing modalities for the measurement of the frontal knee angle

- Implement electronics and software for the acquisition of signals form the sensing modalities being investigated

- Incorporate sensors and electronics into textile to produce smart garments

- Evaluate the performance of the garments in static and dynamic conditions

- Visualize results and write a report of the work (manuscript or project report)

**Tasks**

- Literature review (20%)

- Exploration of various sensing modalities (20%)

- Development of garment (10%)

- Data collection (10%)

- Data analysis and evaluation (20%)

- Report and presentation (20%)

**Your Profile**

- Background in Electrical Engineering, Computer Engineering, mechanical engineering, or related fields

- Prior experience with prototyping (electrical circuits and microcontroller programming)

- Prior experience with data analysis (signal processing, machine learning algorithms, or similar)

- 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") along with the type of project you are applying for (e.g., master project or thesis) and your timeline for the project; 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") along with the type of project you are applying for (e.g., master project or thesis) and your timeline for the project; 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").