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Difference between revisions of "Skin coupling media characterization for fitnesstracker applications (1 B/S)"

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(Created page with "thumb|400px ==Short Description== In ski jumping, low repetition rates of jumps limit effectiveness of training. Thus, increasing...")
 
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==Short Description==
 
==Short Description==
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In ski jumping, low repetition rates of jumps limit effectiveness of training. Thus, increasing learning rate within every single jump is key to success. A critical element of athlete training is motor learning, which has been shown to be accelerated using feedback methods. Today, coach’s training feedback is mainly verbal and based on recorded video data. Video data provides good insight into the entire jump, however for an athlete to convert post-action video and speech information into actual motor control during action is difficult. Therefore, we aim to develop a system that translates sensor data into simple, motor-transferable information online and displays this to jumpers (e.g. via LEDs) during the execution of the jump.
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===Status: Available ===
 
===Status: Available ===
 
: Students will be co-supervised by the Center of Project Based Learning.
 
: Students will be co-supervised by the Center of Project Based Learning.
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: Looking for 1-2 Bachelor or Semester students / 1 Master student
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: Looking for 1 Bachelor or Semester students
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: Contact: [[:User:Cleitne | Christoph Leitner]], [mailto:schuluka@student.ethz.ch Lukas Schulthess (PBL)]
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: Contact: [[:User:Cleitne | Christoph Leitner]], [mailto:marco.giordano@pbl.ee.ethz.ch Marco Giordano (PBL)]
  
 
===Prerequisites===
 
===Prerequisites===
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: Embedded systems and PCB design
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: Signal Procesing
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: Microcontrollers
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: Mechanical Design
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: Mixed Signals
 
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===Status: Completed ===
 
===Status: Completed ===
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===Character===
 
===Character===
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: 40% Hardware and PCB Design
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: 30% Mechanical Design
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: 30% Firmware Development
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: 30% Signal Processing
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: 20% Hardware evaluation and integration
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: 20% Literature Research
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: 10% Data analyses and documentation
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: 20% Data analyses and documentation
  
 
===Professor===
 
===Professor===
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==Detailed Task Description==
 
==Detailed Task Description==
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The main goal of this thesis is to design, build and test an intelligent ski goggle that provides in-action feedback to athletes. Goggles should inform athletes about their center of gravity positioning druing the in-run. For this purpose, sensor data is collected from the insole of ski boots and processed with a tinyML model. The extracted feedback information is displayed over a LED display inside the glasses. According to the level of the student and the chosen thesis type (BT/ST/MT) the work will include some or all following tasks:  
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According to the level of the student and the chosen thesis type (BT/ST/MT) the work will include some or all following tasks:  
  
 
===Goals===
 
===Goals===
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=====Hardware and PCB Design=====
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=====Mechanical Design=====
 
* Creation of design proposals for the integration of a visual biofeedback in ski goggles.
 
* Creation of design proposals for the integration of a visual biofeedback in ski goggles.
 
* Development of a benchtop prototype using a nRF52 development kit (Nordic Semiconductor)
 
* Development of a benchtop prototype using a nRF52 development kit (Nordic Semiconductor)
  
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=====Firmware Development=====
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=====Testing=====
 
* Implementation of biofeedback data transmission via BLE using two nRF52 microcontrollers (on the sensor node and in the glasses).  
 
* Implementation of biofeedback data transmission via BLE using two nRF52 microcontrollers (on the sensor node and in the glasses).  
 
* Conversion of tinyML outputs into visual feedback.
 
* Conversion of tinyML outputs into visual feedback.
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=====Testing=====
 
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* Analyses of data transfer quality using BLE (e.g., identification of losses, delay times,..)
 
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* Testing in lab conditions and in a real world scenario
 
  
 
===Practical Details===
 
===Practical Details===

Revision as of 22:26, 22 July 2023

Fitness tracker coupling.png




Short Description

Status: Available

Students will be co-supervised by the Center of Project Based Learning.
Looking for 1 Bachelor or Semester students
Contact: Christoph Leitner, Marco Giordano (PBL)

Prerequisites

Signal Procesing
Mechanical Design
Mixed Signals

Character

30% Mechanical Design
30% Signal Processing
20% Literature Research
20% Data analyses and documentation

Professor

Luca Benini

↑ top

Detailed Task Description

According to the level of the student and the chosen thesis type (BT/ST/MT) the work will include some or all following tasks:

Goals

Mechanical Design
  • Creation of design proposals for the integration of a visual biofeedback in ski goggles.
  • Development of a benchtop prototype using a nRF52 development kit (Nordic Semiconductor)
Testing
  • Implementation of biofeedback data transmission via BLE using two nRF52 microcontrollers (on the sensor node and in the glasses).
  • Conversion of tinyML outputs into visual feedback.

Practical Details


Links

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