Personal tools

Smart Goggles for Visual In-Action Feedback in Ski Jumping (1 B/S)

From iis-projects

Revision as of 22:30, 14 July 2023 by Cleitne (talk | contribs) (Created page with "thumb|600px ==Short Description== In ski jumping, low repetition rates of jumps limit effectiveness of training. Thus, i...")
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to: navigation, search
SkiJumpingArena lSkiJumpingGoogles.png




Short Description

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 oral and based on recorded video data. Video data provides good insight into the entire jump, however translating video information into actual motor control is difficult.

Therefore, we aim to develop an in-action system that converts sensor data into simple, motor-transferable information and displays it to jumpers via LEDs integrated into ski googles.

Status: Available

Students will be co-supervised by the Center of Project Based Learning.
Looking for 1-2 Semester/Master students
Contact: Christoph Leitner, Lukas Schulthess (PBL)

Prerequisites

Embedded systems and PCB design
Microcontrollers

Character

40% Hardware and PCB Design
30% Firmware Development
20% Hardware evaluation and integration
10% Data analyses and documentation

Professor

Luca Benini

↑ top

Detailed Task Description

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 data is displayed over a LED display inside the glasses. According to the level of the student and the chosen thesis type (BT/ST) the work will include some or all following tasks:

Goals

Firmware Development
  • Implement the BLE coded PHY stack on a nRF52 microcontroller (Nordic semiconductors) integrated in an existing multisensor system for ski-jumping
Characterization

Characterization of data transmission quality and identification of losses using BLE coded PHY in various laboratory scenarious:

  • with increasing distance between source and target
  • with high velocity differences between source and target.
  • Using synthetic and/or real sensor data
Field Test
  • Transfer of the measurment setup on a ski jumping hill.
  • Validation of the system in a real-world scenario.


Practical Details


Links

↑ top