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  2. FAST - FIT Algorithms for Smart Training FAST - FIT Algorithms for Smart Training

FAST - FIT Algorithms for Smart Training

An innovative combination of heart rate control and automatic training planning will establish e-bikes as effective training devices for seniors and people with low physical endurance.

Brief information

School:

Engineering and Architecture

Status:

Completed

Period:

01.10.2020 - 30.04.2022

Overview

Thanks to their electrical support, e-bikes offer a USP which allows even seniors and sporty inactive people to ride longer distances in any terrain. Although e-bikes require a minimum amount of physical energy, they can hardly be called training devices. In this research project, we want to prove that the e-bike can act as an enabler by making it possible for seniors to use it as a sports device through its motor support. Pedal support and the gear ratio will be adjusted adaptively to the riders' fitness level. This will be made possible by the development of an adaptive heart rate control system and intelligent training and route planning.

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Facts

Type of project

Forschung

Internal organisations involved
  • iHomeLab
External project partner
  • Biketec GmbH
External project funder
  • Innosuisse
Funding
  • SBFI
  • Forschungsfinanzierung allgemein
  • Innosuisse - HSLU als Hauptforschungspartnerin (Main Research Partner)
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Persons involved: internal

Project manager
  • Martin Camenzind
Member of project team
  • Edith Birrer
  • Alberto Calatroni
  • Patric Eberle
  • Martin Friedli
  • Patrick Huber Mittler
  • Guido Kniesel
  • Stefan Niederberger
  • Andrew Paice
  • Andreas Rumsch
  • Raphael Schranz
  • Benjamin Vera
  • Manuel Vogel
  • Dieter von Arx

Brief information

School:

Engineering and Architecture

Status:

Completed

Period:

10/01/2020 - 04/30/2022

Project Head

Martin Camenzind

Senior Research Associate

+41 41 349 33 28

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