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A Hidden Markov Model of the Breaststroke Swimming Temporal Phases Using Wearable Inertial Measurement Units

Related publications (40)

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Self-supervised Dense Representation Learning for Live-Cell Microscopy with Time Arrow Prediction

Martin Weigert, Benjamin Tobias Gallusser, Max Stieber

State-of-the-art object detection and segmentation methods for microscopy images rely on supervised machine learning, which requires laborious manual annotation of training data. Here we present a self-supervised method based on time arrow prediction pre-t ...

Cham2023

Monitoring weekly progress of front crawl swimmers using IMU-based performance evaluation goal metrics

Kamiar Aminian, Farzin Dadashi, Fabien Massé, Mahdi Hamidi Rad, Vincent Gremeaux

Technical evaluation of swimming performance is an essential factor in preparing elite swimmers for their competitions. Inertial measurement units (IMUs) have attracted much attention recently because they can provide coaches with a detailed analysis of sw ...

FRONTIERS MEDIA SA2022

Robotic Elytra: Insect-Inspired Protective Wings for Resilient and Multi-Modal Drones

Dario Floreano, Charalampos Vourtsis, William John Stewart

Winged drones that fly in close proximity to obstacles or that are capable of aerial and terrestrial locomotion can benefit from protective systems that prevent damage to delicate aerial structures. Existing protective solutions focus on multi-copter drone ...

2021

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Gamified rehabilitation tackles the problem of keeping patients engaged in, and motivated to do physical rehabilitation to improve its efficacy. However, with respect to standard rehabilitation, patients are freer to move about and may compensate their mot ...

IEEE2021

Mobility concerns most daily tasks (e.g., householding, shopping), affecting life quality. Gait speed, recognized as the sixth vital sign, is a key to characterize mobility. It is also a primary outcome of many clinical interventions. Monitoring gait in un ...

EPFL2020

Over the past few years, there have been fundamental breakthroughs in core problems in machine learning, largely driven by advances in deep neural networks. The amount of annotated data drastically increased and supervised deep discriminative models exceed ...

EPFL2020

A novel approach for swimming analysis in main swimming styles using a single sacrum-worn IMU sensor

Kamiar Aminian, Mahdi Hamidi Rad

Introduction: Today, inertial measurement units (IMU) provide promising solutions for swimmers’ motions analysis [1-3]. However, most studies focused on few parameters, often during strokes of front crawl style [4]. For swimming training session monitoring ...

2020

Adaptive locomotion of artificial microswimmers

Mahmut Selman Sakar, Fazil Emre Uslu

Bacteria can exploit mechanics to display remarkable plasticity in response to locally changing physical and chemical conditions. Compliant structures play a notable role in their taxis behavior, specifically for navigation inside complex and structured en ...

2019

Keep Rollin’—Whole-Body Motion Control and Planning for Wheeled Quadrupedal Robots

Marco Hutter

We show dynamic locomotion strategies for wheeled quadrupedal robots that combine the advantages of both walking and driving. The developed optimization framework tightly integrates the additional degrees of freedom introduced by the wheels. Our approach r ...

2019

Steerable Locomotion Controller for Six-strut Icosahedral Tensegrity Robots

Chiara Ercolani, Massimo Vespignani

This paper proposes a novel steerable locomotion controller for six-strut tensegrity robots. Tensegrity robots are lightweight and have many promising features such as robustness, shape-shifting capabilities, and deployability, making them good candidates ...

2018