Virtual Proprioception with Eccentric Training for a Shoulder Press by a Wearable System

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21460%2F24%3A00382847" target="_blank" >RIV/68407700:21460/24:00382847 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-031-62523-7_50" target="_blank" >http://dx.doi.org/10.1007/978-3-031-62523-7_50</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-031-62523-7_50" target="_blank" >10.1007/978-3-031-62523-7_50</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Virtual Proprioception with Eccentric Training for a Shoulder Press by a Wearable System

Popis výsledku v původním jazyce

The confluence of wearable systems with machine learning enables the opportunity for quantified exercise with the ability to discern specifically personalized strategies, such as eccentric strength training. Using a unique software application with a smartphone to provide real-time feedback with respect to the gyroscope signal, effective threshold bounds can be prescribed and maintained during an exercise, such as a shoulder press. The concept of utilizing visualized feedback from an inertial sensor, such as a gyroscope, for regulating human movement is known as Virtual Proprioception. Additionally, the smartphone software application is capable of recording the gyroscope signal for wireless transmission to an email account, which constitutes a provisional Cloud computing environment. Given these characteristics, the smartphone has the functional properties of a wearable and wireless gyroscope platform. Post-processing of the gyroscope signal data for an eccentric training oriented shoulder press using the smartphone by means of Virtual Proprioception providing real-time feedback can be differentiated relative to standard strength training through a machine learning algorithm, such as a multilayer perceptron neural network, and considerable classification accuracy has been attained. The implications are augmented acuity for strength training strategies that are highly specified according to personalized exercise objectives. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Název v anglickém jazyce

Virtual Proprioception with Eccentric Training for a Shoulder Press by a Wearable System

Popis výsledku anglicky

The confluence of wearable systems with machine learning enables the opportunity for quantified exercise with the ability to discern specifically personalized strategies, such as eccentric strength training. Using a unique software application with a smartphone to provide real-time feedback with respect to the gyroscope signal, effective threshold bounds can be prescribed and maintained during an exercise, such as a shoulder press. The concept of utilizing visualized feedback from an inertial sensor, such as a gyroscope, for regulating human movement is known as Virtual Proprioception. Additionally, the smartphone software application is capable of recording the gyroscope signal for wireless transmission to an email account, which constitutes a provisional Cloud computing environment. Given these characteristics, the smartphone has the functional properties of a wearable and wireless gyroscope platform. Post-processing of the gyroscope signal data for an eccentric training oriented shoulder press using the smartphone by means of Virtual Proprioception providing real-time feedback can be differentiated relative to standard strength training through a machine learning algorithm, such as a multilayer perceptron neural network, and considerable classification accuracy has been attained. The implications are augmented acuity for strength training strategies that are highly specified according to personalized exercise objectives. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20601 - Medical engineering

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Advances in Digital Health and Medical Bioengineering. Proceedings of the 11th International Conference on E-Health and Bioengineering, EHB-2023, November 9–10, 2023, Bucharest, Romania – Volume 3: Telemedicine, Biomaterials, Environmental Protection, Medical Imaging, and Biomechanics

ISBN

978-3-031-62523-7

ISSN

1680-0737

e-ISSN

1433-9277

Počet stran výsledku

8

Strana od-do

453-460

Název nakladatele

Springer Nature Switzerland AG

Místo vydání

Basel

Místo konání akce

Bucuresti

Datum konání akce

9. 11. 2023

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

001434998400050