Application of Machine Learning Approaches for Classifying Sitting Posture Based on Force and Acceleration Sensors. - Wikidata - awgldk - TriplyDB

Application of Machine Learning Approaches for Classifying Sitting Posture Based on Force and Acceleration Sensors.

Application of Machine Learning Approaches for Classifying Sitting Posture Based on Force and Acceleration Sensors.

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Posture Detection Based on Smart Cushion for Wheelchair Users.Activity Level Assessment Using a Smart Cushion for People with a Sedentary Lifestyle.Sitting Posture Monitoring System Based on a Low-Cost Load Cell Using Machine Learning.

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Application of Machine Learning Approaches for Classifying Sitting Posture Based on Force and Acceleration Sensors.

http://www.wikidata.org/entity/Q37404741

description

article científic

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article scientifique

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articolo scientifico

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artigo científico

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bilimsel makale

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scientific article published on 27 October 2016

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vedecký článok

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vetenskaplig artikel

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videnskabelig artikel

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vědecký článek

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name

Application of Machine Learnin ...... orce and Acceleration Sensors.

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Application of Machine Learnin ...... orce and Acceleration Sensors.

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type

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Application of Machine Learnin ...... orce and Acceleration Sensors.

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Application of Machine Learnin ...... orce and Acceleration Sensors.

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prefLabel

Application of Machine Learnin ...... orce and Acceleration Sensors.

@en

Application of Machine Learnin ...... orce and Acceleration Sensors.

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BioMed Research International

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Application of Machine Learnin ...... orce and Acceleration Sensors.

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Karin Schnüriger

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Matteo Tanadini

http://www.w3.org/2001/XMLSchema#string

Stefan Plüss

http://www.w3.org/2001/XMLSchema#string

P2860

Intradiscal pressure together with anthropometric data--a data set for the validation of models.

Identification of properties important to protein aggregation using feature selection.

Ergonomics of posture--review of various problems of standing and sitting posture.

In vivo spinal posture during upright and reclined sitting in an office chair

The Epidemiology of low back pain.

Are pressure measurements effective in the assessment of office chair comfort/discomfort? A review.

Evaluation of foot swelling and lower-limb temperatures in relation to leg activity during long-term seated office work.

Magnetic resonance imaging and stadiometric assessment of the lumbar discs after sitting and chair-care decompression exercise: a pilot study.

Prediction of function changes associated with single-point protein mutations using support vector machines (SVMs).

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5978489

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scholarly article

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10.1155/2016/5978489

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P407

P478

2016

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Silvio Lorenzetti

William R Taylor

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2016-10-27T00:00:00Z

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27868066

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machine learning

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5102712

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