Head motion classification using thread-based sensor and machine learning algorithm

Abstract Human machine interfaces that can track head motion will result in advances in physical rehabilitation, improved augmented reality/virtual reality systems, and aid in the study of human behavior. This paper presents a head position monitoring and classification system using thin flexible st...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Yiwen Jiang, Aydin Sadeqi, Eric L. Miller, Sameer Sonkusale
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/8d461e0b664540458cd64177afc9d49f
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:8d461e0b664540458cd64177afc9d49f
record_format	dspace
spelling	oai:doaj.org-article:8d461e0b664540458cd64177afc9d49f2021-12-02T13:23:58ZHead motion classification using thread-based sensor and machine learning algorithm10.1038/s41598-021-81284-72045-2322https://doaj.org/article/8d461e0b664540458cd64177afc9d49f2021-01-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-81284-7https://doaj.org/toc/2045-2322Abstract Human machine interfaces that can track head motion will result in advances in physical rehabilitation, improved augmented reality/virtual reality systems, and aid in the study of human behavior. This paper presents a head position monitoring and classification system using thin flexible strain sensing threads placed on the neck of an individual. A wireless circuit module consisting of impedance readout circuitry and a Bluetooth module records and transmits strain information to a computer. A data processing algorithm for motion recognition provides near real-time quantification of head position. Incoming data is filtered, normalized and divided into data segments. A set of features is extracted from each data segment and employed as input to nine classifiers including Support Vector Machine, Naive Bayes and KNN for position prediction. A testing accuracy of around 92% was achieved for a set of nine head orientations. Results indicate that this human machine interface platform is accurate, flexible, easy to use, and cost effective.Yiwen JiangAydin SadeqiEric L. MillerSameer SonkusaleNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Yiwen Jiang Aydin Sadeqi Eric L. Miller Sameer Sonkusale Head motion classification using thread-based sensor and machine learning algorithm
description	Abstract Human machine interfaces that can track head motion will result in advances in physical rehabilitation, improved augmented reality/virtual reality systems, and aid in the study of human behavior. This paper presents a head position monitoring and classification system using thin flexible strain sensing threads placed on the neck of an individual. A wireless circuit module consisting of impedance readout circuitry and a Bluetooth module records and transmits strain information to a computer. A data processing algorithm for motion recognition provides near real-time quantification of head position. Incoming data is filtered, normalized and divided into data segments. A set of features is extracted from each data segment and employed as input to nine classifiers including Support Vector Machine, Naive Bayes and KNN for position prediction. A testing accuracy of around 92% was achieved for a set of nine head orientations. Results indicate that this human machine interface platform is accurate, flexible, easy to use, and cost effective.
format	article
author	Yiwen Jiang Aydin Sadeqi Eric L. Miller Sameer Sonkusale
author_facet	Yiwen Jiang Aydin Sadeqi Eric L. Miller Sameer Sonkusale
author_sort	Yiwen Jiang
title	Head motion classification using thread-based sensor and machine learning algorithm
title_short	Head motion classification using thread-based sensor and machine learning algorithm
title_full	Head motion classification using thread-based sensor and machine learning algorithm
title_fullStr	Head motion classification using thread-based sensor and machine learning algorithm
title_full_unstemmed	Head motion classification using thread-based sensor and machine learning algorithm
title_sort	head motion classification using thread-based sensor and machine learning algorithm
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/8d461e0b664540458cd64177afc9d49f
work_keys_str_mv	AT yiwenjiang headmotionclassificationusingthreadbasedsensorandmachinelearningalgorithm AT aydinsadeqi headmotionclassificationusingthreadbasedsensorandmachinelearningalgorithm AT ericlmiller headmotionclassificationusingthreadbasedsensorandmachinelearningalgorithm AT sameersonkusale headmotionclassificationusingthreadbasedsensorandmachinelearningalgorithm
_version_	1718393165363281920

Head motion classification using thread-based sensor and machine learning algorithm

Ejemplares similares