Wise Information Technology of Med: Human Pose Recognition in Elderly Care

The growing problem of aging has led to a social concern on how to take care of the elderly living alone. Many traditional methods based on visual cameras have been used in elder monitoring. However, these methods are difficult to be applied in daily life, limited by high storage space with the came...

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Autores principales:	Difei Xu, Xuelei Qi, Chen Li, Ziheng Sheng, Hailong Huang
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	elderly care human pose recognition feature extraction PCA-LSTM recognition gaussian kernel function classification Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/5df6b2fbaf1f4530847cf7c12160f1a7
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id	oai:doaj.org-article:5df6b2fbaf1f4530847cf7c12160f1a7
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spelling	oai:doaj.org-article:5df6b2fbaf1f4530847cf7c12160f1a72021-11-11T19:07:54ZWise Information Technology of Med: Human Pose Recognition in Elderly Care10.3390/s212171301424-8220https://doaj.org/article/5df6b2fbaf1f4530847cf7c12160f1a72021-10-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/21/7130https://doaj.org/toc/1424-8220The growing problem of aging has led to a social concern on how to take care of the elderly living alone. Many traditional methods based on visual cameras have been used in elder monitoring. However, these methods are difficult to be applied in daily life, limited by high storage space with the camera, low-speed information processing, sensitivity to lighting, the blind area in vision, and the possibility of revealing privacy. Therefore, wise information technology of the Med System based on the micro-Doppler effect and Ultra Wide Band (UWB) radar for human pose recognition in the elderly living alone is proposed to effectively identify and classify the human poses in static and moving conditions. In recognition processing, an improved PCA-LSTM approach is proposed by combing with the Principal Component Analysis (PCA) and Long Short Term Memory (LSTM) to integrate the micro-Doppler features and time sequence of the human body to classify and recognize the human postures. Moreover, the classification accuracy with different kernel functions in the Support Vector Machine (SVM) is also studied. In the real experiment, there are two healthy men and one woman (22–26 years old) selected to imitate the movements of the elderly and slowly perform five postures (from sitting to standing, from standing to sitting, walking in place, falling and boxing). The experimental results show that the resolution of the entire system for the five actions reaches 99.1% in the case of using Gaussian kernel function, so the proposed method is effective and the Gaussian kernel function is suitable for human pose recognition.Difei XuXuelei QiChen LiZiheng ShengHailong HuangMDPI AGarticleelderly carehuman pose recognitionfeature extractionPCA-LSTM recognitiongaussian kernel function classificationChemical technologyTP1-1185ENSensors, Vol 21, Iss 7130, p 7130 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	elderly care human pose recognition feature extraction PCA-LSTM recognition gaussian kernel function classification Chemical technology TP1-1185
spellingShingle	elderly care human pose recognition feature extraction PCA-LSTM recognition gaussian kernel function classification Chemical technology TP1-1185 Difei Xu Xuelei Qi Chen Li Ziheng Sheng Hailong Huang Wise Information Technology of Med: Human Pose Recognition in Elderly Care
description	The growing problem of aging has led to a social concern on how to take care of the elderly living alone. Many traditional methods based on visual cameras have been used in elder monitoring. However, these methods are difficult to be applied in daily life, limited by high storage space with the camera, low-speed information processing, sensitivity to lighting, the blind area in vision, and the possibility of revealing privacy. Therefore, wise information technology of the Med System based on the micro-Doppler effect and Ultra Wide Band (UWB) radar for human pose recognition in the elderly living alone is proposed to effectively identify and classify the human poses in static and moving conditions. In recognition processing, an improved PCA-LSTM approach is proposed by combing with the Principal Component Analysis (PCA) and Long Short Term Memory (LSTM) to integrate the micro-Doppler features and time sequence of the human body to classify and recognize the human postures. Moreover, the classification accuracy with different kernel functions in the Support Vector Machine (SVM) is also studied. In the real experiment, there are two healthy men and one woman (22–26 years old) selected to imitate the movements of the elderly and slowly perform five postures (from sitting to standing, from standing to sitting, walking in place, falling and boxing). The experimental results show that the resolution of the entire system for the five actions reaches 99.1% in the case of using Gaussian kernel function, so the proposed method is effective and the Gaussian kernel function is suitable for human pose recognition.
format	article
author	Difei Xu Xuelei Qi Chen Li Ziheng Sheng Hailong Huang
author_facet	Difei Xu Xuelei Qi Chen Li Ziheng Sheng Hailong Huang
author_sort	Difei Xu
title	Wise Information Technology of Med: Human Pose Recognition in Elderly Care
title_short	Wise Information Technology of Med: Human Pose Recognition in Elderly Care
title_full	Wise Information Technology of Med: Human Pose Recognition in Elderly Care
title_fullStr	Wise Information Technology of Med: Human Pose Recognition in Elderly Care
title_full_unstemmed	Wise Information Technology of Med: Human Pose Recognition in Elderly Care
title_sort	wise information technology of med: human pose recognition in elderly care
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/5df6b2fbaf1f4530847cf7c12160f1a7
work_keys_str_mv	AT difeixu wiseinformationtechnologyofmedhumanposerecognitioninelderlycare AT xueleiqi wiseinformationtechnologyofmedhumanposerecognitioninelderlycare AT chenli wiseinformationtechnologyofmedhumanposerecognitioninelderlycare AT zihengsheng wiseinformationtechnologyofmedhumanposerecognitioninelderlycare AT hailonghuang wiseinformationtechnologyofmedhumanposerecognitioninelderlycare
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Wise Information Technology of Med: Human Pose Recognition in Elderly Care

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