An Alarm System Based on BP Neural Network Algorithm for the Detection of Falls to Elderly Person

Wenhui Chen; Xueming Wang; Junfei Chen; Zhiyong Ding; Jianying Li; Bo Li

doi:10.1007/978-3-030-67514-1_45

An Alarm System Based on BP Neural Network Algorithm for the Detection of Falls to Elderly Person

Wenhui Chen
, Xueming Wang
, Junfei Chen
, Zhiyong Ding
, Jianying Li
, Bo Li

School of Electronics and Information

Northwestern Polytechnical University Xian

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

With the increase in the elderly population, people pay more and more attention to the harm caused by falls. When people reach old age, various functions of the body will degrade to a certain extent. If the elderly fall down, it may endanger their physical and mental health. In view of the above problems, this system designed a elderly fall detection and alarm system based on the reverse neural network algorithm, specifically using MPU6050 sensor to detect human posture data, the control module using the algorithm for real-time judgment, if the fall behavior, the control alarm module to send alarm messages. This system can be used in nursing home health monitoring system, intelligent home system in the detection subsystem and other intelligent medical aspects, can be used in various aspects to protect the health of the elderly, reduce the risk of accidental injury.

Original language	English
Title of host publication	IoT as a Service - 6th EAI International Conference, IoTaaS 2020, Proceedings
Editors	Bo Li, Changle Li, Mao Yang, Zhongjiang Yan, Jie Zheng
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	571-581
Number of pages	11
ISBN (Print)	9783030675134
DOIs	https://doi.org/10.1007/978-3-030-67514-1_45
State	Published - 2021
Event	6th EAI International Conference on IoT as a Service, IoTaaS 2020 - Xi'an, China Duration: 19 Nov 2020 → 20 Nov 2020

Publication series

Name	Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
Volume	346
ISSN (Print)	1867-8211
ISSN (Electronic)	1867-822X

Conference

Conference	6th EAI International Conference on IoT as a Service, IoTaaS 2020
Country/Territory	China
City	Xi'an
Period	19/11/20 → 20/11/20

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

BP neural network
Falls in older people
MPU6050 sensor
Wisdom care

Access to Document

10.1007/978-3-030-67514-1_45

Cite this

Chen, W., Wang, X., Chen, J., Ding, Z., Li, J., & Li, B. (2021). An Alarm System Based on BP Neural Network Algorithm for the Detection of Falls to Elderly Person. In B. Li, C. Li, M. Yang, Z. Yan, & J. Zheng (Eds.), IoT as a Service - 6th EAI International Conference, IoTaaS 2020, Proceedings (pp. 571-581). (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; Vol. 346). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-67514-1_45

Chen, Wenhui ; Wang, Xueming ; Chen, Junfei et al. / An Alarm System Based on BP Neural Network Algorithm for the Detection of Falls to Elderly Person. IoT as a Service - 6th EAI International Conference, IoTaaS 2020, Proceedings. editor / Bo Li ; Changle Li ; Mao Yang ; Zhongjiang Yan ; Jie Zheng. Springer Science and Business Media Deutschland GmbH, 2021. pp. 571-581 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST).

@inproceedings{d2d7fc97d157480d8d472fcc91b16712,

title = "An Alarm System Based on BP Neural Network Algorithm for the Detection of Falls to Elderly Person",

abstract = "With the increase in the elderly population, people pay more and more attention to the harm caused by falls. When people reach old age, various functions of the body will degrade to a certain extent. If the elderly fall down, it may endanger their physical and mental health. In view of the above problems, this system designed a elderly fall detection and alarm system based on the reverse neural network algorithm, specifically using MPU6050 sensor to detect human posture data, the control module using the algorithm for real-time judgment, if the fall behavior, the control alarm module to send alarm messages. This system can be used in nursing home health monitoring system, intelligent home system in the detection subsystem and other intelligent medical aspects, can be used in various aspects to protect the health of the elderly, reduce the risk of accidental injury.",

keywords = "BP neural network, Falls in older people, MPU6050 sensor, Wisdom care",

author = "Wenhui Chen and Xueming Wang and Junfei Chen and Zhiyong Ding and Jianying Li and Bo Li",

note = "Publisher Copyright: {\textcopyright} 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.; 6th EAI International Conference on IoT as a Service, IoTaaS 2020 ; Conference date: 19-11-2020 Through 20-11-2020",

year = "2021",

doi = "10.1007/978-3-030-67514-1\_45",

language = "英语",

isbn = "9783030675134",

series = "Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "571--581",

editor = "Bo Li and Changle Li and Mao Yang and Zhongjiang Yan and Jie Zheng",

booktitle = "IoT as a Service - 6th EAI International Conference, IoTaaS 2020, Proceedings",

}

Chen, W, Wang, X, Chen, J, Ding, Z, Li, J & Li, B 2021, An Alarm System Based on BP Neural Network Algorithm for the Detection of Falls to Elderly Person. in B Li, C Li, M Yang, Z Yan & J Zheng (eds), IoT as a Service - 6th EAI International Conference, IoTaaS 2020, Proceedings. Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, vol. 346, Springer Science and Business Media Deutschland GmbH, pp. 571-581, 6th EAI International Conference on IoT as a Service, IoTaaS 2020, Xi'an, China, 19/11/20. https://doi.org/10.1007/978-3-030-67514-1_45

An Alarm System Based on BP Neural Network Algorithm for the Detection of Falls to Elderly Person. / Chen, Wenhui; Wang, Xueming; Chen, Junfei et al.
IoT as a Service - 6th EAI International Conference, IoTaaS 2020, Proceedings. ed. / Bo Li; Changle Li; Mao Yang; Zhongjiang Yan; Jie Zheng. Springer Science and Business Media Deutschland GmbH, 2021. p. 571-581 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; Vol. 346).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - An Alarm System Based on BP Neural Network Algorithm for the Detection of Falls to Elderly Person

AU - Chen, Wenhui

AU - Wang, Xueming

AU - Chen, Junfei

AU - Ding, Zhiyong

AU - Li, Jianying

AU - Li, Bo

PY - 2021

Y1 - 2021

N2 - With the increase in the elderly population, people pay more and more attention to the harm caused by falls. When people reach old age, various functions of the body will degrade to a certain extent. If the elderly fall down, it may endanger their physical and mental health. In view of the above problems, this system designed a elderly fall detection and alarm system based on the reverse neural network algorithm, specifically using MPU6050 sensor to detect human posture data, the control module using the algorithm for real-time judgment, if the fall behavior, the control alarm module to send alarm messages. This system can be used in nursing home health monitoring system, intelligent home system in the detection subsystem and other intelligent medical aspects, can be used in various aspects to protect the health of the elderly, reduce the risk of accidental injury.

AB - With the increase in the elderly population, people pay more and more attention to the harm caused by falls. When people reach old age, various functions of the body will degrade to a certain extent. If the elderly fall down, it may endanger their physical and mental health. In view of the above problems, this system designed a elderly fall detection and alarm system based on the reverse neural network algorithm, specifically using MPU6050 sensor to detect human posture data, the control module using the algorithm for real-time judgment, if the fall behavior, the control alarm module to send alarm messages. This system can be used in nursing home health monitoring system, intelligent home system in the detection subsystem and other intelligent medical aspects, can be used in various aspects to protect the health of the elderly, reduce the risk of accidental injury.

KW - BP neural network

KW - Falls in older people

KW - MPU6050 sensor

KW - Wisdom care

UR - https://www.scopus.com/pages/publications/85101315016

U2 - 10.1007/978-3-030-67514-1_45

DO - 10.1007/978-3-030-67514-1_45

M3 - 会议稿件

AN - SCOPUS:85101315016

SN - 9783030675134

T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST

SP - 571

EP - 581

BT - IoT as a Service - 6th EAI International Conference, IoTaaS 2020, Proceedings

A2 - Li, Bo

A2 - Li, Changle

A2 - Yang, Mao

A2 - Yan, Zhongjiang

A2 - Zheng, Jie

PB - Springer Science and Business Media Deutschland GmbH

T2 - 6th EAI International Conference on IoT as a Service, IoTaaS 2020

Y2 - 19 November 2020 through 20 November 2020

ER -

Chen W, Wang X, Chen J, Ding Z, Li J , Li B. An Alarm System Based on BP Neural Network Algorithm for the Detection of Falls to Elderly Person. In Li B, Li C, Yang M, Yan Z, Zheng J, editors, IoT as a Service - 6th EAI International Conference, IoTaaS 2020, Proceedings. Springer Science and Business Media Deutschland GmbH. 2021. p. 571-581. (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST). doi: 10.1007/978-3-030-67514-1_45

An Alarm System Based on BP Neural Network Algorithm for the Detection of Falls to Elderly Person

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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