2018 Eighth International Conference on Information Science and Technology (ICIST) 2018
DOI: 10.1109/icist.2018.8426159
|View full text |Cite
|
Sign up to set email alerts
|

The Study of the Electrocardiography Monitoring for the Elderly Based on Smart Clothes

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
4
1

Citation Types

0
8
0

Year Published

2019
2019
2022
2022

Publication Types

Select...
4
3

Relationship

0
7

Authors

Journals

citations
Cited by 8 publications
(8 citation statements)
references
References 9 publications
0
8
0
Order By: Relevance
“…The third category of home-based ECG monitoring involves elderly monitoring; several systems have been developed, among which include [24,[113][114][115]. Mena et al [115] proposed a mobile personal elderly health monitoring for automated classification of ECG signals using machine learning techniques.…”
Section: Context-aware Ecg Monitoring Systemsmentioning
confidence: 99%
See 3 more Smart Citations
“…The third category of home-based ECG monitoring involves elderly monitoring; several systems have been developed, among which include [24,[113][114][115]. Mena et al [115] proposed a mobile personal elderly health monitoring for automated classification of ECG signals using machine learning techniques.…”
Section: Context-aware Ecg Monitoring Systemsmentioning
confidence: 99%
“…A wearable ECG monitor is integrated with a self-designed wireless sensor for ECG signal acquisition and is used with a native, purposely designed smartphone application. Other alternative studies [24,113,114] introduced various smart features to ECG monitoring systems for the elderly people. Smartness is introduced in the elderly monitoring environment where a novel monitoring framework is proposed in [113] to provide flexibility and enable interoperability between a myriad of healthcare monitoring devices.…”
Section: Context-aware Ecg Monitoring Systemsmentioning
confidence: 99%
See 2 more Smart Citations
“…According to the obtained results, a specific circuit optimization method was proposed. Moreover, these results could be exploited by numerous real applications, such as drivers’ safety [ 21 , 28 , 29 , 30 , 31 , 32 , 33 ], remote monitoring of the elderly [ 34 , 35 , 36 , 37 ], sleep monitoring [ 20 , 38 , 39 , 40 , 41 , 42 ], human identification [ 43 , 44 , 45 , 46 ] and emotion recognition [ 47 , 48 , 49 , 50 ].…”
Section: Introductionmentioning
confidence: 99%