An Exploration of Fall-Down Detection by Smart Wristband

2014 ◽  
Vol 687-691 ◽  
pp. 805-808 ◽  
Author(s):  
Song Yuan Li ◽  
An Yu Ying ◽  
Ming Min Yuan ◽  
Hong Shen ◽  
Tian Zhou Chen ◽  
...  
Keyword(s):  
Medical Care ◽  
Everyday Life ◽  
Care Center ◽  
Wearable Devices ◽  
Communication Interface ◽  
Interactive Interface ◽  
Smart Wearable ◽  
Novel Algorithm

Smart wristband has recently emerged as one of the most popular smart wearable devices. With the help of smart wristbands, we can easily gather and record the user's data of everyday life including exercising, sleeping, diet, etc. In this work, we explore the feature of falls of the old and redesign the smart wristband to detect their movement. We propose a novel algorithm to judge whether he/she stops in a sudden, then produce vibrations through the man-machine interactive interface that provided by the smart wristband. The wearer can judge whether it is misjudged if he is still in conscious, if so he can press a button to stop the shaking or the wristband will give an alarm through communication interface to the medical care center.

scholarly journals Smart Wearable Sensors Based on Triboelectric Nanogenerator for Personal Healthcare Monitoring

Micromachines ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 352
Author(s):  
Ruonan Li ◽  
Xuelian Wei ◽  
Jiahui Xu ◽  
Junhuan Chen ◽  
Bin Li ◽  
...  
Keyword(s):  
Medical Care ◽  
Health Monitoring ◽  
Wearable Sensors ◽  
The Elderly ◽  
The Body ◽  
Assessment System ◽  
Triboelectric Nanogenerator ◽  
Personal Healthcare ◽  
Healthcare Monitoring ◽  
Smart Wearable

Accurate monitoring of motion and sleep states is critical for human health assessment, especially for a healthy life, early diagnosis of diseases, and medical care. In this work, a smart wearable sensor (SWS) based on a dual-channel triboelectric nanogenerator was presented for a real-time health monitoring system. The SWS can be worn on wrists, ankles, shoes, or other parts of the body and cloth, converting mechanical triggers into electrical output. By analyzing these signals, the SWS can precisely and constantly monitor and distinguish various motion states, including stepping, walking, running, and jumping. Based on the SWS, a fall-down alarm system and a sleep quality assessment system were constructed to provide personal healthcare monitoring and alert family members or doctors via communication devices. It is important for the healthy growth of the young and special patient groups, as well as for the health monitoring and medical care of the elderly and recovered patients. This work aimed to broaden the paths for remote biological movement status analysis and provide diversified perspectives for true-time and long-term health monitoring, simultaneously.

Review on Reliable and Quality Wearable Healthcare Device (WHD)

2021 ◽  
Vol 10 (4) ◽  
pp. 1-25
Author(s):  
Nimi W. S. ◽  
P. Subha Hency Jose ◽  
Jegan R.
Keyword(s):  
Health Monitoring ◽  
Wearable Devices ◽  
Health Condition ◽  
Wearable Device ◽  
Smart Device ◽  
Signal Acquisition ◽  
Medical Practitioners ◽  
Quality Signal ◽  
Patient Health ◽  
Smart Wearable

This paper presents a brief review on present developments in wearable devices and their importance in healthcare networks. The state-of-the-art system architecture on wearable healthcare devices and their design techniques are reviewed and becomes an essential step towards developing a smart device for various biomedical applications which includes diseases classifications and detection, analyzing nature of the bio signals, vital parameters measurement, and e-health monitoring through noninvasive method. From the review on latest published research papers on medical wearable device and bio signal analysis, it can be concluded that it is more important and very essential to design and develop a smart wearable device in healthcare environment for quality signal acquisition and e-health monitoring which leads to effective measures of multiparameter extractions. This will help the medical practitioners to understand the nature of patient health condition easily by visualizing a quality signal by smart wearable devices.

scholarly journals ECONOMIC AND HOUSEHOLD ARRANGEMENT OF SPECIAL SETTLERS-CHECHENS IN ZYRYANOVSKY DISTRICT OF EAST KAZAKHSTAN REGION

2020 ◽  
Vol 66 (3) ◽  
Author(s):  
А.Т. Kazbekova ◽  
Keyword(s):  
Medical Care ◽  
Everyday Life ◽  
Living Conditions ◽  
Housing Conditions ◽  
Host Society ◽  
Archival Documents ◽  
East Kazakhstan ◽  
Internal Migrations ◽  
First Time ◽  
Household Arrangement

The article is based on the analysis of archival documents introduced into scientific circulation for the first time and examines the process of economic and labor settlement of special settlers-Chechens who were subjected to repeated internal resettlement in the Zyryanovsky district (now the Altai district) East Kazakhstan region in the first years of settlement. Тhe study identified the main problems faced by special settlers-Chechens in the Zyryanov district. Social and living conditions of special settlers were reconstructed. Housing conditions, medical care and everyday life are considered. On the basis of the studied materials, the attitude of special settlers to new living conditions and the host society to the special component is shown. The author, relying on archival materials, comes to the conclusion that repeated internal migrations of special settlers-Chechens did not solve social problems.

scholarly journals Application of Real-Time Visual Feedback System in Balance Training of the Center of Pressure with Smart Wearable Devices

2020 ◽  
Author(s):  
I-Lin Wang ◽  
Li-I Wang ◽  
Yang Liu ◽  
Shi-Jie Xue ◽  
Rui Hu ◽  
...  
Keyword(s):  
Real Time ◽  
Visual Feedback ◽  
Postural Sway ◽  
Center Of Pressure ◽  
Balance Training ◽  
Training Group ◽  
Wearable Devices ◽  
Control Group ◽  
Feedback Training ◽  
Smart Wearable

Abstract Background: Visual feedback from the center of pressure (COP) on the benefits of standing quietly remains controversial. The study was to investigate the adaptive effect of COP real-time visual feedback training provided by smart wearable devices on standing in silence. Methods: Thirty healthy female college students were randomly divided into three groups (visual feedback balance training group (VFT), non-visual feedback balance training group (NVFT) and control group (CG)) .Two force plates were used to calculate the coordinates of COP anteroposterior (COPAP) and COP mediolateral (COPML).The motion analysis system is used to calculate the coordinates of the center of mass in two directions. Enhanced visual feedback on the screen in the form of fluctuating in different directions, VFT received real-time visual feedback from Podoon APP for training, the NVFT only performs open eye balance without receiving real-time visual feedback. The CG group did not receive any visual feedback. The training lasted 4 weeks, the training lasts 30 minutes at an interval of 1 days. Results: After four weeks of balance training, the results showed that visual feedback training can improve the stability of human posture control by one leg stance and tandem stance static balance training on VFT intelligent App. The parameters of COPML/AP max displacement, COPML/AP velocity and COP radius and COP area in the VFT were significantly increased (p＜0.05).Conclusion: The conclusion shows that COP real-time visual feedback training provided by smart wearable devices can reduce postural sway better and improve body balance ability than general training when standing quietly.

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