Hybrid feature fusion for classification optimization of short ECG segment in IoT based intelligent healthcare system

<abstract> <p>Rehabilitation engineering is playing a more vital role in the field of healthcare for humanity. It is providing many assistive devices to diplegia patients (The patients whose conditions are weak in terms of muscle mobility on both sides of the body and their paralyzing effects are high either in the arms or in the legs). Therefore, in order to rehabilitate such types of patients, an intelligent healthcare system is proposed in this research. The electric sticks and chairs are also a type of this system which was used previously to facilitate the diplegia patients. It is worth noting that a voice recognition system along with wireless control feature has been integrated intelligently in the proposed healthcare system in order to replace the common and conventional assistive tools for diplegia patients. These features will make the proposed system more user friendly, convenient and comfortable. The voice recognition system has been used for movements of system in any desired direction along with the ultrasonic sensor and light detecting technology. These sensors detect the obstacles and low light environment intelligently during the movement of the wheelchair and then take the necessary actions accordingly.</p> </abstract>

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Development of intelligent healthcare system based on ambulatory blood pressure measuring device

Neural Computing and Applications ◽

10.1007/s00521-020-05114-z ◽

2020 ◽

Author(s):

Sung-Jong Eun ◽

JungYoon Kim

Keyword(s):

Blood Pressure ◽

Healthcare System ◽

Ambulatory Blood Pressure ◽

Measuring Device ◽

Intelligent Healthcare ◽

Pressure Measuring Device ◽

Blood Pressure Measuring Device

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Fog computing-based intelligent healthcare system for the detection and prevention of mosquito-borne diseases

Computers in Human Behavior ◽

10.1016/j.chb.2018.12.009 ◽

2019 ◽

Vol 100 ◽

pp. 275-285 ◽

Cited By ~ 16

Author(s):

V. Vijayakumar ◽

D. Malathi ◽

V. Subramaniyaswamy ◽

P. Saravanan ◽

R. Logesh

Keyword(s):

Healthcare System ◽

Fog Computing ◽

Intelligent Healthcare

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An intelligent healthcare system for optimized breast cancer diagnosis using harmony search and simulated annealing (HS-SA) algorithm

Informatics in Medicine Unlocked ◽

10.1016/j.imu.2020.100408 ◽

2020 ◽

Vol 21 ◽

pp. 100408

Author(s):

Tawseef Ayoub Shaikh ◽

Rashid Ali

Keyword(s):

Breast Cancer ◽

Simulated Annealing ◽

Healthcare System ◽

Cancer Diagnosis ◽

Harmony Search ◽

Breast Cancer Diagnosis ◽

Intelligent Healthcare

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Intelligent Healthcare System for Recuperation and Inoculation of Communicable Diseases

Journal of Physics Conference Series ◽

10.1088/1742-6596/2115/1/012037 ◽

2021 ◽

Vol 2115 (1) ◽

pp. 012037

Author(s):

Sarika Jay ◽

B V A N S S Prabhakar Rao

Keyword(s):

Healthcare System ◽

Communicable Disease ◽

Human Life ◽

Communicable Diseases ◽

Human Interaction ◽

Automated System ◽

Common People ◽

Appropriate Treatment ◽

Intelligent Healthcare

Abstract Human life gets interrupted a lot when a communicable disease starts in a society. People are alerted a lot on a different basis and eventually, it leads to difficulty for continuing their normal life. This paper is focused on a communicable disease, the COVID-19, which gave an outbreak for all world counties into a state where their fellow human had to stop their daily job and stay back at home. Common people find it difficult to get treatment when they are identified as positive and also most of them lack the awareness of post covid recovery. The idea of this work is to create a healthcare system that initiates right from the covid test, appropriate treatment according to severity, post-recovery, and vaccination awareness and jabs. These units will have less human interaction and they will be fully automated till in need of pure doctor consultation. The automated system is programmed to identify the infection, its severity and prescribe the treatment accordingly, and follow up recovery needs. On-side, automated vaccination system will allow direct walk-in, identify the customer and do the needful.

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Automatic Emotion Perception Using Eye Movement Information for E-Healthcare Systems

Sensors ◽

10.3390/s18092826 ◽

2018 ◽

Vol 18 (9) ◽

pp. 2826 ◽

Cited By ~ 7

Author(s):

Yang Wang ◽

Zhao Lv ◽

Yongjun Zheng

Keyword(s):

Eye Movement ◽

Healthcare System ◽

Emotional State ◽

Feature Fusion ◽

Emotion Perception ◽

Emotional States ◽

Time Frequency ◽

Promising Tool ◽

Novel Approach ◽

Level Fusion

Facing the adolescents and detecting their emotional state is vital for promoting rehabilitation therapy within an E-Healthcare system. Focusing on a novel approach for a sensor-based E-Healthcare system, we propose an eye movement information-based emotion perception algorithm by collecting and analyzing electrooculography (EOG) signals and eye movement video synchronously. Specifically, we extract the time-frequency eye movement features by firstly applying the short-time Fourier transform (STFT) to raw multi-channel EOG signals. Subsequently, in order to integrate time domain eye movement features (i.e., saccade duration, fixation duration, and pupil diameter), we investigate two feature fusion strategies: feature level fusion (FLF) and decision level fusion (DLF). Recognition experiments have been also performed according to three emotional states: positive, neutral, and negative. The average accuracies are 88.64% (the FLF method) and 88.35% (the DLF with maximal rule method), respectively. Experimental results reveal that eye movement information can effectively reflect the emotional state of the adolescences, which provides a promising tool to improve the performance of the E-Healthcare system.

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