Biomedical and Health Sciences
The data collection questionnaire consisted of two sections. One section involved the collection of data via Google Forms questionnaires, and the other involved the collection of WhatsApp voice samples. There were three subsections in the questionnaire section. The first consisted of the individual's basic information, such as email address, name, and identification number. The second was the personal health questionnaire depression scale (PHQ8), which included 8 groups of statements, and the third was the Beck Depression Inventory-II, which contained 21 groups of statements.
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805 Views
In this paper, we propose a mecanum-built perturbation-based balance training (M-PBT) device to train a person with a neurological disorder or an elderly person to regain their deteriorated motor adaptive skill to prevent a fall. The following are the features of the device: to challenge the trainees to predict the fall direction, the device (1) generates multi-directional fall options that simulate a slip and trip scenario; (2) is portable to assist in-patients’ rehabilitation; (3) possesses qualities of modified constraint-induced movement therapy (mCIMT).
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108 Views
In this paper, we propose a mecanum-built perturbation-based balance training (M-PBT) device to train a person with a neurological disorder or an elderly person to regain their deteriorated motor adaptive skill to prevent a fall. The following are the features of the device: to challenge the trainees to predict the fall direction, the device (1) generates multi-directional fall options that simulate a slip and trip scenario; (2) is portable to assist in-patients’ rehabilitation; (3) possesses qualities of modified constraint-induced movement therapy (mCIMT).
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4 Views
The dataset included 640 patients' vital records, which ranged in age from 18 to 60.
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18 Views
Personal assistive devices for rehabilitation will be in increasing demand during the coming decades due to demographic change, i.e., an aging society. Among the elderly population, difficulty in walking is the most common problem. Even though there are commercially available lower limb exoskeleton systems, the coordination between user and device still needs to be improved to achieve versatile personalized gait. To tackle this issue, an advanced EXOskeleton framework for Versatile personalized gaIt generation with a Seamless user-exo interface (called "EXOVIS") is proposed in this study.
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405 Views
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619 Views
Food computing is currently a fast-growing field of research. Web mining and content analysis are also increasingly essential in this field, especially for recognising food entities.
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949 Views
This dataset contains two folders. One folder contains images to be used for image classification and the other folder is used for semantic segmentation.
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129 Views
This dataset is for robust sEMG-based intention recognition with respect to upper-limb positions.
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24 Views
Gestational diabetes is a type of high blood sugar that develops during pregnancy. It can occur at any stage of pregnancy and cause problems for both the mother and the baby, during and after birth. The risks can be reduced if they are early detected and managed, especially in areas where only periodic tests of pregnant women are available. Intelligent systems designed by machine learning algorithms are remodelling all fields of our lives, including the healthcare system. This study proposes a combined prediction model to diagnose gestational diabetes.
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3755 Views