AI Medical Compendium Topic

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Monitoring, Ambulatory

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Wearable-Enabled Algorithms for the Estimation of Parkinson's Symptoms Evaluated in a Continuous Home Monitoring Setting Using Inertial Sensors.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Motor symptoms such as tremor and bradykinesia can develop concurrently in Parkinson's disease; thus, the ideal home monitoring system should be capable of tracking symptoms continuously despite background noise from daily activities. The goal of thi...

Cough-DL: A Deep Learning Model for Ear-Worn Cough Detection.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Cough serves as a crucial bio-marker for evaluation and monitoring of pulmonary conditions. With growing interest towards automatic cough detection systems, it's important to acknowledge the existing hurdles on the way for a robust cough counter. The...

Automated Detection of In-Home Activities with Ultra-Wideband Sensors.

Sensors (Basel, Switzerland)
As Canada's population of older adults rises, the need for aging-in-place solutions is growing due to the declining quality of long-term-care homes and long wait times. While the current standards include questionnaire-based assessments for monitorin...

Analysis of In-Home Movement Patterns for Depression Assessment in Older Adults - A Feasibility Study.

Studies in health technology and informatics
Depression significantly impacts the wellbeing of older Australians, posing considerable challenges to their overall quality of life. This study aimed to detect in-home movement patterns of participants that could be indicative of depressive states. ...

Towards the automatic detection of activities of daily living using eye-movement and accelerometer data with neural networks.

Computers in biology and medicine
Early diagnosis of neurodegenerative diseases, such as Alzheimer's disease, improves treatment and care outcomes for patients. Early signs of cognitive decline can be detected using functional scales, which are written records completed by a clinicia...

Freezing of gait detection: The effect of sensor type, position, activities, datasets, and machine learning model.

Journal of Parkinson's disease
BackgroundFreezing of gait (FoG) is a complex, frequent, and disabling motor symptom of Parkinson's disease (PD). Wearable technology has the potential to improve FoG assessment by providing objective, quantitative, and continuous monitoring.Objectiv...

Innovative Dual-Decoupling CNN With Layer-Wise Temporal-Spatial Attention for Sensor-Based Human Activity Recognition.

IEEE journal of biomedical and health informatics
Human Activity Recognition (HAR) is essential for monitoring and analyzing human behavior, particularly in health applications such as fall detection and chronic disease management. Traditional methods, even those incorporating attention mechanisms, ...

Human Activity Recognition Using Deep Residual Convolutional Network Based on Wearable Sensors.

IEEE journal of biomedical and health informatics
Human activity recognition (HAR) can play a vital role in biomedical and health informatics by enabling the monitoring of human daily activities and health behaviors. Accurate HAR can provide valuable insights into patients' physical activity levels,...

Automated Fall Detection in Smart Homes Using Multiple Radars and Machine Learning Classifiers.

Studies in health technology and informatics
Falls pose a significant risk, especially among elderly persons. Recently, radar sensors have been explored for fall detection. In this study, an attempt has been made to classify fall detection using multiple radars, machine learning (ML) classifier...

Development of an Assistance Robot for Fall Detection and Reporting in Healthcare.

Studies in health technology and informatics
Falls pose a substantial risk to elderly individuals, especially those over 65, often leading to severe consequences. This project investigates the potential of the tēmi robot for fall detection in care facilities and its integration into a simulated...