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Activities of Daily Living

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Spatio-Temporal Abnormal Behavior Prediction in Elderly Persons Using Deep Learning Models.

Sensors (Basel, Switzerland)
The ability to identify and accurately predict abnormal behavior is important for health monitoring systems in smart environments. Specifically, for elderly persons wishing to maintain their independence and comfort in their living spaces, abnormal b...

Caregiver perspectives on a smart home-based socially assistive robot for individuals with Alzheimer's disease and related dementia.

Disability and rehabilitation. Assistive technology
: Innovative assistive technology can address aging-in-place and caregiving needs of individuals with Alzheimer's disease and related dementia (ADRD). The purpose of this study was to beta-test a novel socially assistive robot (SAR) with a cohort of ...

Improving Grasp Function After Spinal Cord Injury With a Soft Robotic Glove.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
People with tetraplegia resulting from spinal cord injury experience debilitating hand impairments that may lead to lifelong dependence on others to perform activities of daily living. Wearable robotic devices that actively support hand function duri...

Improving energy expenditure estimates from wearable devices: A machine learning approach.

Journal of sports sciences
A means of quantifying continuous, free-living energy expenditure (EE) would advance the study of bioenergetics. The aim of this study was to apply a non-linear, machine learning algorithm (random forest) to predict minute level EE for a range of act...

A Video-Based DT-SVM School Violence Detecting Algorithm.

Sensors (Basel, Switzerland)
School bullying is a serious problem among teenagers. School violence is one type of school bullying and considered to be the most harmful. As AI (Artificial Intelligence) techniques develop, there are now new methods to detect school violence. This ...

A Multi-task Learning Model for Daily Activity Forecast in Smart Home.

Sensors (Basel, Switzerland)
Daily activity forecasts play an important role in the daily lives of residents in smart homes. Category forecasts and occurrence time forecasts of daily activity are two key tasks. Category forecasts of daily activity are correlated with occurrence ...

A Study on the Application of Convolutional Neural Networks to Fall Detection Evaluated with Multiple Public Datasets.

Sensors (Basel, Switzerland)
Due to the repercussion of falls on both the health and self-sufficiency of older people and on the financial sustainability of healthcare systems, the study of wearable fall detection systems (FDSs) has gained much attention during the last years. T...

Performance Analysis of Boosting Classifiers in Recognizing Activities of Daily Living.

International journal of environmental research and public health
Physical activity is essential for physical and mental health, and its absence is highly associated with severe health conditions and disorders. Therefore, tracking activities of daily living can help promote quality of life. Wearable sensors in this...

Evaluating the sit-to-stand transfer assistance from a smart walker in older adults with motor impairments.

Geriatrics & gerontology international
AIM: To evaluate the effectiveness and user satisfaction with the sit-to-stand (STS) assistance system of a smart walker (SW), and to identify factors associated with them in potential users.

Does robot-assisted gait training improve mobility, activities of daily living and quality of life in stroke? A single-blinded, randomized controlled trial.

Acta neurologica Belgica
The purpose of this study was to investigate the effects of robot-assisted gait training (RAGT) on mobility, activities of daily living (ADLs), and quality of life (QoL) in stroke rehabilitation. Fifty-one stroke patients randomly assigned to Group 1...