AIMC Topic: Activities of Daily Living
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Prediction of the functional outcome of intensive inpatient rehabilitation after stroke using machine learning methods.
Scientific reports
May 8, 2025
An accurate and reliable functional prognosis is vital to stroke patients addressing rehabilitation, to their families, and healthcare providers. This study aimed at developing and validating externally patient-wise prognostic models of the global fu...
Humanoid robots for assisting people with physical disabilities in activities of daily living: A scoping review.
Assistive technology : the official journal of RESNA
May 4, 2025
The aim of this scoping review was to gather, summarize, and map the knowledge of peoples' experiences on humanoid robots, capable of assisting people with activities of daily living. The review was guided by the framework of Joanna Briggs Institute ...
Sleep efficiency in community-dwelling persons living with dementia: exploratory analysis using machine learning.
Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine
Feb 1, 2025
STUDY OBJECTIVES: Sleep disturbances lead to negative health outcomes and caregiver burden, particularly in community settings. This study aimed to investigate a predictive model for sleep efficiency and its associated features in older adults living...
Performance on Activities of Daily Living and User Experience When Using Artificial Intelligence by Individuals With Vision Impairment.
Translational vision science & technology
Jan 2, 2025
PURPOSE: This study assessed objective performance, usability, and acceptance of artificial intelligence (AI) by people with vision impairment. The goal was to provide evidence-based data to enhance technology selection for people with vision loss (P...
Urban-rural disparities in fall risk among older Chinese adults: insights from machine learning-based predictive models.
Frontiers in public health
Jan 1, 2025
BACKGROUND: Falls among older adults are a significant challenge to global healthy aging. Identifying key factors and differences in fall risks, along with developing predictive models, is essential for differentiated and precise interventions in Chi...
Revolutionizing health monitoring: Integrating transformer models with multi-head attention for precise human activity recognition using wearable devices.
Technology and health care : official journal of the European Society for Engineering and Medicine
Jan 1, 2025
BACKGROUND: A daily activity routine is vital for overall health and well-being, supporting physical and mental fitness. Consistent physical activity is linked to a multitude of benefits for the body, mind, and emotions, playing a key role in raising...
Effect of Upper Robot-Assisted Training on Upper Limb Motor, Daily Life Activities, and Muscular Tone in Patients With Stroke: A Systematic Review and Meta-Analysis.
Brain and behavior
Nov 1, 2024
BACKGROUND: Upper limb rehabilitation robot is a relatively new technology, but its effectiveness remains debatable due to the inconsistent results of clinical trials. This article intends to assess how upper limb rehabilitation robots help the funct...
Enhanced In-Home Human Activity Recognition Using Multimodal Sensing and Spatiotemporal Machine Learning Architecture.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
In this research, we present an enhanced human activity recognition (HAR) framework using advanced machine learning models incorporating temporal dynamics, leveraging multimodal sensor data. Data from wearable wristbands and real-time location system...
ECG-based Daily Activity Recognition Using 1D Convolutional Neural Networks.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
This study presents an approach to human activity recognition (HAR) using electrocardiogram (ECG) signals. We explore the application of ECG for not only providing cardiophysiological information but also for more extensive patient surveillance, incl...
Using natural language processing to link patients' narratives to visual capabilities and sentiments.
Optometry and vision science : official publication of the American Academy of Optometry
Jun 1, 2024
SIGNIFICANCE: Analyzing narratives in patients' medical records using a framework that combines natural language processing (NLP) and machine learning may help uncover the underlying patterns of patients' visual capabilities and challenges that they ...
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