AIMC Topic: Adult

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A comparison of accuracy of fall detection algorithms (threshold-based vs. machine learning) using waist-mounted tri-axial accelerometer signals from a comprehensive set of falls and non-fall trials.

Medical & biological engineering & computing
Falls are the leading cause of injury-related morbidity and mortality among older adults. Over 90 % of hip and wrist fractures and 60 % of traumatic brain injuries in older adults are due to falls. Another serious consequence of falls among older adu...

Hybrid EANN-EA System for the Primary Estimation of Cardiometabolic Risk.

Journal of medical systems
The most important part of the early prevention of atherosclerosis and cardiovascular diseases is the estimation of the cardiometabolic risk (CMR). The CMR estimation can be divided into two phases. The first phase is called primary estimation of CMR...

Using machine learning to identify structural breaks in single-group interrupted time series designs.

Journal of evaluation in clinical practice
RATIONALE, AIMS AND OBJECTIVES: Single-group interrupted time series analysis (ITSA) is a popular evaluation methodology in which a single unit of observation is being studied, the outcome variable is serially ordered as a time series and the interve...

Use of machine learning to improve autism screening and diagnostic instruments: effectiveness, efficiency, and multi-instrument fusion.

Journal of child psychology and psychiatry, and allied disciplines
BACKGROUND: Machine learning (ML) provides novel opportunities for human behavior research and clinical translation, yet its application can have noted pitfalls (Bone et al., 2015). In this work, we fastidiously utilize ML to derive autism spectrum d...

Respiratory Artefact Removal in Forced Oscillation Measurements: A Machine Learning Approach.

IEEE transactions on bio-medical engineering
GOAL: Respiratory artefact removal for the forced oscillation technique can be treated as an anomaly detection problem. Manual removal is currently considered the gold standard, but this approach is laborious and subjective. Most existing automated t...

An intelligent rollator for mobility impaired persons, especially stroke patients.

Journal of medical engineering & technology
An intelligent rollator (IRO) was developed that aims at obstacle detection and guidance to avoid collisions and accidental falls. The IRO is a retrofit four-wheeled rollator with an embedded computer, two solenoid brakes, rotation sensors on the whe...

Accuracy of Component Placement in Robotic-Assisted Total Hip Arthroplasty.

Orthopedics
Robotic-assisted total hip arthroplasty (THA) is a recent platform introduced to decrease the risk of malpositioned components. The goals of this study were to determine whether intraoperative data on robotic-assisted THA acetabular component positio...

Task-specific feature extraction and classification of fMRI volumes using a deep neural network initialized with a deep belief network: Evaluation using sensorimotor tasks.

NeuroImage
Feedforward deep neural networks (DNNs), artificial neural networks with multiple hidden layers, have recently demonstrated a record-breaking performance in multiple areas of applications in computer vision and speech processing. Following the succes...

An EEG-Based Fuzzy Probability Model for Early Diagnosis of Alzheimer's Disease.

Journal of medical systems
Alzheimer's disease is a degenerative brain disease that results in cardinal memory deterioration and significant cognitive impairments. The early treatment of Alzheimer's disease can significantly reduce deterioration. Early diagnosis is difficult, ...