AIMC Topic: Adult

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Analyzing brain structural differences associated with categories of blood pressure in adults using empirical kernel mapping-based kernel ELM.

Biomedical engineering online
BACKGROUND: Hypertension increases the risk of angiocardiopathy and cognitive disorder. Blood pressure has four categories: normal, elevated, hypertension stage 1 and hypertension stage 2. The quantitative analysis of hypertension helps determine dis...

Deep learning approaches for plethysmography signal quality assessment in the presence of atrial fibrillation.

Physiological measurement
OBJECTIVE: Photoplethysmography (PPG) monitoring has been implemented in many portable and wearable devices we use daily for health and fitness tracking. Its simplicity and cost-effectiveness has enabled a variety of biomedical applications, such as ...

A Deep Transfer Learning Approach to Reducing the Effect of Electrode Shift in EMG Pattern Recognition-Based Control.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
An important barrier to commercialization of pattern recognition myoelectric control of prostheses is the lack of robustness to confounding factors such as electrode shift, skin impedance variations, and learning effects. To overcome this challenge, ...

Highest ambulatory speed using Lokomat gait training for individuals with a motor-complete spinal cord injury: a clinical pilot study.

Acta neurochirurgica
BACKGROUND: Motor impairment and loss of ambulatory function are major consequences of a spinal cord injury (SCI). Exoskeletons are robotic devices that allow SCI patients with limited ambulatory function to walk. The mean walking speed of SCI patien...

Prediction of Lower Limb Kinetics and Kinematics during Walking by a Single IMU on the Lower Back Using Machine Learning.

Sensors (Basel, Switzerland)
Recent studies have reported the application of artificial neural network (ANN) techniques on data of inertial measurement units (IMUs) to predict ground reaction forces (GRFs), which could serve as quantitative indicators of sports performance or re...

Development and validation of a machine learning, smartphone-based tonometer.

The British journal of ophthalmology
BACKGROUND/AIMS: To compare intraocular pressure (IOP) measurements using a prototype smartphone tonometer with other tonometers used in clinical practice.

Natural language processing for automated detection of incidental durotomy.

The spine journal : official journal of the North American Spine Society
BACKGROUND: Incidental durotomy is a common intraoperative complication during spine surgery with potential implications for postoperative recovery, patient-reported outcomes, length of stay, and costs. To our knowledge, there are no processes availa...

Application of Machine Learning for Predicting Clinically Meaningful Outcome After Arthroscopic Femoroacetabular Impingement Surgery.

The American journal of sports medicine
BACKGROUND: Hip arthroscopy has become an important tool for surgical treatment of intra-articular hip pathology. Predictive models for clinically meaningful outcomes in patients undergoing hip arthroscopy for femoroacetabular impingement syndrome (F...

The Interaction Between Feedback Type and Learning in Routine Grasping With Myoelectric Prostheses.

IEEE transactions on haptics
While prosthetic fitting after upper-limb loss allows for restoration of motor functions, it deprives the amputee of tactile sensations that are essential for grasp control in able-bodied subjects. Therefore, it is commonly assumed that restoring the...

Mild Dehydration Identification Using Machine Learning to Assess Autonomic Responses to Cognitive Stress.

Nutrients
The feasibility of detecting mild dehydration by using autonomic responses to cognitive stress was studied. To induce cognitive stress, subjects ( = 17) performed the Stroop task, which comprised four minutes of rest and four minutes of test. Nine in...