Research
Upper-extremity Function (UEF) - Assessing Physical and Cognitive Frailty in Older adults
This research seeks to change current risk stratification and adverse health outcomes prediction paradigms among older adults, by utilizing novel biomechanical approaches and wearable sensor technology. Using this test we are able to objectively assess:
1- Frailty
(please visit our website for more information: https://aging.arizona.edu/upper-extremity-function-assessment):
Treatment Evaluation (Patient-centered Studies)
The main purpose of the series of studies are to 1) evaluate motor performance enhancement following clinical treatments; 2) predict treatment failure using baseline function measures
1- Parkinson's disease: Effect of electro-acupuncture, in-home and in-clinic assessment of motor performance
2- Degenerative facet osteoarthropathy: Effect of paravertebral spinal injection
3- Peripheral artery disease: frailty and gait impairments
Treatment Evaluation (Patient-centered Studies)
The main purpose of the series of studies are to 1) evaluate motor performance enhancement following clinical treatments; 2) predict treatment failure using baseline function measures
1- Parkinson's disease: Effect of electro-acupuncture, in-home and in-clinic assessment of motor performance
2- Degenerative facet osteoarthropathy: Effect of paravertebral spinal injection
3- Peripheral artery disease: frailty and gait impairments
Fall Risk Assessment and Fall Prevention
Vibratory stimulation will disturb postural balance among those with normal sensory performance; however, it will not influence those with high fall risk with sensory deficits (or may even improve it), because of aging-induced alterations in muscle spindle sensory function and slowed nerve conduction. The purpose is to:
2- Develop a lower-extremity vibratory stimulation device that improves gait and postural balance among elders at high fall risk (in progress).
Early Diagnosis of the Alzheimer’s Disease using Functional Brain Imaging
In this research we assess functional differences in the aging brain (≥65 years) between groups of cognitively normal, amnestic mild cognitively impaired (aMCI), and early stage AD patients, with the goal of early detection of AD using fMRI image processing, functional near-infrared spectroscopy (fNIRS), and machine learning techniques (in progress).
1- Brain function complexity is associated with cognitive impairment
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Heart Rate Dynamic Measures to Predict Frailty in Heart Disease
Despite advances in the clinical treatment procedures, advanced heart disease remains one of the leading cause of death in the United States. One main reason for the lack of optimal healthcare performance for treating these patients is the inefficiency in predicting clinical outcomes related to frailty. In this research, we develop and validate a novel objective sensor-based approach in combination with machine learning approaches to characterize heart behavior in response to a localized rapid upper-extremity function task, among older adults with advanced heart disease to predict therapy outcomes and reversible frailty (in progress). Some of our recent findings are presented here:
1- Frailty Assessment Using Combined Motor and Cardiac Functions
2- Frailty Identification using Heart Rate Dynamics and Deep Learning
3- The association between heart rate behavior and gait performance
Low Back Disorders (LBDs)
To investigate the risk of LBDs due to prolonged and/or repetitive loadings, we developed a time-dependent finite element model with viscoelastic properties. Using this model we were able to:
1- Describe trunk load-relaxation and creep behaviors
2- Predict changes in spine loads following trunk flexion exposures
3- Understand dependency of spine loads on prior flexion angles and loading conditions
