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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

2- Cognitive Impairments

3- Functional Capacity 

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 may improve it in high fall risk older adult, because of aging-induced alterations in muscle spindle sensory function. The purpose is to:

1- Validate an objective stimulation-based balance test for assessing fall risk among community-dwelling older adults using novel biomechanical approaches, vibratory stimulation, and wearable sensors.

2- Understand the contribution of ankle vs. hip muscle proprioceptive information in balance recovery.

3- Develop a lower-extremity vibratory stimulation device that improves gait and postural balance among elders at high fall risk (in progress).

Sensor-based Real-time Tracking-Game (SRT) 

We establish a novel Sensor-based Real-time Tracking-game (SRT), which is based on tracking a flying target by ankle movements using a smartwatch on the foot and a smartphone/tablet. By measuring the amplitude and directional accuracy during the tracking, we engage ankle proprioceptive function based on correction mechanism of tracking error through the open-loop reflexive responses and closed-loop adjustment within the central nervous system. SRT incorporates combined anterior-posterior and medial-lateral ankle maneuvers to replicate realistic real-life sensation experiences. 

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 Dynamics to Predict Frailty in Heart Disease

One main reason for the lack of optimal healthcare performance for treating heart disease patients is the inefficiency in predicting clinical outcomes related to frailty. In this research, we develop 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:

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 

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